U5

Question 1

As its name suggests, “big data” is huge and fast-growing data. Big data initially:

With the dramatic increase in data, database costs, e.g., hardware, software, and operating costs, have accordingly increased. Hence,

Answer 1

attributed to search engines and social networks is now making its way into enterprises.

Question 2

There exist several challenges while working with big data, including?

Answer 2

how to store it and how to process it.

Question 3

Among these challenges is enabling the databases to meet the needs of?

Answer 3

high concurrent reading and writing with low latency.

Question 4

there is an immense need to lower the costs of storing big data?

Answer 4

Because, with the dramatic increase in data, database costs,
e.g., hardware,
software,
and operating costs,
have accordingly increased.

Question 5

The traditional relational databases, e.g., structured query language (SQL), are a?

Answer 5

collection of data items with pre-defined relationships between them.

Question 6

These items are organized as a set of tables with:

Answer 6

columns and rows.

Question 7

Unfortunately, these relational databases have some inherent limitations which emerge with:

Answer 7

the rapid growth of data.

Question 8

In these cases, relational databases are:

Answer 8

widely prone to deadlocks and other concurrency issues.

Question 9

These situations lead to rapid declines in?

Answer 9

the efficiency of reading and writing.

Question 10

Furthermore, the multi-table correlation mechanism that exists in —————————————-represents a major limitation of database scalability. To overcome these problems, ——————–databases were proposed instead of the traditional database. NoSQL is an —————–term for ——————- databases which do not use the SQL structure.

Answer 10

relational database

NoSQL

umbrella

non-relational

Question 11

NoSQL databases are useful for ?

Answer 11

applications that deal with very large semi-structured and unstructured data.

Question 12

Unlike relational databases, NoSQL databases are designed to ?

Answer 12

scale horizontally and can be hosted on a cluster of processors.

Question 13

In most of these databases, each row is a ?

Answer 13

key-value pair.

Question 14

NoSQL databases contains truly elastic databases, e.g., MongoDB and Cassandra, which allows?

Answer 14

the addition/removal of nodes to/from a cluster without any observable down-time for the clients.

Question 15

To this end, routing algorithms are used to decide when to move the inter-related data chunks, for instance, ?

Answer 15

when data must be moved to newly added node B. During the copying process, the data is served from the original node A. When the new node B has an up-to-date version of the data, the routing processes start to send requests to the node B.

Question 16

In general, there are some important aspects related to distributed databases that need to be thoroughly addressed, including :

Answer 16

scalability,
availability,
and consistency.

Question 17

First, scaling is typically achieved through?

Answer 17

“sharding” to meet the data volume.

Question 18

Sharding is ?

Answer 18

a type of database partitioning that separates very large databases into smaller, faster, more easily managed parts, referred to as data shards.

Question 19

NoSQL databases support an auto-sharding mode in which?

Answer 19

the shards are automatically balanced across the nodes on a cluster.

Question 20

Additional nodes can be easily added as ?

Answer 20

necessary to the cluster to align with data volume.

Question 21

Second, availability can be achieved via replication, i.e., ?

Answer 21

master-slave replication or peer-to-peer replication.

Question 22

With master-slave replication, two types of nodes are typically implemented including:

Answer 22

a master node where all the write operations go to the master node.

Question 23

Data can be read from any node, either a —————————– If a master node goes down, a slave node gets promoted to a ————–, and continues to replicate to the —————.

Answer 23

master or a slave.

master node
third node

Question 24

When a failed master node is resurrected, it joins the cluster as a slave. Alternatively,?

Answer 24

peer-to-peer replication is slightly complex where all the nodes receive read/write requests.

Question 25

In terms of consistency, two major types of inconsistencies exist:

Answer 25

read and write.

Question 26

Read inconsistencies arise in ————————- replication when a user tries to read of a —————– before changes propagate from the ———————–, while in —————————- replication the user runs into both read and write inconsistencies, as write (update) is allowed on —————-s.

Answer 26

master/slave

slave

master node

peer-to-peer

multiple node

Question 27

It is obvious that availability and consistency are ?

Answer 27

two contradicting metrics.

Question 28

Achieving the right balance between these metrics highly depends on ?

Answer 28

the nature of the IoT application.

Question 29

For example,

Answer 29

a user can prohibit read and write inconsistencies through considering slaves as hot standby without reading from them.

Question 30

MongoDB is a prominent example of a document-oriented, scalable NoSQL database system which has?

Answer 30

a powerful query language.

Question 31

MongoDB supports complex data types, e.g.,?

Answer 31

BJSON data structures.

Question 32

It allows most functions like?

Answer 32

-query in single-table of relational databases,

-and it also supports indexing.

-Furthermore, MongoDB has the advantage of supporting high-speed access to mass data.

Question 33

When the stored data exceeds 50 GB, the access speed of MongoDB is?

Answer 33

ten times higher than MySQL (Yan, 2015).

Question 34

Thanks to these characteristics, many system designers are?

Answer 34

considering MongoDB instead of relational database.

Question 35

Another example of a NoSQL database is?

Answer 35

the Apache Cassandra. It offers good scalability and high availability without compromising performance.

Question 36

Cassandra demonstrated?

Answer 36

fault-tolerance on commodity hardware (i.e., cloud infrastructures)
and linear scalability,
thus making it the ideal platform for mission-critical data.

Question 37

Cassandra features allow?

Answer 37

replication across multiple datacenters,

offering lower latency for data availability during regional outages.

Question 38

With Cassandra, columns can be easily indexed with ?

Answer 38

powerful built-in caching mechanism.

Question 39

Netflix, Twitter, Urban Airship, Reddit, Cisco, OpenX, and Digg are examples of the companies that use?

Answer 39

Cassandra to deal with huge, active, online interactive datasets.

Question 40

The largest known Cassandra cluster has over?

Answer 40

300 TB (terabytes) of information in over 400 machines.

Question 41

Processing a massive amount of data, i.e., big data, demands?

Answer 41

a shift from the client server model of data processing where a client node pulls the data from a server node.

Question 42

Instead, data can be processed on the ————————————-. In addition, this processing can be carried out independently in parallel as the underlying data is already ————————–across different nodes.

Answer 42

cluster nodes

partitioned

Question 43

This approach of data processing is referred to as ?

Answer 43

the MapReduce framework and it also interestingly uses key-value pairs.

Question 44

MapReduce makes use of hundreds or even thousands of “pluggable” nodes in a cluster to?

Answer 44

process data in parallel, which significantly shortens the time between the operational events and presenting the analytics results.

Question 45

The ——————————– framework offers an effective method for the efficient analysis of the collected ————-data, especially when the computations involve linearly computable ———–functions over the elements of the data streams, e.g.,
——————————————————-.

Answer 45

MapReduce

sensor

statistical

MIN, MAX, SUM, and MEAN

Question 46

Google’s original MapReduce framework was designed for ?

Therefore, this framework represents an ideal candidate for sensor data analytics. The figure below demonstrates the MapReduce architecture for processing sensor data in parallel on different processing nodes.

Answer 46

analyzing large amounts of web logs, and more specifically deriving such linearly computable statistics from the logs.

Question 47

In fact, the sensor-generated data has many conceptual similarities to web logs. Specifically,?

Answer 47

they are similarly repetitive, and the typical statistical computations which are often performed on sensor data for many applications are linear in nature.

Question 48

this framework represents an ideal candidate for sensor data analytics?

Answer 48

the sensor-generated data are often performed on sensor data for many applications are linear in nature.

Question 49

The figure below demonstrates the MapReduce architecture for processing sensor data in parallel on different processing nodes.

Question 50

To understand the MapReduce framework, consider a case where?

the data can be in the form of (year, value) where the year is the key. The Map function takes a list of pairs (year, value) from one domain and then returns a list of pairs (year, local max value). The local max value denotes the local maximum in the subset of the data processed by that node. This computation is typically performed in parallel by dividing the key value pairs across different distributed computers.

Answer 50

the maximum temperature each year is to be determined from sensor data recorded over a long period of time.

To this end, the “Map” and “Reduce” functions of MapReduce are defined with respect to data structured in (key, value) pairs.

Question 51

For example,

Answer 51

the data can be in the form of (year, value) where the year is the key.
The Map function takes a list of pairs (year, value) from one domain and then returns a list of pairs (year, local max value).
The local max value denotes the local maximum in the subset of the data processed by that node.
This computation is typically performed in parallel by dividing the key value pairs across different distributed computers.

Question 52

Subsequently, the MapReduce framework combines ?

Answer 52

all pairs with the same key from all lists, thus creating one group for each one of the different generated keys.

Question 53

This grouping step requires ——————-between the different ———————–. However, the cost of this communication is much lower than moving the——————————- around because the ———– has already generated a —————- summary of the processed data.

Answer 53

communication

computers

original data
Map step
compact

Question 54

It is worth mentioning that the exact implementation of the Map step widely depends upon?

Answer 54

the implementation of the adopted MapReduce,

and also on the exact nature of the distributed data.

