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This paper explores the mobility of publishers in distributed publish/subscribe systems, specifically focusing on the effects of publisher mobility on data dissemination. It discusses various scenarios and presents solutions to handle publisher mobility efficiently.
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Publisher Mobility in Distributed Publish/Subscribe Systems Vinod Muthusamy, Milenko Petrovic, Dapeng Gao, Hans-Arno Jacobsen University of Toronto June 10, 2005 4th International Workshop on Distributed Event-Based Systems (DEBS'05)
Motivation • Explosion of information producers • Blogs, wikis, podcasting, photo sharing • Mobility of users • Cell phones, PDAs, sensors • Mobile information producers • Traditionally wired publishers can increasingly be mobile • New types of publishers • SMS, camera phones, location based services • Pub/sub data dissemination • Well suited to mobile clients • Decoupling, filtering • Mobility of information producer has not been studied in pub/sub • Breaks common pub/sub assumption Mobile-ToPSS (University of Toronto)
Publisher Mobility Scenarios • Journalists with blogs • Update blogs on location • Upload pictures from camera phone • Police patrol car • Send status updates • Traffic, accidents, parts failures • Mail delivery • Track delivery status, location updates 1 2 Publisher Mobile-ToPSS (University of Toronto)
Agenda • Background • Context • Subscriber mobility • Publisher mobility • Problem • Solutions • Evaluation • Setup • Results • Conclusions Mobile-ToPSS (University of Toronto)
Context • Part of Toronto Publish/Subscribe System (ToPSS) • Improve expressiveness • Approximate matching, location queries, XML, RDF, composite subscriptions, historic subscriptions, etc. • Distributed issues • Fault tolerance, load balance, reliability • New environments • MANETs, P2P overlays, sensor networks • Mobile-ToPSS project • Subscriber mobility [MDM’04] • Based on JEDI, SIENA work • Publisher mobility [DEBS’05] • Effects of routing computations [Mobicom’05] • Content based routing in MANET [Mobiquitous’05] Mobile-ToPSS (University of Toronto)
Subscriber Subscriber Publisher Distributed Publish/Subscribe . . . . . . • Advertisements flooded • Create adv tree • Subscriptions along reverse adv path • Create multicast tree • Publications along reverse sub path Advertisements Subscriptions Publications Mobile-ToPSS (University of Toronto)
Subscriber Mobility Problem • Matching publications during disconnection • Stored by broker • Replayed upon reconnection • “State” transfer is expensive • Double message load with only 10% of mobile subscribers [MDM’04] • No state lost when publishers are disconnected • No problem with mobile publishers? 1 2 Subscriber Subscriber Subscriber Subscriber Mobile-ToPSS (University of Toronto)
t1 t3 t4 t5 At Old Broker Disconnected At New Broker t2 Disconnect Connect Can publish (moveout) (movein) new events Publisher Mobility Problem . . . . . . • Adv and sub trees • Moveout: both trees torn down • Movein: both trees rebuilt • Expensive • Network load: • May be # ads > # subs • No delivery until tree constructed • Distinguish temporary disconnections 1 2 moveout Publisher Mobile-ToPSS (University of Toronto)
t1 t3 t4 t5 At Old Broker Disconnected At New Broker t2 Disconnect Connect Can publish (moveout) (movein) new events Publisher Mobility Problem . . . . . . • Adv and sub trees • Moveout: both trees torn down • Movein: both trees rebuilt • Expensive • Network load: • May be # ads > # subs • No delivery until tree constructed • Distinguish temporary disconnections 1 2 movein Publisher Mobile-ToPSS (University of Toronto)
t1 t3 t4 t5 At Old Broker Disconnected At New Broker t2 Disconnect Connect Can publish (moveout) (movein) new events Prefetching Optimization . . . . . . • Exploits knowledge of future mobility patterns • Concurrent • Construction at new broker • Teardown at old broker • Tree construction time hidden from user 1 2 moveout Publisher Mobile-ToPSS (University of Toronto)
t1 t3 t4 t5 At Old Broker Disconnected At New Broker t2 Disconnect Connect Can publish (moveout) (movein) new events Prefetching Optimization . . . . . . • Exploits knowledge of future mobility patterns • Concurrent • Construction at new broker • Teardown at old broker • Tree construction time hidden from user 1 2 movein Publisher Mobile-ToPSS (University of Toronto)
t1 t3 t4 t5 At Old Broker Disconnected At New Broker t2 Disconnect Connect Can publish (moveout) (movein) new events Proxy Optimization . . . . . . • Maintain trees from several brokers • Advantageous if restricted mobility region 1 2 moveout movein Publisher Publisher Mobile-ToPSS (University of Toronto)
t1 t3 t4 t5 At Old Broker Disconnected At New Broker t2 Disconnect Connect Can publish (moveout) (movein) new events Delayed Optimization . . . . . . • Maintain trees at old broker for some time • Allow new tree to graft onto old tree • Remove extraneous portions of old tree 1 2 moveout movein Publisher Publisher Mobile-ToPSS (University of Toronto)
Evaluation: Setup • Simulation Environment • ns-2 network simulator • Implemented mobility optimizations • Parameters • Topology • Metropolitan Area Network • 4 levels of degree 4 64 leaf brokers • Subscribers: 500 • Publishers: 50 • Locality: random, 30%, 60%, 90% • Mobility • Static subscribers, mobile publishers • Random speeds (5km/h, 50km/h, 100km/h) • Metrics • Tree rebuild load • Tree rebuild time, delivery ratio • • • • • • 1 64 Mobile-ToPSS (University of Toronto)
Publisher Scalability • Standard and Prefetching >>Proxy and Delayed • Prefetching worse due to extra control messages • Delayed better due to smaller tree deltas Mobile-ToPSS (University of Toronto)
Publisher Scalability • Probe tree completion • Prefetching is fastest • Starts early • Standard is slowest • Almost 4s • Delayed close to Prefetching • Note: time is not known to publisher Mobile-ToPSS (University of Toronto)
Publisher Scalability • Tree rebuilding cost • Best: Delayed, Proxy • Worst: Standard, Prefetching • Tree rebuilding time • Best: Prefetching, Delayed • Worst: Standard • Prefetching • Good for the user • Bad for the network • Delayed • Good for user and network • Practical Mobile-ToPSS (University of Toronto)
Publication Locality • 250 publishers • Vary publication similarity • Standard and Prefetching approach Proxy and Delayed Mobile-ToPSS (University of Toronto)
Publication Locality • Time from publish to notification • Again, Standard and Prefetching approach Proxy and Delayed Mobile-ToPSS (University of Toronto)
Publication Locality • With sufficient publication similarity, optimizations have diminishing benefit • Tree rebuilding cost • Delivery latency Mobile-ToPSS (University of Toronto)
Conclusions • The publish/subscribe model is well suited to mobile applications • But publisher mobility has not been evaluated • Publisher mobility is expensive • Breaks conventional assumptions • Tree rebuilding imposes large cost • Must distinguish temporary vs. permanent disconnection • Delayed has best performance and is most practical • Future Work • Other scenarios: realistic traces, mobile subscribers • Develop more optimizations Mobile-ToPSS (University of Toronto)
Publisher Mobility in Distributed Publish/Subscribe Systems Thank you Mobile-ToPSS (University of Toronto)