Exercise: Paper discussion Flashcards
What was Marc Weisers Vision?
- The most profound technologies are those that disappear
- -> Ubiquitous computing
What means Ubiquitous computing?
- No PCs but computers everywhere
- People take computers for granted
- They are not anymore aware of their existence -> embodied virtuality
How to become a embodied virtuality?
- Computers become invisible (computers in switches, ovens, fridges; connected by network)
What are the issues to become a embodied virtuality?
- Location and scale
- Computers need to know where they are
- Devices of different sizes for different purposes
Which implications of ubiquitous computing did Weiser predict?
- Privacy will become key issue
- Individuals will be more aware of other people instead of working alone with a PC
- All groups in society will use computers
- No information overload (don’t frustrate the user)
How was Weiser vision created?
- He way bold and creative about technology
- He had a goal which determined technology, not the other way around
What new knowledge was developed by Satya, who revisited Weisers vision in 2001?
Pervasive computing is the intersection of:
- Distributed System
- Mobile Computing
Pervasive computing research focus:
- Effective use of smart spaces
- Invisibility
- Localized scalability
- Masking uneven conditions
Explain the research focus Effective use of smart spaces
- Embedding computers in rooms
- Automatic adjustment of cooling in a room
Explain the research focus Effective use of invisibility
- Optimally: computer usage completely unconscious
- Approximation: minimal user distraction
Explain the research focus Effective use of Localized Scalability
- More interaction with computers that are in proximity
- Few distant interactions (creates a new understanding of scalability)
–> Like implemented by Google Cloud: upload to tenants that are far away?
Explain the research focus Effective use of Masking uneven conditions
- User should still have the impression of high service quality independent of the environment he uses
What do Satyas finding imply in detail in terms of User Intent?
- Applications are too generic
- They need to determine what the user really wants in a situation
What do Satyas finding imply in detail in terms of Adaption Strategy?
- How to adapt the mismatch between resource supply and demand ? (e.g. bandwith)
What do Satyas finding imply in detail in terms of High-level energy management?
- Higher energy demand vs more compact computers
What do Satyas finding imply in detail in terms of Client-thickness?
- What capabilities do pervasive computers need to have?
What do Satyas finding imply in detail in terms of Context awareness?
- System has to be aware of users state and surroundings
- Adapt behavior to different contexts
What do Satyas finding imply in detail in terms of Balancing proactivity and transparency?
- Find perfect tradeoff
- User-dependent and not generic
What do Satyas finding imply in detail in terms of impact on layering?
- Different layers of a system have to cooperate
- Low-level information and application information
What do Satyas finding imply in detail in terms of Cyber foraging?
- Mobile device communicates wireless with “Surrogate” fixed in infrastructure
- Surrogate communicates wired with cloud (for faster communication)
What was Satya’s prediction for the 21st century?
- Pervasive computing offers new exciting opportunities
- Pervasive computing is a rich open space; rules have to be written and borders need to be drawn
What has cyber foraging become today?
- No commercial deployment of cyber foraging
What is the big challenge with pervasive computing?
- No “killer application” so far
- Devices get more powerful
- Dataset too large
- Surrogate setup and maintenance -> Who pays?
- Is VR the answer?
- Real-time requirement
- Lack of computing power
- Low battery capacity
What are new research streams in pervasive computing?
- Big data also influences pervasive computing research
- > Pervasive data science emerged
What is pervasive data science?
- Pervasive computing research focuses on user experience
- We live in a data-centric world
- Combination of data-centric and user experience can lead to new opportunities
What are current challenges in pervasive data science ?
Data collection:
- Data ownership more complex (data fusion from multiple sources)
Analysis / Inference:
- Data Volume / Variety / Velocity
- Where to process data? (Locally, edge, cloud?)
Actuation:
- Visualization with pervasive computing technology
- Data-driven actuation (of e.g. environment)
Example areas of pervasive data science
- Autonomous vehicles
- Smart spaces
- Augmented cognition
Whats new about pervasive data scienece?
- Its not an isolated area -> intersection with trends is very relevant
- challenges of the data pipeline influence pervasive computing
- requires multi-disciplinary approach
