isa5428: 普及計算 research issues

ISA5428: 普及計算Research Issues

金仲達教授清華大學資訊系統與應用研究所

九十三學年度第一學期

Pervasive Computing Research Issues-2

Source “Pervasive Computing: Vision and Challenges

”M. Satyanarayanan, Carnegie Mellon UniversityIEEE Personal Communications,pp. 10-17, August 2001


Outline Related fields

Distributed System Mobile Computing Pervasive Computing

Example scenario Drill down Conclusion


Distributed Systems Research involving two or more computers

connected by a network Areas foundational to pervasive computing:

Remote communication: protocol layering, RPC, end-to-end argument

Fault tolerance: atomic transactions, two phase commit

High availability: replica control, mirrored execution, recovery

Remote information access: caching, function shipping, distributed file system

Security: authentication, privacy


Mobile Computing (1/2) Research on building distributed systems

with mobile clients Principles in distributed system design still

apply 4 constraints to distinguish it from distributed

systems and demand new research Unpredictable variation in network quality Lowered trust and robustness of mobile elements Limited local resources imposed by weight and

size Battery power consumption


Mobile Computing (2/2) Research areas:

Mobile networking: mobile IP, ad hoc protocols, improving TCP performance in wireless networks

Mobile information access: selective control of data consistency

Support for adaptive applications: transcoding by proxies

System-level energy saving techniques: energy-aware adaptation, variable speed processor scheduling

Location sensitivity: location sensing, location-aware system behavior


Pervasive Computing Pervasive computing environment:

An environment saturated with computing and communication capability, yet so gracefully integrated with users that it becomes a “technology that disappears”

Subsume distributed computing and mobile computing, but incorporate 4 additional research thrusts (next figure)


4 Additional Research Areas (1/2) Effective use of smart spaces:

Space: an enclosed area or a well-defined open area Smart space: embedding computing infrastructure in

building infrastructure => physical/virtual converge Enable sensing and control of one world by the other

Example? Invisibility:

Minimal user distraction is a more practical goal Ex.: the environment continuously meets user

expectations and rarely presents him with surprises Some alerts may still be needed


4 Additional Research Areas (2/2) Localized scalability:

Increasing complexity in interactions between a user’s personal computing space and surroundings as well as other persons

Must consider scalability with physical distance Masking uneven conditioning

Different environments will have huge differences in their smartness, causing user distraction

One solution: have user’s personal computing space to compensate

Complete invisibility may be impossible, but reduced variability is possible


Outline Related fields Example scenario

Scenario 1 Scenario 2 Miss Capabilities

Drill down Conclusion


Scenario 1 Jane is at Gate 23 of an airport and would like to

e-mail her edited files through wireless connection, but the bandwidth is miserable

Aura, the pervasive computing environment, detects the situation, consults airport servers, and finds Gate 15 will have no flight in 1.5 hour

Aura suggests Jane to go to Gate 15 and prioritize her email

Jane accepts the suggestions Files are transmitted at Gate 15 and Aura

informs Jane when she needs to be back to gate


Scenario 2 Fred has to walk to a meeting from his office to

give a presentation, but he is not quite ready yet Fred grabs a handheld computer and starts

walking to the meeting Aura transfers his state from desktop to

handheld, and Fred does final editing with voice Aura infers Fred’s schedule, downloads materials

to projection computer and warms up projector Room’s face detection system recognizes some

unfamiliar faces and advises Fred not to show sensitive data


Some Key Aspects Scenario 1:

Proactivity: Aura can estimate how long the whole process takes and look ahead on her behalf

Combining knowledge from different layers: wireless congestion and boarding time

Smart space: provide information of wireless BW, flight time and gates, distance between gates

Scenario 2: Moving execution state across diverse platforms Automatic adjusting behavior to fit circumstances:

voice inputs Proactivity and smart space


Missing Capabilities Component technologies are simple and

basic They are available today

The challenge:The seamless integration of component technologies into a pervasive computing system Architecture Component synthesis System-level engineering


Outline Related fields Example scenario Drill down

User intent Cyber foraging Adaptation strategy High-level energy management Client thickness Context awareness Balancing proactivity and transparency Privacy and trust Impact on layering

Conclusion


The Model Each user is immersed in a personal

computing space that mediates all interactions with the pervasive computing elements in surroundings

As a command center System design: wearable computer? personal

assistant? thicker or thinner? what sensors and networking?

Context aware: how to know user’s state and surrounding, and modify behavior

How to cooperate and interact with infrastructure? with other persons?

How to roam and adapt? reconfigurable? => PDA with 802.11b, Java


Issue: Smart Object/Environment Provide services

System design: which embedded system? web server? sensors and actuators? NW?