Question 55

For instance, the sensor data may be distributed over a local cluster of computers (with the use of an implementation such as Hadoop). An alternative solution is to geographically distribute the sensor data because?

Answer 55

the data is originally created at different locations, and it is too expensive to move the data around.

Question 56

The latter scenario is much more suited for —— applications. Nevertheless, the steps for collecting the intermediate results from the different Map steps may depend upon the specific ———————————————– in which the MapReduce framework is —————–.

Answer 56

IoT

implementation and scenario

utilized

Question 57

After performing the grouping step, the Reduce function is applied in?

Answer 57

parallel to each group.

Question 58

Such a step generates a collection of?

Answer 58

values in the same domain.

Question 59

Next, we apply Reduce —————- in order to create list————.

Answer 59

(k2, list(V2))

(v3)

Question 60

Each execution of the Reduce function returns only one value, although it is also?

Answer 60

possible for the function to return more than one value.

Question 61

For instance,

Answer 61

the input to the “Reduce” function will be a list in the form (Year [local max1, local max2, …, local maxr]),

where the local maximum values are determined by the execution of the different Map functions.

The Reduce function determines the maximum value over the corresponding list in each call of the Reduce function.

Question 62

A Hadoop client typically submits jobs to the MapReduce framework through what is called?

Answer 62

the “jobtracker” running on the master server.

Question 63

Subsequently, the ————————— automatically assigns the jobs to ————————— running on many —————————–.

Answer 63

jobtracker

“tasktrackers”

slave nodes

Question 64

The tasktrackers regularly send heartbeats to the jobtracker to update the status, e.g.,?

Answer 64

alive, idle or busy.

Question 65

If a job fails or timeouts, or a node is dead, the jobtracker can automatically reschedule ?

Answer 65

the jobs to run on available nodes.

Question 66

In general, HDFS comprises two components, namely ?

Answer 66

name-nodes
and data-nodes.

Question 67

A name-node is?

Answer 67

responsible for keeping the metadata about the data on each data-node.

Question 68

When a client application reads or writes data into HDFS, it must communicate with?

Answer 68

the name-node to get the locations of data block to be read from or written to.

Question 69

The metadata is read into main memory when ?

Answer 69

Hadoop starts, and is dynamically maintained.

Question 70

A data-node updates name-node the metadata of its local data blocks through?

Answer 70

heart beats.

Question 71

Hadoop also has?

Answer 71

a secondary name-node mainly used to store the latest checkpoints of HDFS states.

Question 72

Although the Hadoop MapReduce framework has the goal of
high scalability
and better fault-tolerance,
it is not ?

Answer 72

optimized for input/output efficiency. Specifically, both the Map and Reduce functions are “block operations” in which data transition cannot proceed to the next stage until the tasks of the current stage have finished.

Question 73

Accordingly, the output of mappers needs to be ?

Answer 73

first written into HDFS before shuffled to the reducers.

Question 74

Such blocking, the one-to-one shuffling strategy, and the runtime scheduling ?

Answer 74

degrade the performance of each node.

Question 75

The MapReduce framework lacks:

Answer 75

a database management system
and does not optimize data transferring across various nodes.

Question 76

it is more suitable for batch jobs than real-time processing.

Answer 76

Because Hadoop has a latency problem due to its inherent nature.

Question 77

Large-scale IoT applications,
e.g.,traffic monitoring,
weather forecasting,
homeland security,
entertainment,
and disaster response, often have ?

Answer 77

the challenge of capturing too much data with too little inter-operability.

Question 78

Such challenges are accompanied with ?

Answer 78

too little knowledge about the ability to utilize different resources which are available in real time.

Question 79

To overcome these challenges, the Sensor Web Enablement initiative ?

Answer 79

defines service interfaces which enable developers to make all types of sensors, transducers, and sensor data repositories discoverable, accessible, and usable via the Web.

Question 80

Such standardized interfaces are extremely beneficial since?

Answer 80

they hide the heterogeneity of the underlying IoT devices from the applications that use them.

Question 81

In this context, the term “Sensor Web” defines ?

Answer 81

an infrastructure enabling access to IoT devices and archived sensor data.

Question 82

Such data can readily be discovered and accessed using ———————————————–. The goal of the Sensor Web is to enable real-time “———————” in order to ensure timely ——————— to a wide variety of events.

Answer 82

standard protocols and APIs

situation awareness

responses

Question 83

The major benfits of the IoT sensor data can only be realized if we have?

Answer 83

the infrastructure and mechanisms to synthesize, interpret, and apply this data intelligently via automated means.

Question 84

The Sensor Web enables automated applications to
understand,
interpret,
and reason with basic but critical semantic notions such as ?

Answer 84

“nearby,” “far,” “soon,” “immediately,” “dangerously high,” “safe,” “blocked,” or “smooth.” Ontologies are at the heart of the semantic sensor web technology.

Question 85

An ontology is a mechanism for ?

resources, the Resource Description Framework (RDF) data model is widely used to describe resources.

Answer 85

knowledge sharing and reuse.

Question 86

Ontologies are generally knowledge representation systems. To represent ?

Answer 86

resources, the Resource Description Framework (RDF) data model is widely used to describe resources.

Question 87

Literally, a resource is ?

Answer 87

any device or concept, e.g., person, place, restaurant. Each resource is uniquely identified by a URI.

Question 88

Aside from describing resources, RDFs are capable of ?

Answer 88

specifying how resources are inter-related through performing inference.

Question 89

The building blocks of RDF are triples, where a triple is?

Answer 89

a 3-tuple of the form <subject, predicate, object> where subject, predicate, and object are interpreted as in a natural language sentence.

Question 90

It is most helpful to perceive RDF as a
———–, where subject resources are represented in ———, literals in ————, and predicate (relationships) represented as directed ————————- or between ———————————.

Answer 90

graph
ovals
rectangles
edges between ovals
ovals and rectangles

Question 91

For instance,

Answer 91

the triple representation of the sentence, “Washington, D.C. is the capital of the United States,” is illustrated in the following figure.

Question 92

The Web Ontology Language (OWL) is ?

Answer 92

another ontology formalism that was developed to overcome the drawbacks of RDF.
Specifically, RDFs do not provide ways to represent constraints,
e.g., domain or range constraints.

Question 93

Furthermore, ————————————————————- cannot be represented in RDF data model.

Answer 93

transitive or inverse properties

Question 94

Extending RDF(s) makes it straightforward to provide?

Answer 94

a formal specification in OWL.

Question 95

Both RDF and OWL ontology formats have extensive developer community support in terms of?

Answer 95

the availability of tools for ontology creation and authoring.

Question 96

An example is ?

Answer 96

Protege, which supports RDF and OWL formats, data storage, and management stores, such as
OpenSesame, for efficient storage and querying of data in RDF or OWL formats.

Question 97

Furthermore, there is significant availability of actual ontologies in a variety of domains in the —————————- formats.

Answer 97

RDF and OWL

Question 98

The Semantic Sensor Network (SSN) is an example of ?

Answer 98

an ontology which relies on the OWL data model to describe sensors and observations.

Question 99

It describes the IoT sensors in terms of ?

Answer 99

their capabilities,
measurement processes,
observations,
and deployments.

Question 100

The SSN ontology is conceptually organized into ———————–. In fact, the ontology can be seen from ———- main perspectives, namely ?

Answer 100

ten modules
four

sensor perspective,
observation perspective,
system perspective,
and feature and property perspective.

Question 101

The full ontology consists of?

Answer 101

41 concepts and 39 object properties.

Question 102

The ontology can describe?

Answer 102

sensors,
the accuracy and capabilities of such sensors,
observations,
and methods used for sensing.

Question 103

Concepts for operating and survival ranges are also included, as?

Answer 103

these are often part of a given specification for a sensor, along with its performance within those ranges.

Question 104

Finally, a structure for field deployments is included to?

Answer 104

describe deployment lifetimes and sensing purposes of the deployed macro instrument.

Question 105

To achieve automatic processing and interpretation of the IoT data, we need ?

Answer 105

common agreements on providing and describing the IoT data.

Question 106

To evaluate the quality aspects of data, the source provider,
device,
and environment-specific information also need to be?

Answer 106

associated to the data.

Question 107

Considering the diversity of data types, device types, and potential providers in the IoT domain, common description frameworks are essential to ?

Answer 107

describe
and represent the data to make it seamlessly accessible
and processable across heterogeneous platforms.

Question 108

Considering the diversity of data types, device types, and potential providers in the IoT domain, common description frameworks are essential to ?

Answer 108

describe
and represent the data to make it seamlessly accessible
and processable across heterogeneous platforms.

Question 109

The semantic descriptions and annotations must be provided at different layers of the IoT framework, including:

the “Things” level, device,
and network level (e.g., SSN ontology), and the interaction and business process

model to?

Answer 109

enable autonomous processing and interpretation of the IoT data.

Question 110

In fact, the effective discovery, access, and utilization of the IoT resource require?

Answer 110

machine-interpretable descriptions of different components and resources in the IoT framework,

e.g., sensors, actuators, and network resources.

