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1 Odyssey – Support for Mobile, Adaptive Applications Examples and some slides from Brian Noble and Kip Walker (contributors to the project)

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Presentation on theme: "1 Odyssey – Support for Mobile, Adaptive Applications Examples and some slides from Brian Noble and Kip Walker (contributors to the project)"— Presentation transcript:

1 1 Odyssey – Support for Mobile, Adaptive Applications Examples and some slides from Brian Noble and Kip Walker (contributors to the project)

2 2 A Glimpse of the Future  Imagine you are a tourist in Paris  with a wearable computer  wireless access to remote services  unobtrusive heads-up display, microphone, earphones  speech for computer interactions  online language translation  Let’s go......

3 3 What Makes This Science Fiction?  Lack of hardware?  No! We have what we need.  Lack of applications?  Nope - we have those too.  Need a system capable of coping with the problems of mobility  Odyssey to the rescue...

4 4 Problems with Mobility  Mobile elements are resource-poor  relative to static elements of same era  weight, power, size constraints  Mobility leads to communication uncertainty  enormous variation in bandwidth & latency  intermittent connectivity  Power management is a concern  actions may have to be slowed or deferred  communication costs energy  need to rely on resources of remote servers,  but may not be able to reach them!

5 5 Adaptation is Key  Highly dynamic environment – adaptation key to good performance  Who adapts?  System? take advantage of good times Behave ok during bad times CODA  This paper: applications also must adapt Change expectations depending on surrounding state End to end argument?

6 6 Client Adaptation  Make mobile clients more robust by offering adaptation  rely on servers when possible  function autonomously if needed  monitor and adjust to current conditions  Change application expectations

7 7 Adaptive Applications  applications consume resources network bandwidth, CPU cycles, battery power, disk space, $$$  resources are variable  …so…  applications adapt use of resources as resource quality changes

8 8 Who Controls Adaptation  The Operating System?  Individual applications?  Both!  … Application-Aware Adaptation

9 9 Application-Aware Adaptation  Application only (laissez faire)  What if different applications compete for the resources?  OS only (application-transparent)  Does not differentiate between applications (student viewing a video of a lecture vs. a video teleconference)  Joint responsibility in Odyssey (application-aware)  Several ways to divide the functionality – odyssey only one

10 10 What Knobs Do We Have?  Where work gets done  let powerful remote servers do the work  How snazzy the data is: “Fidelity”  degrade data meaningfully before giving to mobile host  Fidelity has many dimensions  one is universal: consistency  others depend on data type movies: frame rate, frame quality geographical databases: feature set, minimum feature size  tradeoffs are application-dependent  Discussion – anything else?

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12 12 Applications  Video  server offers movie at several levels of fidelity  application plays the track that the current bandwidth can support  xanim: split into client and server  WWW  “distillation server” degrades data before shipping to client  images can be compressed  HTML can be summarized  Netscape: client-side proxy + remote distillation server  Speech Recognition  local/remote/hybrid execution  Janus: support remote recognition method, hybrid  Other?

13 13 Odyssey A Platform for adaptive mobile data access Built a prototype for Un*x as OS extension Provides a small API to the application Implementation: Need a central component for resource monitoring and management (Viceroy) Need data aware components that offer fidelity choices (Wardens)

14 14 Viceroy and Wardens  System-level data differentiation through wardens  specialized code components (a la device drivers)  provides system-level support to manage a data type  trusted entities (unlike applications)  Wardens subordinate to viceroy  single, central component  type-independent, system-level support  responsible for all resource allocation, arbitration  central point of authority and control for Odyssey

15 15 Odyssey Architecture Upcalls Interceptor Odyssey runtime Application kernel Tsop, request Video warden Web Warden viceroy Sys calls Odyssey calls

16 16 Resource Negotiation  Applications give viceroy a window of tolerance for some resource  viceroy monitors resource availability  if it leaves window, notifies application via upcall  Currently focus only on network bandwidth; what are other resources of interest? Available bandwidth Fid. 1Fid. 2Fid. 3Fid. 4

17 17 Viceroy  Monitors resources and notifies applications of any changes in resource levels  Does this apply to non-mobile applications?  Viceroy acts as a single point of resource control  Applications must be able to specify what changes of resources are of interest to them  Reporting everything is too expensive since it crosses the OS to user boundary  Solution – application specifies a window of tolerance in a resource request system call Viceroy does an upcall if resource availability moves outside the window

18 18 Wardens  Wardens are code components that manage type specific operations  Wardens manage communication with the various servers  They also offer the fidelity menu to applications  Type specific operations can be customized using wardens (e.g., caching)  To avoid API explosion, one system call (type- specific operation tsop() is provided  Tsop is similar to the un*x ioctl()  Can also be used to request type specific operations

19 19 Operational Model  Control loop: 1. Select fidelity (application) 2. Place request (system call) 3. Detect change 4. Notify application

20 20 Agility  An Odyssey client must estimate the quality of network paths used by various applications.  Odyssey records:  Round-trip time  Throughput  Odyssey updates its estimates of latency and bandwidth once every half second.  Aside, Noble’s group followed up with agility estimation work for ad hoc networks

21 21 Agility (cont.)