Naming, registration, discovery Physical/virtual mapping Mobile management, energy management Service composition, I/O matching, adaptation,

environment monitoring


Issue: Infrastructure Support Infrastructures in real life

e.g., electricity, roads, ... Just there or even invisible, open platform

Internet infrastructure Domain name service (DNS registry) Services: cooperating routers, time servers TCP/IP: common formats/protocols Web standards

Extend the Internet to everyday objects


Infrastructure for Smart Objects Guarantee

Security, privacy, availability, reliability Provide services

Location (Where am I?) Context (Are we in a meeting?) Event delivery (Tell me when... happens) Brokering (Find something that…) Directory, discovery, registry Mobility, roaming, ...

How do we organize billions of mobile smart objects that are highly dynamic, short living,…?

For applications

built with smart objects

For smart objects


Issue: User Intent (1/2) A pervasive computing system must track

user intent Determine which actions will help, not hinder,

user Ex.: suppose a user is viewing video over a

network, whose bandwidth suddenly drops. Should the system

Reduce the fidelity of the video? Pause briefly to find another higher-bandwidth

connection? Advise the user that the task can no longer be

accomplished?Correct choice depends on what user is trying to

accomplish


User Intent (2/2) Today’s applications either have no idea abo

ut user intent (e.g. to support adaptation and proactivity), or do it badly

Issues: Can user intent be inferred, or does it have to be ex

plicitly provided? How is user intent represented internally? What are

represented? How does one characterize accuracy of knowledge?

Is incomplete or imprecise information useful? Will obtaining intent place an burden on the user?


Issue: Cyber Foraging (1/2) Dynamically augment computing

resources of end user devices with wired hardware infrastructure => surrogate

Usage: On entering a neighborhood, a device detects

the presence of surrogates and negotiates its use

Surrogates serve as gateway to the Internet and server for heavy computation

When the device leaves the neighborhood, surrogate binding is broken and staged data are discarded


Cyber Foraging (2/2) Issues:

How to discover the presence of surrogates? How to establish an appropriate level of trust?

How to amortize the cost of establishing trust? How to balance the load of surrogates? How to minimize latency in serving devices? How to deploy surrogates? How scalable? How to make surrogate uses seamless and

minimally intrusive for a user?


Issue: Adaptation Strategy (1/2) Necessary when there is significant

mismatch between the supply and demand of a resource, e.g. bandwidth, energy, computing cycles, ...

Three strategies for adaptation The client guides applications in changing their

behavior The client asks the environment to guarantee a

certain level of a resource The client suggests a corrective action to the

user


Adaptation Strategy (2/2) Issues:

How does a client choose between adaptation strategies? How strategies be changed seamlessly as user moves?

How to do resource reservation in a smart space? What are appropriate admission control policies? What API are needed to make reservation?

Will corrective actions be intrusive? How to do it, e.g. API, programming model?

What is the relationship between lowing fidelity and adaptation?


Issue: High-Level Energy Management Necessary because low-level techniques,

e.g. battery and circuit design, are insufficient

Issues: What high-level systems can be managed for

energy efficiency? (memory, application adaptation, …)

Are they intrusive to the user? Can user intent help?

Can smart spaces and surrogates be used to reduce energy demand on a mobile device?

How to tradeoff the energy used in remote execution with wireless connection?


Issue: Client Thickness How powerful does a mobile client need to be?

From bare-bones devices (high-resolution displays thru wireless to servers) to full-function clients (standalone & disconnected operation)

Issues: How to quantify thickness with env. conditioning, e.g., sensor

s added and better networking? How to migrate app. between clients of different thickness? How to cooperate with infrastructure? Can clients be reconfigurable to adapt to env.? Semi-portable infrastructure for less hospitable env.? How to roam transparently? especially from a benign environ

ment to a poor one? How to lower the cost of diversity in devices?


Issue: Context Awareness Needed for an environment minimally intrusive

Recognize user state and surroundings Make decisions proactively, modify behavior

accordingly Issues:

Obtaining information needed to function How to represent context internally? How to combine

it with system and application state? Where to store? How often to update and consult context

information? What services does the infrastructure have to

provide? How to track location? sense surroundings?


Issue: Proactivity and Transparency How not to annoy a user in a proactive

system?=> self-tuning according to user expertise and experiences

Issues: How are user preferences and tolerances

specified and taken into account? How to determine the right level of balance?


Issue: Privacy and Trust A pervasive computing environment needs

to monitor user actions almost continuously in order to be effective

Need mutual trust between environment and user

Issues: Tradeoff between seamless system behavior

and privacy/trust enforcement Any appropriate authentication techniques? How to specify security constraints? How to

specify one’s identity?


Issue: Impact on Layering Pervasive computing often requires

merging information from different layers a system

Issues: Relationship between layering and pervasive

computing How to create a new layer?


Conclusions Almost all sub domains in CS are affected

System infrastructures, networking, security, user interfaces, embedded systems, AI, perception, speech recognition,...

We are already moving in this direction XML, UDDI, mobile IP, Jini, ...

Systems integration is the key Many new and fascinating research problems

emerge!


The Field Is Burgeoning IEEE Pervasive magazine Springer Personal and Ubiquitous Computing Ubicomp Various links to universities, research institute

s, companies

isa5428: 普及計算 research issues

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