Question 111

The current Semantic Web technologies and ontologies can efficiently describe various aspects of?

Answer 111

the IoT data and resources.

Question 112

Description models and representation frameworks that can describe the IoT data and services need to consider the constraints and dynamicity of the IoT domain.

Answer 112

Since IoT environments are often dynamic and pervasive,

Question 113

In this context, the concept of “linked data” emerges to connect?

Answer 113

individual data items to support semantic query and inferences on the data coming from the physical and virtual objects.

In other words,
linked data simply refers to data published on the Web in such a way that it is machine-readable, its meaning is explicitly defined, and it is readily linked to other external data sets.

Question 114

The linked data, represented using formal knowledge representation ———————such as ——————————, provides potential for information reuse and ———-among ———————-sources. The information published for the linked data is typically structured and connected to one another.

Answer 114

formalism

RDF and OWL

interoperability

heterogeneous

Question 115

In general, publishing linked data widely encourages the reuse?

(1) using URIs as names for data; (2) providing HTTP access to those URIs; (3) providing useful information for URIs using the standards such as RDF and SPARQL; and finally (4) including links to other URIs.

Answer 115

of existing information rather than creating new information.

Question 116

This implies that human users can exploit the existing knowledge base by?

Answer 116

simply providing links to the data in it.

Question 117

For instance,

Answer 117

the DBpedia project
-extracts structured information from Wikipedia.
-DBpedia enables sophisticated queries over the information that exists in Wikipedia.
- Moreover, it provides new ways of browsing and navigation through the semantic links.

Question 118

Nevertheless, semantic descriptions without being linked to other existing data on the Web would be mostly?

Answer 118

processed locally and according to the domain descriptions (i.e., ontologies) and their properties.

Question 119

The linked data offers four main principles to publish linked-data:

Answer 119

(1) using URIs as names for data;
(2) providing HTTP access to those URIs; (3) providing useful information for URIs using the standards such as RDF and SPARQL; and finally
(4) including links to other URIs.

Question 120

In fact, the emergence of sensor data as linked data enables IoT applications and sensor network providers to?

Answer 120

connect sensor descriptions to potentially endless data existing on the Web.

Specifically, the action of relating sensor data attributes, such as location, type, and measurement features, to the other resources on the Web of data enables the users to integrate physical world data and the logical world data.

Question 121

The results of such an integration are:

Answer 121

drawing beneficial conclusions,
creating business intelligence,
enabling smart environments,
and supporting automated decision-making systems.

Question 122

In order to get the most out of the integration of IoT and cloud computing, the use of ?

Answer 122

microservices is recommended.

Question 123

Microservices represent an architectural approach for developing applications as a set of small services, where?

Answer 123

each service is running as a separate process, communicating through simple mechanisms .

Question 124

Most of the advantages of the microservices architecture stem from ?

Answer 124

decomposing a service or an application into smaller components, i.e., microservices.

Question 125

Each of these components should implement a specific functionality. As a result, :

Answer 125

we can independently develop,
deploy,
upgrade,
and scale every microservice.

Question 126

each microservice can be separately scaled?

Answer 126

Since the different microservices may have different workloads.

Question 127

Accordingly, we can?

Answer 127

-use an optimal amount of resources making microservices architecture a natural fit for achieving both scalability and elasticity.

-We can separately control every microservice where they are easily manageable thanks to being small.

Question 128

Developing microservices separately enables?

Answer 128

the employment of different technologies, e.g., different programming languages for each microservice

Question 129

Furthermore, the task of releasing an update for a part of our application or service does not require?

Answer 129

the redeployment of the whole application,

but only
the corresponding microservice.

Question 130

Microservices often communicate through web services, such as:

Answer 130

REST,
or through remote procedure calls (RPC).

Question 131

there is a need to reduce the communication between the different microservices to the minimum. ?

Answer 131

as communication between processes may become costly.

Question 132

The advantages of microservices architecture are best identified when?

Answer 132

we compare it to the traditional monolithic architecture.

Question 133

Monolithic application has all of its components packed together.
For instance,

Answer 133

monolithic web applications have the client-side,
the server-side
, and the database in a single logical executable.
Similarly, monolithic IoT applications have the whole logic for communication with IoT devices,
processing of devices’ data, communication with databases,
and visualization, in a single logical executable.

Question 134

To achieve scalability and elasticity in monolithic applications, more instances of the whole application must be?

Answer 134

deployed or terminated. However, different application functionalities rarely have an equal share of the workload.

Question 135

Alternatively, every microservice is packed as?

Answer 135

an independent component in the microservices approach.

Question 136

We can scale every —————————-independently and change the number of instances for each microservice separately. In this context, the application ———————–can be controlled according to the workload of each of the microservices. To summarize, microservices —————————————————— application development.

Answer 136

microservice

scalability

enable a scalable
elastic,
and resource-efficient

Question 137

Another major difference between microservices and monolithic architecture is that?

a change in how an application communicates with IoT devices and receives data from them must have no impact or only minimal impact on how we process the data. Therefore, we should “componentize” the application into microservices in a way that would allow for the communication between microservices to be minimal.

Answer 137

the latter usually runs as a single process.

Question 138

If we want to release an update of the application, the whole application must be?

Answer 138

redeployed for the changes to take effect;

Question 139

it does not matter which component we have changed. With microservices, the update of one microservice has to cause?

Answer 139

no changes or only minor changes to the other microservices.

Question 140

In this realm, we can highlight a potential challenge of the microservices approach. As mentioned previously, the communication between components is?

Answer 140

relatively expensive and has to be deliberately minimized.

Question 141

If a change in a single microservice imposes many changes in other microservices, ?

Answer 141

the advantages of the microservices architecture might be lost.

Question 142

For instance,

we should “componentize” the application into microservices in a way that would allow for the communication between microservices to be minimal?

Answer 142

Because a change in how an application communicates with IoT devices and receives data from them must have no impact or only minimal impact on how we process the data.

Question 143

In some applications, the monolithic architecture could become excessively large. In these cases, several drawbacks emerge, such as:

if a microservice which communicates with a certain group of sensors crashes, such a crash will not affect or stop the processing of the data provided by microservices which communicate with other sensors. The other components of the application will still be up and properly running.

Answer 143

the difficulty of software management, being more vulnerable, and being harder to update.

Question 144

Bugs in monolithic applications could be expensive,?

Answer 144

as they cause the whole application to crash, whereas in microservices architecture only the corresponding microservice collapse.

Question 145

Bugs in monolithic applications could be expensive, as they cause the whole application to crash, whereas in microservices architecture only the corresponding microservice collapse. In this case, the microservices-based application can continue?

Answer 145

running and only the specific functionality implemented by the malfunctioned microservice is unavailable.

Question 146

Such behavior of ———————————————-is highly important in the IoT domain. For example, ?

Answer 146

microservices-based architectures

if a microservice which communicates with a certain group of sensors crashes,

such a crash will not affect or stop the processing of the data provided by microservices

which communicate with other sensors.

The other components of the application will still be up and properly running.

Question 147

In general, IoT applications have high requirements regarding?

Answer 147

scalability.

Question 148

These scalability requirements fundamentally push toward?

Answer 148

designing distributed architectures rather than monolithic ones.

Question 149

In general, the microservices architecture is ?

Answer 149

adaptable to the requirements of IoT applications.

Question 150

When developing applications, it is generally good practice to break down the application into several ——————–. Such components that programmers frequently use are referred to as————-.

Answer 150

components

libraries

Question 151

The concept of services in microservices architecture is similar to the libraries concept with one major difference:

Answer 151

libraries are essentially linked to a main program and when the program is running, there is only one process.

On the other hand, the microservices architecture tends to componentize a project into services, where each service is running in its own separate process.

Question 152

each microservice could be deployed and scaled independently?

Answer 152

As the microservices architecture tends to componentize a project into services, where each service is running in its own separate process.

Question 153

each microservice could be deployed and scaled independently. By ?

Answer 153

componentization into microservices, the problem of vast heterogeneity of devices could be simply addressed.

Question 154

To this end, distinctive microservices can be implemented as?.

Answer 154

proxies for the IoT devices that communicate using different protocols, e.g., Wi-Fi, LoRa, BLE

Question 155

Furthermore, adding new devices, which may communicate using unsupported protocol, is usually resolved by?

Answer 155

adding a microservice acting as a proxy between protocols.

Question 156

In general, there exist two common approaches for decomposition of applications into microservices:

Answer 156

verb-based
and noun-based strategies.

Question 157

The former strategy deals with the ——–of an application around single use cases. Such a decomposition strategy is ————- for —— applications.

Answer 157

decomposition
ill-suited
IoT

Question 158

If we are dealing with multiple groups of devices, we might group the logic for communication with certain type of devices, e.g.,?

Answer 158

temperature sensors, the data processing logic, and the visualization logic for this certain group of sensors in one microservice.

Question 159

In fact, the approach is not a natural fit for IoT applications, ?

Answer 159

as the scaling of different modules is dependent upon different factors.

