Fog computing and more

Question 1

What is fog computing, and how does it differ from traditional cloud computing?

Answer 1

Fog computing is a model in which data, processing, and applications are concentrated in devices at the network edge, as opposed to being primarily located in the cloud. It differs from cloud computing by bringing computational resources closer to the data source or end-users, reducing latency and enabling real-time processing.

Question 2

Who introduced the term “Fog Computing,” and what was the primary purpose of this model?

Answer 2

The term “Fog Computing” was introduced by Cisco Systems as a new model to facilitate wireless data transfer to distributed devices in the Internet of Things (IoT) network paradigm. The primary purpose was to enable applications to run directly at the network edge, improving responsiveness.

Question 3

In a Cloud-Fog-Edge Computing model, what are the primary components that bring intelligence closer to the end-user or data source?

Answer 3

The primary components include cellular base stations, network routers, WiFi gateways capable of running applications (Fog), and end devices such as sensors that can perform basic data processing (Edge). This combination brings intelligence closer to the ground, reducing response time for real-time applications.

Question 4

What are some challenges in a “Cloud-only” scenario for IoT applications?

Answer 4

Challenges include latency due to data transmission to remote cloud data centers, high bandwidth requirements, and the inadequacy of the cloud for handling the large volume, variety, and velocity of data generated by IoT devices. Additionally, IoT devices may face issues related to processing, storage, and power requirements in a cloud-only setup.

Question 5

How do fog and edge computing complement cloud computing, and what is their role in addressing latency issues?

Answer 5

: Fog and edge computing complement cloud computing by processing data closer to the data source or edge devices. They reduce latency and improve system responsiveness. By handling local data processing, they alleviate the challenges associated with transmitting data to remote cloud data centers, making them suitable for time-sensitive and real-time applications.

Question 6

What is fog computing, and how does it differ from traditional cloud computing?

Answer 6

Fog computing is a model in which data, processing, and applications are concentrated in devices at the network edge, as opposed to being primarily located in the cloud. It differs from cloud computing by bringing computational resources closer to the data source or end-users, reducing latency and enabling real-time processing

Question 7

What are some challenges in a “Cloud-only” scenario for IoT applications, and why might processing IoT applications directly in the cloud not be efficient?

Answer 7

Challenges include issues with latency, bandwidth requirements, and managing large volumes of data generated by IoT devices. Processing IoT applications directly in the cloud may not be efficient, especially for time-sensitive applications, due to the delays introduced by transmitting data to remote cloud data centers.

Question 8

How can fog and edge computing help overcome latency issues in IoT applications, and what is their relationship with cloud computing?

Answer 8

Fog and edge computing address latency issues by processing data closer to the data source, reducing the need for data transmission to distant cloud data centers. They are not substitutes for cloud computing but work in collaboration with it. The three technologies, cloud, fog, and edge computing, can together improve latency, reliability, and response times.

Question 9

What is the Cloud-Fog Paradigm, and what is its vision for the distribution of data and processing?

Answer 9

The Cloud-Fog Paradigm envisions distributing data, processing, and applications across cloud, fog, and edge layers. The vision is to bring intelligence closer to the end-user, with cellular base stations, network routers, and other devices capable of running applications, thus enabling real-time applications.

Question 10

In a Cloud-Fog-Edge environment, what are the primary components of the fog layer, and how do they manage resources for clients?

Answer 10

The fog layer typically consists of a client layer (edge), a fog layer, and a cloud layer. The fog layer manages resource requirements for clients. It employs a fog server manager that allocates available processors to clients, uses virtual machines (VMs) to process data, and delivers results to the fog server manager.

Question 11

What is the trend in utilizing computing resources in Cloud-Fog-Edge environments, and what are the forms that these resources can take?

