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Supporting Disconnected Operations in Publish/Subscribe Systems

Supporting Disconnected Operations in Publish/Subscribe Systems. Vinod Muthusamy Joint work with Milenko Petrovic, Ioana Burcea, H.-Arno Jacobsen, Eyal de Lara University of Toronto. 2004 IEEE International Conference on Mobile Data Management. Agenda. Part I – Publish/Subscribe

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Supporting Disconnected Operations in Publish/Subscribe Systems

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  1. Supporting Disconnected Operations in Publish/Subscribe Systems Vinod Muthusamy Joint work withMilenko Petrovic, Ioana Burcea, H.-Arno Jacobsen, Eyal de Lara University of Toronto 2004 IEEE International Conference on Mobile Data Management

  2. Agenda • Part I – Publish/Subscribe • Centralized/distributed models • Benefits • Applications • Part II – Mobile Publish/Subscribe • Disconnected operation in distributed publish/subscribe systems • Motivation and Problem • Solutions • Evaluation • Factors • Results • Conclusions

  3. Notification Notification The Publish/Subscribe Model TSX Stock markets NASDAQ NYSE Publisher Publisher AMGN=58 Publications IBM=84 ORCL=12 JNJ=58 HON=24 INTC=19 MSFT=27 Broker Subscriptions: IBM > 85 ORCL < 10 JNJ > 60 Subscriptions Subscriber Subscriber

  4. Distributed Publish/Subscribe Broker • Hierarchy of brokers [Siena, JEDI] • Subscriptions to root • Publications to root and multicast down to interested subscribers Broker Broker Broker Broker Broker stocks/ibm/* Publisher stocks/* stocks/oracle

  5. Publish/Subscribe Benefits • Simple interface • Decoupling of producers and consumers of data • Address • Content-based routing • Anonymity • Platform • Space • Time • Representation (semantic) • Efficient data dissemination (scalability) • Push model • Multicast

  6. Publish/Subscribe Applications • News dissemination • Location based services • Workflow management • E-commerce • Auctions • Distributed gaming • Software updates delivery • Sensor networks • Existing systems • Research: ToPSS, Siena, JEDI, Gryphon, Hermes • Industry: IBM, Precache, TIBCO, Talarian

  7. Part II • How does disconnected operation work in distributed publish/subscribe systems? • Why is disconnected operation a problem? • What are some solutions? • How do these solutions perform?

  8. Disconnected Operation: Motivation Broker • User’s laptop connected at work • Disconnect at the end of the day • Reconnect at home • Events published while a subscriber is disconnected should be stored somewhere and replayed upon reconnection Broker Broker Subscriber

  9. t1 t2 t3 t4 At Old Broker Disconnected At New Broker Disconnect Connect Receive (moveout) (movein) new events Disconnected Operation [JEDI] Publisher • Subscriber receives publications • Subscriber disconnects • Broker stores publications • Subscriber connects • Transfer state to new broker & replay old publications • New publications go directly to subscriber Broker Broker Broker Subscriber

  10. t1 t2 t3 t4 At Old Broker Disconnected At New Broker Disconnect Connect Receive (moveout) (movein) new events Disconnected Operation [JEDI] Publisher • Subscriber receives publications • Subscriber disconnects • Broker stores publications • Subscriber connects • Transfer state to new broker & replay old publications • New publications go directly to subscriber Broker Broker Broker Subscriber

  11. t1 t2 t3 t4 At Old Broker Disconnected At New Broker Disconnect Connect Receive (moveout) (movein) new events Disconnected Operation [JEDI] Publisher • Subscriber receives publications • Subscriber disconnects • Broker stores publications • Subscriber connects • Transfer state to new broker & replay old publications • New publications go directly to subscriber Broker Broker Broker moveout Subscriber

  12. t1 t2 t3 t4 At Old Broker Disconnected At New Broker Disconnect Connect Receive (moveout) (movein) new events Disconnected Operation [JEDI] Publisher • Subscriber receives publications • Subscriber disconnects • Broker stores publications • Subscriber connects • Transfer state to new broker & replay old publications • New publications go directly to subscriber Broker Broker Broker Subscriber

  13. t1 t2 t3 t4 At Old Broker Disconnected At New Broker Disconnect Connect Receive (moveout) (movein) new events Disconnected Operation [JEDI] Publisher • Subscriber receives publications • Subscriber disconnects • Broker stores publications • Subscriber connects • Transfer state to new broker & replay old publications • New publications go directly to subscriber Broker Broker Broker movein

  14. t1 t2 t3 t4 At Old Broker Disconnected At New Broker Disconnect Connect Receive (moveout) (movein) new events Disconnected Operation [JEDI] Publisher • Subscriber receives publications • Subscriber disconnects • Broker stores publications • Subscriber connects • Transfer state to new broker & replay old publications • New publications go directly to subscriber Broker Broker Broker

  15. t1 t2 t3 t4 At Old Broker Disconnected At New Broker Disconnect Connect Receive (moveout) (movein) new events Disconnected Operation [JEDI] Publisher • Subscriber receives publications • Subscriber disconnects • Broker stores publications • Subscriber connects • Transfer state to new broker & replay old publications • New publications go directly to subscriber Broker Broker Broker

  16. Problem: Unicast State Transfer Broker Broker Broker Broker Broker Broker • State transfer is inefficient [unicast] • Publish/subscribe is efficient [multicast] • What’s the bandwidth overhead of unicast state transfer?