Question 160

For instance:

Answer 160

The communication with devices is most dependent upon the number of devices and the amount of data they generate, while the visualization application must consider the number of users which access it simultaneously.

Question 161

In the noun-based decomposition, a microservice is responsible for?

Answer 161

every operation related to a certain functionality.

Question 162

A single microservice communicates with ? data visualization.

Answer 162

the devices and exchanges data with them

Question 163

a second microservice processes the data, e.g., ?

Answer 163

CEP engine;

Question 164

a third microservice might store the data in ?

Answer 164

a database for later processing;

Question 165

and finally, a fourth microservice might be responsible for?

Answer 165

data visualization.

Question 166

Such a decomposition leads to the design of a dynamic application, where ?

Answer 166

each functionality can be separately scaled.

Question 167

A combination of the verb-based and noun-based approach is also ?

Answer 167

possible.

Question 168

fault tolerance can be easily considered?

Answer 168

Since microservices are independent components.

Question 169

The microservices architecture brings more freedom for?

Answer 169

deployment and management of applications in cloud infrastructures.

Question 170

For a scalable IoT application, every microservice must use?

Answer 170

an optimal amount of resources.

Question 171

To this end, microservices typically employ the platform as ?

Answer 171

a service (PaaS) cloud computing mode.

Question 172

PaaS offers a platform, which is responsible for?

Answer 172

low-level operations like management of virtual machines (VMs), application deployment, load balancing, etc.

Question 173

PaaS enables :

Answer 173

easier management of applications

and is especially suitable for microservices.

It enables system designers to focus on the IoT aspect and not on the essential low-level part of the application.

Question 174

On the contrary, it is naturally hardly to find a PaaS provider that supports ?

Answer 174

monolithic applications.

Question 175

In case of a monolithic application, system designers need to?

Answer 175

perform the job of configuration and management of the application.

Question 176

The first scaling strategy of microservices is referred to a—————————In vertical scaling, more resources, e.g., —————————-units, are added to a single specific IoT node to incorporate additional—————- so that it can successfully handle the application requirements.

Answer 176

“vertical scaling.”

memory and CPU

capabilities

Question 177

Nevertheless, such a scaling strategy is relatively limited in?

Answer 177

its nature, as it is impractical to continuously add resources due to some physical constraints.

Question 178

the vertical approach is not common in the IoT domain, unless it is combined with other horizontal scaling approaches.?

Answer 178

Because IoT applications often deal with a huge number of events and thus require lots of resources, which a single node often cannot provide.

Question 179

The following scaling approaches are the three dimensions of a scale cube:

Answer 179

X-axis scaling
Y-axis scaling
Z-axis scaling

Question 180

X-axis ?

Answer 180

X-axis scaling is a typical horizontal scaling in which several application instances are used to distribute the workload evenly.

It is common for monolithic applications to use this kind of scaling.

Question 181

Having N instances of an application, each instance gets?

Answer 181

1/N of the workload.

Question 182

Alternatively, each microservice is ?

Answer 182

separately scaled

Question 183

PaaS environments further facilitate the scaling of microservices, as they allow us to ?

Answer 183

specify the number of instances for a specific microservice.

Some PaaS providers also offer automatic scaling, i.e., microservices are dynamically scaled depending on the current workload.

Question 184

Similarly, Y-axis scaling splits ?

Answer 184

the application into multiple, different services.
Each service is responsible for one or more closely related functions.

Question 185

In practice, a combination of X-axis and Y-axis scaling is commonly used for ?

Answer 185

scaling of IoT applications.

Question 186

In the third class of the horizontal scaling strategies, referred to as the Z-axis scaling, each server runs?

Answer 186

an identical copy of the code.

Question 187

The big difference between Z-axis and X-axis is that ?

Answer 187

each server is responsible for only a subset of the data.
Some component of the system is responsible for routing each request to the appropriate server.
A common use case where Z-axis scaling is applicable is division according to the user category.

Question 188

For example, ?

Answer 188

requests of users who have paid for a service are routed to different, more powerful servers.

Question 189

Premium users requests are not routed together with the requests of non-premium users, as higher performance must be ensured?

Answer 189

since Premium users usually have higher service level agreements (SLA) than non-premium users.

Question 190

Better performance is usually provided by?

Answer 190

less restrictive policy on the creation of new instances or redirection to more powerful instances.

Question 191

Premium users might also have access to additional services. For example, ?

Answer 191

we might process and visualize data from additional sensors, available to premium users only.

Therefore, they will be redirected to servers which are hosting these additional services.

Question 192

A component for routing might be implemented as an additional microservice.
In fact, Z-axis scaling has many benefits?

Answer 192

Since each server only deals with a subset of the data, the cache utilization is improved while reducing the memory usage and the input/output traffic.

Question 193

In addition, Z-axis scaling improves fault isolation since?

Answer 193

a failure only makes part of the data in accessible.

Question 194

Unfortunately, Z-axis scaling has some drawbacks. One major drawback is ?

Answer 194

the increased application complexity.
It is necessary to implement a partitioning scheme, which can be tricky especially if we ever need to repartition the data.

Question 195

Complex event processing (CEP) is?

Answer 195

an approach that identifies data and application traffic as events, correlates these events to reveal predefined patterns, and reacts to them by generating actions to systems, people, and devices.

Question 196

CEP is based on?

Answer 196

the observation that actions are mostly triggered not by a single event, but by a complex composition of events, happening at different times, and within different contexts.

Question 197

It can provide companies with ?

Answer 197

the ability to define,
manage,
and predict events,
situations,
conditions,
opportunities,
and threats.

Question 198

CEP is as an event-driven processing engine because ?

Answer 198

the computation is triggered by the receipt of event data.

Question 199

the computation is triggered by the receipt of event data. The events being analyzed can be happening across different parts of an organization as sales?

Answer 199

leads, orders, or customer service calls.

Question 200

These data types can include:

Answer 200

news items, text messages, social media posts, stock market feeds, traffic reports, weather reports, or other kinds of data.

Question 201

An event may also be defined as?

Answer 201

a change of state, when a measurement exceeds a predefined threshold of time, temperature, or other value—that is really where IoT comes in.

Question 202

The challenge of real-time analysis continues to grow as ?

Answer 202

more IoT devices are deployed to collect more data.

Question 203

Being able to react quickly in a mission-critical situation can?

Answer 203

save companies millions of dollars and is one of the pillars of IoT functionality.

Question 204

Being able to react quickly in a mission-critical situation can. save companies millions of dollars and is one of the pillars of IoT functionality. This is why CEP is becoming ?

Answer 204

a more mainstream solution for IoT deployments.

Question 205

In a large-scale IoT application, event processing applications must process events that arrive from ?

Answer 205

various kinds of sources such as sensors which constitute a WSN, RFID readers, GPS, social media, etc.

Question 206

For instance,

Answer 206

each reading operation of the RFID reader at a garage generates a simple event but a complex event like “a car leaves the garage” is the kind of event that a user is really concerned with.

To get such a complex event, we need to combine many simple events based on some rule.

Question 207

Many events, generated by IoT devices, are used as?

Answer 207

an input to a CEP engine.

Question 208

The CEP engine correlates the complex events with already-stored pattern/rules. Once a match between the complex events and the patterns is found?

Answer 208

an action is generated to react to the complex events.

Question 209

In general, the CEP engine can be either ———————————————-. The centralized CEP architecture requires greater ————————————–capability as the number of clients increases, and the system is hardly robust and scalable because of————————————– .

Answer 209

centralized or distributed

bandwidth and computational

a single point failure or network break.

Question 210

Distributed CEP architecture becomes more common in the IoT domain. In fact, employing CEP in the IoT domain poses special requirements on CEP.

Answer 210

As many IoT applications are naturally distributed and hence complex events are to be detected from the distributed system.

Question 211

To optimize various processes in IoT applications, such as logistics, smart grid, traffic management, it is crucial to ?

Answer 211

react to the occurrence of critical situations with low latency.

Question 212

Examples of such situations can be?

Answer 212

accidents, load variations in power consumption, or changing weather conditions.

Question 213

The monitoring of situations of interest is enhanced by?

Answer 213

a steadily growing infrastructure of globally deployed sensors.

Question 214

By continuously capturing and analyzing sensor streams, CEP systems can help to?

Answer 214

detect the relevant situations.

Question 215

To react on complex events, CEP engines trigger decisions such as:

Answer 215

updating a traffic route
or changing the configuration in power consumption.

Question 216

In this context, the utility of such decisions widely depends on

Answer 216

(1) the time at which events are delivered by the CEP system,

and (2) the view of the application on the set of delivered events at decision time.

Question 217

This view should be consistent, i.e., at time of decision all relevant events are present (——————————————-) and no false events (————————————) are delivered.

Answer 217

no false-negatives

no false-positives

Question 218

For example,

Answer 218

consider a scenario where it is required to establish an overtaking ban on a certain region of a highway.
To this end, two camera-based sensors are deployed at the beginning and end of the no-passing zone.