22 22 Agility (cont.)

23 23 Stability  Pursuing agility while completely sacrificing stability can be counterproductive.  Rapidly switching  Low-fidelity  Variable latency  Stability is properly incorporated by individual application.  When notifying an application, the viceroy can include information about the expected variance of estimate.

24 24 Client Server Based Solutions  Server, typically:  Stationary host  Possibly replicated  Resource rich  Holds long running state  Client, typically:  Mobile host, intermittent connectivity  Resource poor, etc..  Communication restricted between client and server, no mobile-to-mobile communication

25 25 Extended Client-Server Model  Classic client-server systems assume that the location of client and server hosts do not change and also the connection among them does not change  Functionality between client and server is statically partitioned  Extended Client server Architecture thus deals with these inconsistencies in network connections and location specifics

26 26 Extended Client-Server Model  Thin client architecture  Full client architecture  Flexible client architecture

27 27 Thin client architecture

28 28 Full-Client Architecture  Can support disconnected or weakly connected client  The full client architecture supports emulations of functions of server at client host  Light weight servers or proxy  E.G CODA, WebExpress

29 29 Flexible Client-Server Architecture  Generalizes both thin client and full client architecture  Connection between client and server can be dynamically established

30 30 Client-Server Application Adaptation  The Rover toolkit supports application aware adaptation through the use of RDO http://www.pdos.lcs.mit.edu/rover/  RDOs are relocatable dynamic objects (more in a second)  Philosophy/Motivation similar to Odyssey; approach is different  Odyssey changes application in place  Rover allows responsibility to be exchanged between client and server  Benefits to Application Designers  Application designers have semantic knowledge  Can tightly couple data with program code and manage resources

31 31 Key Ideas  Relocatable Dynamic Objects  Objects (code and data) that can be exchanged between the client and the server – why?  Queued Remote Procedure Calls (QRPCs)  Asynchronous/non-blocking RPC calls  If disconnected, application can continue execution  RPC executed upon reconnection

32 32 Programmer’s tasks  Define RDO’s  for data types manipulated by the application  For data exchanged between client and server  Partition application:  Portions that run on client and those that run on server  They communicate using QRPC  Define methods for updating objects  Includes conflict detection and resolution

33 33 Using Rover  Programmer links code with toolkit  Application “cooperates” with runtime environment  Imports RDOs  Invokes methods on RDOs  Export logs of invocation to servers  Reconcile copies of objects with those at server  Similar to agents?  Similar to process migration?

34 34

35 35  The application specific proxy has been proposed as an intermediary between client and server  It performs storage intensive and computation intensive tasks  Proxy reduces Bandwidth demands and allow legacy and non standard client to communicate with the server Proxy-Based Application Adaptation

36 36 Mobile Objects/Agents  Pieces of code that can freely roam the network  Mobile objects allow clients to download the server code to mobile host for execution  They can maintain state information and make intelligent decisions  Challenge in using mobile objects?  Frequently disconnected or weak environment

37 37 Collaborative Groups  Division of members into groups  Members can access data for the group  A client is able to access data residing on server to which it is communicating or any machine holding the copy of the database, including personal laptop, should be willing to server read and write requests from nearby machines  E.g., Bayou system

38 38 Mobile Data Access Some slides and Diagram courtesy Mike Franklin, UMD (Lead the Broadcast Disks project)

39 39 Mobile Data Access  Mobile data access enables the delivery of server data and the maintenance of client-server data  Data Access strategies in mobile environment can be characterized by  Data delivery  Data organization  Consistency requirement  Data Delivery Modes  Client –pull  Server-push  Hybrid delivery  In fact, this is instance of the more general problem of scalable content delivery

40 40 Dissemination based Application  Applications where content is delivered to a large number of clients  Stock tickers  Sport tickers  Real-time video broadcasts  Software updates (Got redhat 9 yet?)  Entertainment/News delivery  Others?  How well does it scale? Use the web to deliver  Heavy traffic, central point of failure

41 41 What is the problem?  Asymmetric applications, but web is symmetric  Asymmetry: client to server ration  Mouse and keyboard clicks vs. content and update  Asymmetry  Couch Potatoes  Most people are informational couch potatoes  …thankfully

42 42 Push is the answer?  Traditional pull (e.g., RPC) requires two way interaction  “push” can solve some types of asymmetry  Update – no need for polling  Client-Server ratio: clients don’t need to bother  Network: reduce or eliminate back channel use

43 43 Push and Pull  Overloaded terms  Push vs. pull is just one dimension to compare data delivery mechanisms  Different mechanisms for data delivery can and should be applied at different points in the system

44 44 Server Data Dissemination  With mobile nodes, asymmetric communication and resources emphasized  Which alternatives does it make sense to use?  Scalability problems for applications with asymmetrical communication  Solution: Broadcast –based dissemination  Broadcast disk  Indexing on air  Increases query time  Decreases Listening time

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