  17. t1 t2 t3 t4 At Old Broker Disconnected At New Broker tp Disconnect Connect Receive (moveout) (movein) new events State Transfer Optimizations:Prefetching Broker • Eagerly migrate state while the user is disconnected • Exploits knowledge of future mobility patterns • Shortens perceived length of disconnection to the system • Less state to transfer • State transfer period hidden from user Broker Broker moveout

  18. State Transfer Optimizations:Logging Broker • Brokers cache recent publications • Exploits locality • Only partial state transfer needed if locality exists • Overhead could be worse if no locality exists • Requires cache space at brokers Broker Broker

  19. State Transfer Optimizations:Home-Broker Broker • Mobile client logically reconnects to “home” broker • Eliminates state transfer overhead • Increases perceived disconnection period • Unicast transfer even when connected Broker Broker movein

  20. Network Bandwidth and latency of links Broker placement Broker topology Number of brokers Evaluation:Factors Affecting Mobility Mobility • Connection and disconnection periods • Predictive or repetitive mobility • Group mobility Application • No. of publishers and subscribers • Publication rate • Subscription specificity • Subscription (interest) locality • Message size

  21. Evaluation: Setup • Simulation Environment • NS2 network simulator • Implemented state transfer optimizations • Parameters • Topology • Metropolitan Area Network • 4 levels of degree 4  64 leaf brokers • Subscribers: 200, 400, 600, 800 • Publishers: 100 • Locality: random, 30%, 60%, 90% • Metric • Total message traffic • State transfer overhead (unicast/multicast) • • • • • • 1 64

  22. City center Outskirts Outskirts 1 64 Downtown Commute Scenario • Simulate evening commute home • Subscribers work downtown (20 inner brokers) • Start commute between 4:00 pm and 6:00 pm • 40% live in city center (30 inner brokers) • Take 15 min to 45 min to commute • 60% live in outskirts (34 outer brokers) • Take 45 min to 90 min to commute • Few total disconnections • Long disconnection periods

  23. Commute Scenario:Average Overhead • Standard: almost 100% overhead • Logging: Slight improvement • Prefetching: negligible overhead • Home broker: poor due to sustained unicast • Peak overhead results • Up to 3x for Standard • Up to 27x for Home-broker

  24. Commute Scenario:Total Message Cost • 800 subscribers • Same relative performance • Message cost tracks # of state transfers • Home-broker overhead even after reconnection • Max 10% concurrent state transfers

  25. Random Scenario • More ad-hoc mobility • Subscriber starts at random broker • Disconnects for 10 min to 30 min • Walk (5 km/h), city driving (50 km/h), highway driving (100 km/h) • Reconnects to a random broker within range • Remains connected for 10 min to 30 min • (repeat) • More disconnections • Shorter disconnection periods

  26. Random Scenario:Average Overhead • Standard: 100% overhead • Prefetching overhead now noticeable • Due to shorter disconnections • Logging diverges more from Standard • Due to hidden increase in locality with population • Due to more disconnections

  27. Random Scenario:Effect of Locality • 800 subscribers • Adjust subscription locality by varying % of subscribers with identical subscriptions • Logging can approach “ideal” Prefetching • Others’ increasing overhead is due to decreasing multicast, and constant unicast

  28. Random Scenario:Effect of Log Size • For Logging approach • Log size 0, 400, 800, 1200 events • Diminishing returns of increasing log size

  29. Pervasive Scenario • Persistent connectivity • Similar mobility patterns as Random scenario • Disconnections are few seconds long • E.g. Cellular handoffs between cells • Many disconnections • Short disconnection periods

  30. Pervasive Scenario:Average Overhead • Event migration is small portion of state transfer overhead • Similar overhead (except home-broker) • Due to very short disconnec-tions

  31. Conclusions • The publish/subscribe model lends itself well to mobile applications • Mobility can break a distributed pub/sub system • Network overhead can double with only 10% concurrent movein’s • Stored events typically dominate overhead, not subscriptions • With sufficient locality, Logging approaches Prefetching • Future Work • Other scenarios: realistic traces, mobile publishers • Investigate effects of state transfer traffic on latency • Develop more state transfer optimizations • Multicast state transfer • Logging at intermediate brokers • Smarter cache replacement policies

  32. Thank You

  33. Pub/Sub Optimizations Covering Advertisements SubscriptionsAdvertisementsPublications Broker Broker stocks/* stocks/* Broker Broker Broker Broker stocks/* stocks/ibm/* Publisher • Reduce subscription traffic • Reduce publication traffic to the root

  34. Covering and Advertisements • Our scenarios did not benefit significantly from covering and ads • Forwarding of events dominate overhead • 98% of overhead in Commute and Random scenarios • Covering only helps to quench subscriptions • There is little subscriber locality (in our scenarios) • Most events must propagate to the root broker • Ads only help to quench upstream publications

  35. Toronto Publish/Subscribe System (ToPSS) Research Areas ToPSS (matching algorithms) A-ToPSS (approximate) M-ToPSS (mobile) p2p-ToPSS (peer-to-peer) S-ToPSS (semantic) ToPSS L-ToPSS (location-based correlation) Rb-ToPSS (rule-based) Information consumers subscribe to information of interest. Information producers publish information. ToPSS-broker(s) match and routerelevant information to interested subscribers. X-ToPSS (semi-structured data; XML) Ad hoc-ToPSS (ad hoc networking) persistent-ToPSS (Subject Spaces) Federated-ToPSS (federation of ToPSS brokers)

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