Question 219

Readings from these sensors are used as?

Answer 219

an input to a CEP operator to detect when a vehicle overtakes another one.

Question 220

Obviously, such a scenario requires both?

Answer 220

the consistent and low-latency detection of complex events that signal when a vehicle has overtaken another one.

Question 221

In case of false-positive detection, an unjustified ticket maybe ————–, while a false-negative detection would leave the —————-unpunished. On the other hand, low-latency detection of an overtaking maneuver allows for direct
——————– to drivers who have
—————–the traffic rules.

Answer 221

issued

transgressor

feedback

violated

Question 222

In controlled environments, e.g., data centers, it is often uncomplicated to find?

Answer 222

acceptable bounds for communication and processing latencies.

Question 223

Nevertheless, understanding communication and processing delays is not enough when?

Answer 223

the CEP operator suffers from overload, i.e., the arrival rate of events exceeds the achievable processing rate.

Question 224

Nevertheless, understanding communication and processing delays is not enough when the CEP operator suffers from overload, i.e., the arrival rate of events exceeds the achievable processing rate. In this case, the CEP operator may adopt one of two strategies:

Answer 224

“load shedding”
or “buffering.”

Question 225

With load shedding, the CEP operator simply discards events that it is?

Answer 225

not
capable of processing in time.

Question 226

Obviously, such a strategy may lead to?

Answer 226

inconsistencies, which are not tolerable in several IoT applications.

Question 227

it is necessary to keep a buffering limit in the operators to support low-latency event detection?

Answer 227

since In the second strategy, a high number of events are to be buffered before being processed, which can cause an unacceptable latency in event detection.

Question 228

In fact, keeping a buffer limit is highly challenging ?

Answer 228

since many applications, e.g., traffic monitoring and smart grids, comprise very high and fluctuating event rates.

Question 229

Efficient and consistent parallel execution of dozens of processing entities is necessary to?

Answer 229

speed up the CEP systems.

Question 230

In this manner, the parallel CEP operators are capable of ?

Answer 230

meeting the buffering limits.

Question 231

When deploying resources while considering the worst-case workload, the resources could be?

Answer 231

underutilized for a large part of the day when the traffic intensity is lower.

Question 232

This underutilization causes unnecessary cost for resource provisioning. In fact, the costs already become?

Answer 232

high by reacting to dozens or even hundreds of different patterns that can occur in large-scale IoT applications, such as a smart city.

Question 233

This underutilization causes unnecessary cost for resource provisioning. In fact, the costs already become high by reacting to dozens or even hundreds of different patterns that can occur in large-scale IoT applications, such as a smart city. One possible solution to such a problem is?

Answer 233

to dynamically adjust the parallelization degree of operators according to the current workload given by the arrival rate of events.

Question 234

In this manner, significant cost gains can be achieved through?

Answer 234

avoiding underutilization of the system resources.

Question 235

CEP operators need to support parallelization, dynamic reconfigurations, and adaptive provisioning of resources such that ?

Answer 235

the operator can meet a buffering limit for a given workload at minimal cost.

Question 236

In fact, there exist several classes of CEP parallelization techniques, including :

Answer 236

intra-operator parallelization and data parallelization.

Question 237

In the former class, internal processing steps are identified so that ?

Answer 237

the operator logic is split accordingly,

and the identified processing steps are executed in parallel on the incoming event streams.

Question 238

This approach offers only a limited achievable parallelization degree depending on?

Answer 238

the number of variables in the query.

Question 239

Alternatively, the data parallelization class involves?

First, a splitter assigns the events, according to a partitioning model, to several identical operator instances. The execution of an operator instance is controlled by a runtime environment (RE). The RE receives information about the assigned partitions and the corresponding events. Afterward, it manages the operator execution so that the assigned partitions are processed. Finally, a merger ensures that an ordering between all produced events is established. The ordered events are consecutively assigned sequence numbers.

Answer 239

applying stream partitioning.

Question 240

In lieu of splitting the operator logic, the incoming event streams are split into?

Answer 240

partitions that can be processed by a number of identical instances of the operator.

Question 241

The architecture of such a framework consists of:
a splitter,
many operator instances,
and a merger.

Answer 241

First, a splitter assigns the events, according to a partitioning model, to several identical operator instances.
The execution of an operator instance is controlled by a runtime environment (RE).
The RE receives information about the assigned partitions and the corresponding events.
Afterward, it manages the operator execution so that the assigned partitions are processed.
Finally, a merger ensures that an ordering between all produced events is established.
The ordered events are consecutively assigned sequence numbers.

Question 242

To divide the event stream among the various operator instances, two common partitioning models can be utilized, namely:

insufficient to support consistent partitioning for operators that detect patterns of an unknown size.

Answer 242

key-based and batch-based.

Question 243

The former model partitions the event stream by?

Answer 243

a key that is encoded in each event.

Question 244

key-based partitioning only offers limited expressiveness?

Answer 244

The parallelization degree is limited to the number of different key values.

Question 245

Alternatively, the batch-based stream partitioning model splits the streams into ?

Answer 245

batches that are large enough to fit any match to a queried pattern.

Question 246

the communication overhead which occurs when?

Answer 246

patterns fluctuate in their size in terms of comprised events,

Question 247

Aside from the communication overhead which occurs when patterns fluctuate in their size in terms of comprised events, the approach is?

Answer 247

insufficient to support consistent partitioning for operators that detect patterns of an unknown size.

Question 248

In fact, machine learning is not a new computer science development. Instead, these mathematical models for data fitting and probability go back to?

Answer 248

the early 1800s to Bayes’ theorem and the least squares method of fitting data. Both models still widely used in machine learning models.

Question 249

The first neural network devices, referred to as —————————-, were developed in the early 1950s when computing machines and learning were ———————-. At that time, mathematics was ———————————————————————, e.g., IBM S/360. Evolutionary computation, e.g., genetic algorithms and swarm intelligence, became a research focus in the late 1960s and 1970s and was used for —————————————————————.

Answer 249

perceptrons

unified

beyond the reasonable resources of existing computers

solving complex engineering problems

Question 250

In fact, genetic algorithms are still employed today in?

a form of probabilistic AI, such as Bayesian inference models, and was successfully applied to research in gesture recognition and bioinformatics.

Answer 250

mechanical engineering and automatic software design.

Question 251

In the mid-1960s, the concept of hidden Markov models was introduced as?

Answer 251

a form of probabilistic AI, such as Bayesian inference models, and was successfully applied to research in gesture recognition and bioinformatics.

Question 252

With the advent of logic systems, the field of AI known as a logic-based AI emerged. The logic-based AI enabled programmers to ?

Answer 252

easily describe symbolic expressions.

Question 253

One major drawback of logic-based AI models at this time was?

Answer 253

the inability of logic-based semantics to think like a human.

Question 254

In the 1980s, expert systems were invented as another form of logic-based systems for ?

Answer 254

a well-defined problem trained by experts in that particular domain.
One could think of them as a rule-based engine for a control system.

Question 255

Expert systems had been successfully used in ———————————– and became the first ————————– available AI systems sold.

Answer 255

corporate and business settings

commercially

Question 256

Along a different line, fuzzy logic first manifested in research by Lotfi Zadeh at University of California Berkeley in 1965, but it was not until 1985 that?

Answer 256

researchers at Hitachi discovered how fuzzy logic could be successfully applied to control systems.

Question 257

Thanks to this discovery, significant interest was sparked in Japanese ———————————— firms to adopt fuzzy systems into actual products. While expert systems and fuzzy logic seemed to be the basic building blocks for —–, researchers in the early 1990s observed that ————-systems, or————- systems, could never ——the mind.

Answer 257

automotive and electronics

AI

expert

logic-based

emulate

Question 258

Support vector machines (SVMs) became popular between ?

Answer 258

1970s and the early 1980s.
using a novel technique to find the best hyperplanes to categorize data sets.

Question 259

They became the foundation for linear and nonlinear classification by?

Answer 259

using a novel technique to find the best hyperplanes to categorize data sets.

Question 260

This technique became popular with?

Answer 260

handwriting analysis, before being evolved into uses for neural networks.

Question 261

Recursive neural networks (RNNs) also became a topic of interest in the
1990s.
Such networks were different to traditional deep learning neural networks,
e.g.,?

Answer 261

convolutional neural network (CNN), because RNN could be applied to a problem involving the notion of time, such as audio and speech recognition.

Question 262

The utilization of RNN and CNN were prohibitive until ?

Answer 262

the advent of GPU processors.

Question 263

Thanks to all the aforementioned efforts to develop intelligence, today we find AI-based systems everywhere,:

Answer 263

from self-driving cars to speech recognition in Siri, to tools emulating humans in online customer service, to medical imaging, to retailers using machine learning models to identify consumer interest in shopping and fashion as they move about a store.

Question 264

The following figure demonstrates the full spectrum of Al algorithms where machine learning represents the heart of AI-based systems.

Question 265

In the context of IoT, machine learning offers interesting solutions while processing the massive amount of data generated by the IoT devices. In general, the value of a system of sensors is based on?