Answer 11

The trend is to decentralize computing resources by distributing them closer to the end-users and sensors at the edge of the network. Resources can take the form of dedicated “micro” data centers or enhancing Internet nodes like routers and gateways with computing capabilities. This approach is known as “edge computing.” A model that uses both edge and cloud resources is referred to as “fog computing.”

Question 12

: What is the main objective of fog computing in the context of cloud computing, and what role does fog play in overcoming cloud limitations?

Answer 12

The main objective of fog computing is to reduce latency and improve responsiveness by processing data and applications closer to the data source. Fog computing helps overcome cloud limitations by reducing the need for data to be transported to distant cloud data centers. It complements cloud computing rather than replacing it.

Question 13

In a Cloud-Fog environment model, how is resource management structured, and what are the main components of this model?

Answer 13

Resource management in a Cloud-Fog environment typically includes three layers: a client layer (edge), a fog layer, and a cloud layer. The fog layer manages resources for clients. It involves a fog server manager that allocates processors to clients, employs virtual machines (VMs) for data processing, and delivers results to the fog server manager.

Question 14

What are the primary types of resource management approaches in fog and edge computing, and what do they encompass?

Answer 14

Resource management approaches in fog and edge computing encompass architectures, infrastructure, and algorithms. Architectures are classified based on data flow, control, and tenancy. Infrastructure includes hardware resources, system software, and middleware. Algorithms serve functions like resource discovery, benchmarking, load balancing, and placement.

Question 15

How are resource management architectures classified in fog and edge computing, and what do the categories of data flow, control, and tenancy represent?

Answer 15

Resource management architectures in fog and edge computing are classified based on data flow, control, and tenancy. Data flow categorizes how workloads and data move within the ecosystem (e.g., from user devices to edge nodes or from cloud servers to edge nodes). Control focuses on resource control methods, such as a single controller or distributed control. Tenancy determines whether a single or multiple applications can be hosted on an edge node.

Question 16

What types of resources are utilized in fog and edge computing for resource management in terms of hardware, system software, and middleware?

Answer 16

In fog and edge computing, hardware resources include small-form-factor devices like network gateways, WiFi access points, and home servers, as well as commodity products like desktops, laptops, and smartphones. System software operates on hardware resources, managing CPU, memory, and network devices. Middleware runs on the operating system and provides additional services for resource coordination.

Question 17

What are the key resource management algorithms used in fog and edge computing, and what functions do they serve?

Answer 17

Resource management algorithms include discovery, benchmarking, load balancing, and placement. Discovery identifies available edge resources for workload deployment. Benchmarking captures performance metrics. Load balancing optimizes task distribution. Placement determines where computation tasks should be executed based on resource availability and environmental conditions.

Question 18

What is the Service Placement Problem in the context of fog and edge computing, and why is it significant?

Answer 18

The Service Placement Problem involves determining where to place application components and links within a fog and edge computing infrastructure. This is significant because it impacts resource utilization, latency, and overall performance of applications in these environments.

Question 19

What are the characteristics of fog infrastructure in Cloud-Fog-Edge computing, and how do they contribute to its functionality?

Answer 19

Fog infrastructure includes IoT devices, fog nodes, and cloud data centers. It offers location awareness, low latency, better bandwidth utilization, scalability, and support for mobility, contributing to efficient processing at the edge of the network.

Question 20

What does application placement entail in the Cloud-Fog-Edge framework, and why is it a critical task?

Answer 20

Application placement involves mapping application components and links to the infrastructure graph. It is critical as it ensures that applications satisfy requirements, constraints, and objectives while utilizing available network resources effectively.

Question 21

What are some common constraints considered during application placement in fog and edge computing, and why are they important?

Answer 21

Constraints in application placement include resource constraints (e.g., CPU, RAM), network constraints (e.g., latency, bandwidth), and application constraints (e.g., locality requirements, delay sensitivity). These constraints ensure that applications function optimally within the network.

Question 22

What are the primary objectives and metrics considered when optimizing service placement in a Cloud-Fog infrastructure?