Answer 265

what a collection of sensors measures.

Question 266

Some of that generated data will be structured, e.g.,?

Answer 266

time-correlated series.

Question 267

Other data will be unstructured, e.g., ?

Answer 267

cameras, synthetic sensors, audio, and analog signals.

Question 268

a manufacturing plant could plan to optimize ?

Answer 268

operational expenses and potentially capital expenses by adopting IoT and machine learning.

Question 269

In such industrial environments, the manufacturers typically have many interdependent systems. They may have some assembly tool to produce?

Answer 269

a widget, another robot to cut parts out of metal or plastic, conveyor belts, lighting and heating systems, packaging machine, and inventory control systems.

Question 270

In this case, IoT devices are to be attached to these systems to generate different types of data, before being intelligently processed by means of ?

Answer 270

various AI-based models.

Question 271

In this context, machine learning and AI can predict ?

machine learning can handle big data that cannot be handled by humans.

Answer 271

behavioral effects.

Question 272

Currently, experienced technicians are able to predict possible machine failures by?

Answer 272

observing some behavioral effects, e.g., a machine may start creaking in a certain way.

Question 273

Machine learning can perform this role much earlier to implement?

Answer 273

a predicative maintenance system.

Question 274

Sensors can surround such machines to monitor their actions. An entire factory could be perceived in such a case to ?

Answer 274

understand how that factory is performing at that very instant based on a collection of millions or even billions of events from every machine.

Question 275

With this massive amount of data, only machine learning can overcome the noise and find the required patterns. In other words,?

Answer 275

machine learning can handle big data that cannot be handled by humans.

Question 276

In fact, there is no single machine learning algorithm that can optimally fit for ?

Answer 276

all IoT data.

In particular, each model has its specific strength and the use case it serves.

Question 277

In terms of the training data, there exist three types of learning systems to consider:

Question 278

In terms of the training data, there exist three types of learning systems to consider:

Answer 278

supervised learning.
The training data provided to the model has an associated label with each entry. For instance, a dataset may be a collection of pictures each labeled with the content of that image, e.g., cat, dog, banana, car. Many machine learning models today are supervised. Supervised learning is mainly used for solving classification and regression problems.

unsupervised learning.
It requires no labels for the training data. This type of learning model utilizes mathematical rules to reduce redundancy. A typical use case is to find clusters of like things.

semi-supervised learning.
It mixes labeled data and unlabeled data. The main objective is to force the machine learning model to organize data as well as make inferences.

Question 279

In general, the three fundamental uses of machine learning are :

Answer 279

classification,
regression,
and anomaly detection.

Question 280

Classification :

Answer 280

is a form of supervised learning where labeled data is used to detect a name, value, or category.
For instance, neural networks can be used to scan images for the sake of detecting pictures of a shoe.

Question 281

The following figure depicts three sets of data, i.e., blue, green, and red data points which are to be classified using the SVM algorithm.

Question 282

The hyperplane is

Answer 282

a straight line; thus, it is called a linear classifier.

Question 283

Through a training phase,:

Answer 283

SVM can find the best hyperplane, i.e., creates artificial segments, to divide the colored data points.

After several thousand iterations, the division is somewhat optimal where the artificial segments properly separate the different data sets,
i.e., the red data points exist in the red hyperplane.
In fact, SVM algorithm cannot support nonlinear relationships which are common in machine learning.
In fact, employing a linear model over nonlinear data would cause severe error rates.

Question 284

Aside from classification algorithms concerned with predicting a discrete value, regression models are used to?

Answer 284

predict a continuous value.

Question 285

For instance,

Answer 285

regression analysis can be used to predict the average selling price for a home based on the selling prices of all the homes in the neighborhood.

Question 286

Several techniques exist to perform regression analysis, including:

Answer 286

least squares method, linear regression, and logistic regression.

Question 287

“Random forest” is?

(1) they are easy to interpret and make for straightforward visualizations; (2) they can handle both numerical and categorical data; (3) they perform well on large datasets; and (4) they are extremely fast. A major shortcoming of decision trees is that they are prone to overfitting, especially when a tree is particularly deep. In this context, overfitting means the generation of a machine learning model that corresponds too closely or exactly to a particular set of data and may therefore fail to fit additional data or predict future observations reliably.

Answer 287

a subset of another machine learning model called the decision tree.

Question 288

A decision tree is ?

Answer 288

a statistical learning algorithm that simply takes several variables into consideration and produces a single output that classifies the dataset.

Question 289

Decision trees are?

Answer 289

-typically used for both classification and regression.
-The decision tree generates a set of probabilities that a path has taken based on the input.
-The model behaves with “if this, then that” conditions ultimately yielding a specific result.

Question 290

Decision trees have several advantages:

Answer 290

(1) they are easy to interpret and make for straightforward visualizations;
(2) they can handle both numerical and categorical data;
(3) they perform well on large datasets; and (4) they are extremely fast.

Question 291

A major shortcoming of decision trees is that they are?

Answer 291

prone to overfitting, especially when a tree is particularly deep.

In this context, overfitting means:
the generation of a machine learning model that corresponds too closely or exactly to a particular set of data and may therefore fail to fit additional data or predict future observations reliably.

Question 292

To overcome the shortcoming of decision trees, random forest is?

Answer 292

usually used for classification and regression.

It is a supervised learning algorithm where it creates a forest of decision trees.

In other words, random forest builds multiple decision trees and merges them together to get a more accurate and stable prediction.

Question 293

If the outcome of several trees——–with one another even though they arrived at that decision through ——– paths and a single tree is an ———-, one will naturally side with the majority. This creates a model with low variance, compared to a ————– tree model that can be extremely ———–.

Answer 293

agrees

different

outlier

single decision
biased

Question 294

Aside from random forest, Bayesian models are?

Answer 294

based on Bayes’ theorem which describes the probability that an event will occur based on prior knowledge of the system.

Question 295

For instance,

Answer 295

Bayesian models can estimate the probability that a machine will fail based on the temperature of the device.

Question 296

As analog to random forest, a Bayesian network is?

Answer 296

an extension of Bayes’ theorem in the form of a graphical probability model, i.e., a directed acyclic graph (DAG).

Question 297

In DAGs, the graph flows?

Answer 297

in one direction and there are no loopbacks to previous states.

Question 298

The various probabilities of each state come from ?

Answer 298

expert knowledge, historical data, logs, trends, or a combination thereof.

Question 299

A Bayesian network is well suited for?

Answer 299

environments in IoT that cannot be completely observed or when the data is unreliable.

Question 300

One major advantage of Bayesian networks is ?

Answer 300

their robustness against poor sampled data, noisy data, and missing data.

Question 301

Furthermore, Bayesian methods avoid the overfitting problem. Additionally, Bayesian networks have been deployed to find?

Answer 301

time-correlated series from sensors and find and filter malicious packets in networking.

Question 302

Various IoT platforms are currently available that can be used for?

Answer 302

developing an IoT solution.

Question 303

platforms that are widely used for data storage and processing in IoT solutions, e.g.,?

Answer 303

Google Cloud and Amazon Web Services (AWS).

Question 304

Microsoft Azure is a collection of ?

Answer 304

Microsoft-managed cloud services that connect, monitor, and control billions of IoT devices.

Question 305

An IoT solution is typically made up of ?

Answer 305

one or more IoT devices and one or more back-end services running in the Azure Cloud that communicate with each other.

Question 306

The back-end services provide several important functions:

Answer 306

(1) receiving telemetry, data collected by the IoT devices, at large scale, and determining how to process and store that data;
(2) analyzing the telemetry to provide insights, either in real time or in batch processing;
(3) sending commands from the cloud to a specific IoT device; and finally
(4) controlling the state of the IoT devices and monitor their activities.

Question 307

For instance,

Answer 307

in a predictive maintenance scenario, the cloud back-end service stores historical telemetry.
The solution uses this data to identify potential anomalous behavior on specific machines before they cause a real problem.
Data analytics can be used to identify an appropriate solution, before sending a command back to the device to take a corrective action.
This process generates an automated feedback loop between the device and the cloud that greatly increases the solution efficiency.

Question 308

The first component of Microsoft Azure is referred to as?

In other words, IoT Hub provides reliable device-to-cloud (D2C) and cloud-to-device (C2D) messaging at scale together with enabling secure communications. Accordingly, customers can use D2C telemetry data to understand the state of their machines and assets so that proper actions can be taken. Using the C2D messages, it is possible to reliably send commands and notifications to any connected devices. To develop an IoT application, an IoT Hub comprises device libraries for the most popular languages and platforms, thus making it versatile and common.

Answer 308

the Azure IoT Hub service, i.e., it represents the first endpoint of any IoT application running over Microsoft Azure.

Question 308

The first component of Microsoft Azure is referred to as?

In other words, IoT Hub provides reliable device-to-cloud (D2C) and cloud-to-device (C2D) messaging at scale together with enabling secure communications. Accordingly, customers can use D2C telemetry data to understand the state of their machines and assets so that proper actions can be taken. Using the C2D messages, it is possible to reliably send commands and notifications to any connected devices. To develop an IoT application, an IoT Hub comprises device libraries for the most popular languages and platforms, thus making it versatile and common.

Answer 308

the Azure IoT Hub service, i.e., it represents the first endpoint of any IoT application running over Microsoft Azure.

Question 308

In other words, IoT Hub provides?

Answer 308

reliable device-to-cloud (D2C) and cloud-to-device (C2D) messaging at scale together with enabling secure communications.

Question 309

Accordingly, customers can use D2C telemetry data to understand?

Answer 309

the state of their machines and assets so that proper actions can be taken.

Question 310

Using the C2D messages, it is possible to reliably send?

Answer 310

commands and notifications to any connected devices.

Question 311

To develop an IoT application, an IoT Hub comprises device libraries for?

Answer 311

the most popular languages and platforms, thus making it versatile and common.

Question 312

the most popular languages and platforms, thus making it?

Answer 312

versatile and common.

Question 313

The Azure IoT Hub has an “identity registry” which stores?

Answer 313

all information about provisioned devices.

Question 314

In fact, this information is related to ?

Answer 314

identity and authentication of the devices.

Question 315

Specifically, it provides monitoring information such as?

Additionally, IoT Hub exposes another endpoint, referred to as the?

After receiving the telemetry data, the Stream Analytics service plays the role of?

Answer 315

connection status (i.e., connected or disconnected) and last activity time. Accordingly, customers can easily enable and disable the devices using this registry.

“device identity management,” which is used to create, retrieve, update, and delete devices.

monitoring the Azure IoT Hub and performing operations on the received data streams.

Question 316

Such operations range from reformatting and transferring the data, to looking for?

Answer 316

specific patterns that may result in triggering some sort of action, depending on the event.

Question 316

For instance,

Answer 316

in a healthcare application, the Stream Analytics service will constantly monitor the raw sensor data of the IoT Hub that is related to a user’s heart rate.

Once a sudden change occurs, an appropriate action is to be taken, e.g., calling a person or notifying an ambulance.

Question 317

Such simple events can be simply identified using hard-coded rules through?

Answer 317

an SQL-like language which Microsoft has developed for the Stream Analytics services.

Question 318

It is necessary to employ machine learning techniques that allow the system to recognize complex patterns.

Answer 318

In fact, detecting more complicated patterns and events can be more challenging.

Question 319

Luckily, Microsoft Azure provides seamless integration with Azure’s Machine Learning Studio. Hence, it is ?

Answer 319

straightforward to create statistical models of sensor use cases using previous historical data, deploy them, and then use them as functions on the Stream Analytics service to help easily recognize new similar events that match the patterns of the trained models.

Question 320

Such a pattern generation scheme is extremely helpful in ?

Answer 320

many IoT applications.

Question 321

For instance,

Answer 321

predictive monitoring, i.e., predicting when an engine will break, can be performed based on similar sensor data patterns of engines that previously broke.

Question 322

Finally, the last stage of Microsoft Azure deals with?

To the outside world, an IoT application can seem like a black-box that takes in raw sensor data, stores it, and performs the necessary actions depending on the application. Accordingly, Microsoft Azure’s services can be used together to build extremely efficient and scalable IoT solutions easily.

Answer 322

storing the received data and possibly visualizing it.

Question 323

Microsoft Azure already provides several solutions such as:

Answer 323

SQL Database,
SQL Data Warehouse,
and DocumentDB for storage,
and PowerBI for visualization.

Question 324

In fact, the major advantage of the Microsoft Azure IoT architecture is that:

Answer 324

all the services can interact with each other seamlessly.

Question 325

In fact, the major advantage of the Microsoft Azure IoT architecture is that:

Answer 325

all the services can interact with each other seamlessly.

Question 326

Such interaction typically occurs without ?

Answer 326

delay,
availability,
or security issues,
since all the services reside on the same data centers used to host the entire solution.

Question 327

Google Cloud Platform (GCP) is ?

Answer 327

a collection of cloud computing services including data storage, data analytics, and machine learning.

Question 328

GCD runs on the same infrastructure that Google internally utilizes for?

Answer 328

its end-user products, e.g., Google Search and YouTube.

Question 329

From the architectural prospective, GCP consists of a set of physical servers, as well as?

Answer 329

virtual resources like VMs that are contained in Google’s data centers around the globe.

Question 330

Through GCP, IoT developers can code, test, and deploy their applications with?

Answer 330

highly scalable and reliable infrastructure provided by Google.

Question 331

Accordingly, system developers must solely focus on?

Answer 331

the code and Google handles issues regarding infrastructure, computing power, and data storage facility.

Question 332

In fact, GCP is one of the popular IoT platform thanks to?

Answer 332

(1) its fast global network,
(2) providing better pricing than its competitors,
(3) offering support of various available services of cloud such as Firebase, PubSub, and Telit Wireless Solutions, and
(4) its powerful mechanism for connecting IoT devices to Firebase and Cassandra services.

Question 333

There are several stages of IoT data management in ?

Answer 333

the Google Cloud Platform.

Question 334

After the IoT project is up and running, many devices will?

Answer 334

produce a massive amount of data.

Question 335

In this case, we need an efficient, scalable, and affordable way to both:

Answer 335

manage those devices and handle all that information and make it suitable for application.

Question 336

Google Cloud is an ideal solution for ?

Answer 336

storing, processing, and analyzing the big data.

Question 337

For the sensors which typically use an operating system, Google offers a ?

Answer 337

stripped-down version of Android for IoT devices called “Android Things.”

Question 338

Android Things lets developers configure and push ?

Answer 338

over-the-air software updates to the operating system and applications on the IoT devices.

Question 339

In general, Cloud IoT Core is a platform that enables?

Answer 339

large-scale data collection from IoT devices.

Question 340

Furthermore, it automatically performs load balancing and scaling to support?

Answer 340

data ingestion from millions of devices.

Question 341

Any application that needs to read data from certain IoT devices can subscribe to?

Answer 341

a single channel to receive the required data.

Question 342

Cloud Functions are used to——– the data to its final destination. A Cloud Function is triggered to execute when ——— occur. A Cloud Function may react to incoming data by writing it to a document database called ——-as well as to ———.

Answer 342

route

certain events

FireStore

BigQuery

Question 343

BigQuery is also a fully managed data warehouse that can run?

Answer 343

SQL-like queries against terabytes of data in seconds.

Question 344

Using BigQuery enables data scientists to ask questions against terabytes of data without needing to?

Answer 344

deploy and manage Hadoop clusters and to do so at reasonable costs.

Question 344

Using BigQuery enables data scientists to ask questions against terabytes of data without needing to?

Answer 344

deploy and manage Hadoop clusters and to do so at reasonable costs.

Question 345

Once we collect enough data, the Cloud Machine Learning service is used to?

Answer 345

train the models that can be later exported to run elsewhere on different data.

Question 346

Firebase Firestore, a NoSQL document database, is utilized when ?

Answer 346

a database that supports location-aware queries in real time is highly required.

Question 347

For instance,

Answer 347

Pokémon Go (2016) was built on a predecessor of Firestore, referred to as Datastore.

Question 348

Amazon Web Services (AWS) are a ?

Answer 348

collection of services that form a cloud computing platform (Raj and Raman, 2017).

Question 349

The most common services are :

Answer 349

Amazon Elastic Compute Cloud (EC2)

and Amazon Simple Storage Service (S3).

Question 350

AWS provides large computing capacity faster and cheaper than ?

Answer 350

the privately built and maintained servers.

Question 351

AWS automatically handles :

Answer 351

resource provisioning,
load balancing,
scaling,
and monitoring.

Question 352

The main concept in AWS platform is the ?

Answer 352

device state.

Question 353

The devices are able to report their state by ?

Answer 353

publishing messages to the message broker through topics.

Question 354

The broker delivers the received messages to?

Answer 354

all clients subscribed on the specific topics.

Question 355

The default settings for any application is ?

Answer 355

to run a single Amazon EC2 micro instance and an Elastic Load Balancer.

Question 356

If required, additional instances can be added to efficiently handle any peaks in the ——. AWS IoT has a “———” database that contains devices-related information. Through the —— command line interface (CLI), a thing registry can be used to ——————————————- things.

Answer 356

workload

thing registry

AWS

create, delete, and update

Question 357

The AWS IoT Device SDK is a set of ?

Answer 357

software components that easily and quickly enables connecting an IoT device or a mobile application to AWS IoT Core.

Question 358

The AWS IoT Device SDK can not only establish a connection, but?

Answer 358

it also enables authentication and messages exchange with AWS IoT Core using the MQTT, HTTP, or WebSockets protocols.

Question 359

The AWS IoT Device SDK can be implemented using?

Answer 359

C and JavaScript, where it supports Arduino hardware platforms.

Question 360

At the AWS cloud, the Device Gateway represents the?

Answer 360

entry point for IoT devices connecting to AWS.