Answer 22

Optimization objectives and metrics for service placement can include latency, resource utilization, cost, and energy consumption. Different objectives help achieve diverse performance and efficiency goals.

Question 23

What is offloading in the context of fog and edge computing, and how does it affect the distribution of computational tasks?

Answer 23

Offloading involves moving servers, applications, and data closer to the edge of the network, reducing data transmission distances. It redistributes computational tasks, either from user devices to the edge or from the cloud to the edge, to improve performance.

Question 24

What are the two primary control approaches used in fog and edge computing, and what are their respective characteristics?

Answer 24

Fog and edge computing use centralized and distributed control approaches. Centralized control relies on a single controller, while distributed control involves multiple controllers. Centralized control offers uniformity, while distributed control provides flexibility and redundancy.

Question 25

What types of hardware are commonly used in fog and edge computing, and how do low-power devices contribute to this environment?

Answer 25

Fog and edge computing employ low-power devices like mobile devices, routers, and gateways. These devices, combined with the network, create a computing environment suitable for processing data from IoT and cyber-physical systems (CPS).

Question 26

What are the two categories of system software in fog and edge computing, and what roles do they play?

Answer 26

System software in fog and edge computing includes system virtualization and network virtualization. System software manages resources and supports multi-tenancy and isolation, ensuring efficient resource utilization.

Question 27

What functions does middleware perform in fog and edge computing, and how does it enhance the system?

Answer 27

Middleware provides services such as performance monitoring, coordination, orchestration, communication facilities, and protocols. It enhances system functionality by facilitating communication and coordination.

Question 28

What are the four major algorithms used in fog and edge computing, and what roles do they play in the ecosystem?

Answer 28

The four major algorithms in fog and edge computing are discovery, benchmarking, load balancing, and placement. Discovery identifies edge resources, benchmarking captures performance data, load balancing optimizes task distribution, and placement selects resources for deploying workloads.

Question 29

What is Cloud Federation (Federated Cloud), and why is it significant in cloud computing?

Answer 29

Cloud Federation, also known as Federated Cloud, involves deploying and managing multiple external and internal cloud services to align with business needs. It’s significant for capacity utilization, interoperability, service catalog, and insights into providers and SLAs.

Question 30

What motivates different Cloud Service Providers (CSPs) to join together and form a federation, and what benefits does it offer?

Answer 30

Different CSPs form federations to maximize resource utilization, minimize power consumption, achieve load balancing, provide global utility, and expand their global footprint, benefiting both providers and users.

Question 31

What are the key characteristics of a Cloud Federation, and how does it address limitations in cloud computing?

Answer 31

Cloud federation overcomes limitations in cloud computing, such as service interruptions, lack of interoperability, and service degradation. It is a voluntary, geographically separated inter-cloud organization with a well-defined marketing system and regulated federal agreement.

Question 32

What are the typical architectures used in Cloud Federation, and how are they classified based on their coupling or interoperation level?

Answer 32

Typical federation architectures include cloud bursting, brokering, aggregation, and multitier. These architectures are classified based on their coupling level, ranging from loosely coupled (limited interoperation) to tightly coupled (full interoperability among cloud instances).

Question 33

What does a Loosely Coupled Federation entail in the context of Cloud Federation, and how does it function?

Answer 33

In a Loosely Coupled Federation, there’s limited interoperation between CSPs/cloud instances. CSPs have little control over remote resources, limited monitoring information, and no support for advanced features, making it ideal for private clouds complementing their infrastructure with external cloud resources.

Question 34

What is a Partially Coupled Federation, and how does it enable more advanced control and interoperation among partner clouds?

Answer 34

In a Partially Coupled Federation, partner clouds establish a contract or framework agreement, allowing some control over remote resources, interchange of detailed monitoring information, and advanced networking features among partner clouds. It enables more advanced coordination and resource sharing.