Question 361

This component manages all active device connections and implements multiple protocols to ensure that?

Answer 361

the IoT devices can securely and efficiently communicate with AWS IoT Core.

Question 361

The Device Gateway supports several communication protocols, e.g.,?

Answer 361

MQTT, WebSockets, and HTTP 1.1.

Question 361

For devices that connect using MQTT or WebSockets, the Device Gateway can establish long-lived, bidirectional connections, thus enabling these IoT devices to?

Answer 361

send and receive messages at any time with low latency.

Question 361

The Device Gateway is designed to be ?

Answer 361

fully managed and scales automatically to support over a billion devices.

Question 362

The Message Broker is a pub/sub message broker that securely transmits messages to and from?

Answer 362

the IoT devices and applications in a timely manner.

Question 363

It supports various messaging patterns, such as:

Answer 363

control messaging and broadcast notification systems.

Question 364

Additionally, fine-grained access controls can be implemented to enable managing the permissions of?

Answer 364

individual connections at the topic level, thus ensuring that the IoT devices and applications only send and receive the relevant data.

Question 365

In general, AWS IoT Core provides:

Answer 365

mutual authentication
and encryption at all points of connection.

Question 366

Accordingly, the collected data is never ?

Answer 366

exchanged between devices

and AWS IoT Core without a proven identity.

Question 367

Specifically, AWS IoT Core offers several methods of authentication, such as ?

Answer 367

SigV4, X.509 certificate-based authentication,
and customer-created token-based authentication.

Question 368

HTTP connections may use any of these methods, while MQTT connections use?

Answer 368

certificate-based authentication,
and WebSockets connections can use SigV4 or custom authorizers.

Question 369

With AWS IoT Core, customers can authorize certain IoT devices or applications to have?

Answer 369

access, or revoke access without ever touching the IoT device.

Question 370

In general, it is straightforward to create, deploy, and manage certificates and policies for?

Answer 370

the IoT devices from the console or using the API.

Question 371

AWS IoT Core can also provide temporary AWS credentials after a device has authenticated with?

Answer 371

an X.509 certificate, so that the device can more easily access other AWS services such as DynamoDB or S3.

Question 372

Another component of the AWS IoT Core is referred to as ?

Answer 372

the Device Shadow.

Question 373

A Device Shadow of a certain device includes?

Answer 373

the device’s latest state so that applications
or other devices can read messages and interact with the device.

Question 374

Even if the IoT device is offline, the Device Shadow provides?

Answer 374

the last reported state and desired future state of each device.

Question 375

Thanks to the Device Shadow tool, we can retrieve the last reported state of?

Answer 375

a device or set a desired future state through the API or using the rules engine.

Question 376

Applications can set the desired future state of a device without ?

Answer 376

accounting for the device’s current state.

Question 377

AWS IoT Core compares the difference between

Answer 377

the desired and last reported state, and then command the device to make up the difference.

Question 378

In general, the Device Shadow enables IoT developers to ?

Answer 378

store the state of your devices for up to a year.

Question 379

Finally, the Rules Engine component enables building IoT applications that gather, process, analyze, and act on data generated by ?

Answer 379

the IoT connected devices at a global scale without having to manage any infrastructure.

Question 380

The Rules Engine evaluates messages published into?

Answer 380

AWS IoT Core before delivering them to another device or a cloud service, based on customer-defined business rules.

Question 381

A rule can be applied to data generated from one or many IoT devices, and then?

Answer 381

it can simultaneously take one or many actions.

Question 382

The Rules Engine can route messages to several AWS endpoints including :

Answer 382

AWS Lambda, Amazon Kinesis, Amazon S3, Amazon Machine Learning, Amazon DynamoDB, Amazon CloudWatch, Amazon Simple Notification Service (SNS), Amazon Simple Queue Service (SQS), AWS IoT Analytics, Amazon Elasticsearch Service with built-in Kibana integration, and AWS Step Functions.

Question 383

In addition to the existing rules, IoT developers can write ?

Answer 383

new rules using an SQL-like syntax.

Question 384

Rules can be authored to behave differently depending upon?

Answer 384

the application.

Question 385

For instance,

Answer 385

if a temperature reading exceeds a certain threshold it could trigger a rule to transmit data to AWS Lambda.

Question 386

Rules can also be authored to take into?

Answer 386

account other data in the cloud, such as data from other devices.

Question 387

For example,

Answer 387

a rule can be designed to make an action if the temperature is more than 15 percent higher than the average of 5 other devices.

Question 388

The Rules Engine :

Answer 388

1-provides dozens of available functions that can be used to process the collected data.
2- Moreover, a myriad of other functions can be created through the AWS Lambda component.

For instance, if we are dealing with a wide range of values, we could take the average of the incoming numbers.

Question 389

Rules can also trigger the execution of Java, Node.js, or Python code in AWS Lambda, giving developers?

Answer 389

maximum flexibility and power to process device data.

Question 390

Data storage and data processing are two important components of an—–system architecture. Traditional relational database systems based on —– fail to accommodate rapid change of —— data and to provide an efficient means for ——————-.

Answer 390

IoT
SQL
unstructured
storage and elaboration

Question 391

NoSQL database systems have been designed to?

Answer 391

scale horizontally and to run on clusters.

Question 392

Briefly speaking, they are non-relational and distributed database systems which enable ?

Answer 392

rapid organization and analysis of huge amount of heterogeneous data.

Question 393

Scalability, availability and consistency are achieved with?

Answer 393

ad hoc approaches (e.g., sharding).

Question 393

Examples of widely used NoSQL database systems are?

Answer 393

MongoDB and Apache Cassandra.

Question 394

A common approach to process the amount of data stored into databases effectively and efficiently is?

Answer 394

the MapReduce pattern.

Question 395

the MapReduce pattern.

Answer 395

It uses hundreds or thousands of pluggable nodes in a cluster to process data in parallel, which significantly shortens the time between the events and the presentation of their analysis.

Question 396

An open source implementation of the MapReduce framework can be found in ?

Answer 396

the Apache Hadoop.

Question 397

The major benefits of IoT can be realized only if ?

Answer 397

a suitable infrastructure and mechanism to synthesize and interpret the data to make actionable decisions is set up.

In other words, there must be a way to generate and represent knowledge extracted from the heterogeneous data base.

Question 398

Ontologies are knowledge representation systems which find applications in IoT in ?

Answer 398

describing resources and connections/relations among them.

Question 399

The Resource Description Framework (RDF) is one way to describe such resources, which can be?

Answer 399

any device or concept (e.g., person, place).

Question 400

RDF allows the description of the connections by means of ?

Answer 400

a subject, predicate, object triple.

Question 401

The Web Ontology Language (OWL) formalism is another approach to ?

Answer 401

resource description that extends the RDF by solving some of its limits.

Question 402

An implementation of OWL for sensors networks is? It can describe sensors and their characteristics, observations, and methods used for sensing.

Answer 402

the Semantic Sensor Network (SSN) ontology.

Question 403

the Semantic Sensor Network (SSN) ontology.

Answer 403

It can describe sensors and their characteristics, observations, and methods used for sensing.

Question 404

To achieve automatic processing and interpretation of the IoT data, we need —-to describe the IoT data including the —— of the data. The concept of linked data emerges to connect individual data items to support ——————————————on the data coming from physical and virtual objects.

Answer 404

standards
source

semantic query and inferences

Question 405

The linked data is represented by the RDF or OWL formalism and provides the basis for?

Answer 405

information reuse and interoperability among heterogeneous sources.

DBpedia, which enables sophisticated queries over the information contained in Wikipedia.

Question 406

One example of implementation of the linked data concepts is

Answer 406

DBpedia, which enables sophisticated queries over the information contained in Wikipedia.

Question 407

Processing of IoT data can be performed with several technologies. Complex event processing (CEP) is?

processing of IoT data, in particular to perform classification, regression and anomaly detection.

Answer 407

an approach that identifies data and application traffic as events, correlates these events to reveal some patterns, and reacts to them by generating actions to systems, people, and devices.

Question 408

It is an event-driven processing approach because ?

Answer 408

the computation is triggered by the receipt of event data, and aims at a real-time reaction.

Question 409

One main challenge with CEP is ?

Answer 409

the overload which occurs when the arrival rate of events exceeds the achievable processing rate.

Question 410

Solutions to this problem are based on ?

Answer 410

buffering, load shedding or parallelization.

Question 411

Machine learning, as a subset of artificial intelligence methods, is another widely adopted approach for?

Answer 411

processing of IoT data, in particular to perform classification, regression and anomaly detection.

Question 412

Various IoT platforms are available to ?

Answer 412

develop IoT applications and solutions.

Examples
are Microsoft Azure, Google Cloud Platform and Amazon Web Services.

Question 413

Growth opportunities provided by IoT and insight from IoT data across the enterprise can give companies in any industry a —————————. IoT helps companies realize greater ———————–, more effective —————–, and increased customer and employee ——————–.

Answer 413

competitive advantage
innovation

operations

engagement