Question 35

What is a Tightly Coupled Federation, and what level of control and interoperation does it offer among clouds?

Answer 35

In a Tightly Coupled Federation, cloud instances are governed by the same administration, providing advanced control over remote resources. It supports features like precise VM placement, cross-site VM migration, advanced networking, and high availability techniques among remote cloud instances.

Question 36

What are the four common Cloud Federation Architectures, and what are their key features?

Answer 36

The four common Cloud Federation Architectures are (a) Hybrid/Bursting, (b) Broker, (c) Aggregated, and (d) Multiplier. They each have distinct features that influence how they interoperate and share resources among different cloud instances.

Question 37

: What is the Hybrid/Bursting Architecture in Cloud Federation, and what is its primary purpose?

Answer 37

The Hybrid/Bursting Architecture combines private and public clouds to provide extra capacity during peak demand periods. It is loosely coupled and aims to enhance capacity and performance.

Question 38

What is the Broker Architecture in Cloud Federation, and what role does the broker play in this scenario?

Answer 38

In the Broker Architecture, a broker serves multiple users and provides access to various public clouds. The broker deploys virtual resources based on user preferences, and advanced brokers may optimize placements based on criteria like cost and performance.

Question 39

What is the Aggregated Architecture in Cloud Federation, and how do partner clouds cooperate in this model?

Answer 39

The Aggregated Architecture involves two or more partner clouds that aggregate resources and create a larger virtual infrastructure. It is partially coupled, and partner clouds interoperate based on contracts, allowing more control and sharing of resources.

Question 40

: What is the Multitier Architecture in Cloud Federation, and how does it enable hierarchical management of cloud sites?

Answer 40

In the Multitier Architecture, different cloud sites, often belonging to the same corporation, are managed by a root/top cloud OS instance in a hierarchical arrangement. It is tightly coupled and provides uniform access to geographically distributed cloud infrastructures.

Question 41

What is Offloading in the context of Cloud Federation, and how does it work for application and data management?

Answer 41

Offloading in Cloud Federation involves moving servers, applications, and data between the cloud and the edge of the network. This can augment computing capabilities and bring cloud services closer to users or devices. Offloading can be from user devices to the edge or from the cloud to the edge, utilizing application partitioning and caching mechanisms.

Question 42

How does Control in Cloud Federation differ in terms of centralized and distributed models?

Answer 42

Control in Cloud Federation can be either centralized or distributed. In the centralized model, a single entity has control over all resources, making decisions for the federation. In the distributed model, control is more decentralized, with different entities making decisions for their respective resources. The choice depends on the level of coordination and control desired within the federation.

Question 43

What is the significance of Hardware in the Cloud Federation context, and what types of devices are commonly used?

Answer 43

Hardware plays a crucial role in Cloud Federation, with low-power devices like mobile devices, routers, gateways, and home systems being commonly used. These devices, connected to the network, enable cloud computing environments for applications processing IoT and cyber-physical systems data.

Question 44

What is the role of System Software in Cloud Federation, and how does it manage resources?

Answer 44

System software in Cloud Federation operates directly on edge devices and manages computation, network, and storage resources. It needs to support multi-tenancy and isolation. System software can involve system virtualization and network virtualization.

Question 45

What does Middleware provide in the context of Cloud Federation, and what services and facilities does it offer?

Answer 45

Middleware in Cloud Federation provides complementary services to system software. It offers performance monitoring, coordination, orchestration, communication facilities, and protocols. Middleware plays a crucial role in enabling the seamless operation of cloud resources across different providers.

Question 46

What are the core algorithms used in Cloud Federation to facilitate resource management, and what are their primary functions?

Answer 46

Core algorithms used in Cloud Federation include Discovery (identifying edge resources), Benchmarking (capturing performance metrics), Load Balancing (efficiently distributing workloads), and Placement (identifying suitable resources for deploying workloads). These algorithms aim to optimize resource utilization and application performance in the federation.