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Peer-to-Peer Overlay Networks in an Event-Based Middleware

Peer-to-Peer Overlay Networks in an Event-Based Middleware. DEBS’03, San Diego, CA, USA, June 2003. Overlay Broker Networks. Distributed pub/sub systems Mapping of brokers to physical nodes Specification of overlay topology Efficiency, reliability, manageability, …. Today

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Peer-to-Peer Overlay Networks in an Event-Based Middleware

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  1. Peer-to-Peer Overlay Networks in an Event-Based Middleware DEBS’03, San Diego, CA, USA, June 2003

  2. Overlay Broker Networks • Distributed pub/sub systems • Mapping of brokers to physical nodes • Specification of overlay topology • Efficiency, reliability, manageability, … Today • Static neighbour lists • Difficult at deployment time • Require global view • Depend on physical network topology • Hierarchical topologies • Hard to maintain global properties • No redundancy Tomorrow • Self-managing overlays • Add more brokers on demand • Not only useful for large-scale • Adaptive overlay networks • Reflect current network situation • Lead to more efficient event dissemination • Evaluation

  3. Overview • Overlay Broker Networks • Peer-to-Peer Techniques • Hermes • Type- and Attribute-Based Routing • Simulational Evaluation • Routing Efficiency • Space Efficiency and Distribution • Message Complexity • Conclusions

  4. Peer-to-Peer Techniques • Distributed hash tables (Pastry, CAN, Chord, …) • Overlay network of nodes with unique ids • Hash operation from key to nodeid • Scalable and efficient • Locality properties • Advantages of P2P for publish/subscribe • Higher abstraction for building pub/sub systems • Content-based routing algorithm deals with hash keys • P2P overlay handles neighbouring set for event brokers route (msg, key)

  5. R B B B B B B P P P P S S P P P P S S S S Hermes • Hermes, an event-based middleware • P2P overlay network • Evaluation of its efficiency vs. Siena-like approach • Type- and attribute-based publish/subscribe • Event Clients • Event Brokers • Local Broker, Rendezvous Node • Rendezvous Nodes • Set up on a per type basis • Hash of event type name gives key for DHT • Ensure that advertisements and subscriptions join in the network

  6. Type- and Attribute-Based Routing Advertisement Messages • Routed towards RN by publishers • Create entries in advertisement routing tables along the way Subscription Messages • Routed towards RN by subscribers • Follow the reverse path of advertisements • Create entries in subscription routing tables along the way Publication Messages • Follow the reverse path of subscriptions • Get filtered along the way

  7. Simulational Evaluation • Evaluation of content-based pub/sub in simulator • Large-scale deployment for experiments difficult • Realistic network topologies and model for simulation • E.g. notification latency, hop count, routing cost, … • Scale reflects corporate deployment (102 event brokers) • Keep number of subscribers small if routing unaffected DSSim • Discrete event simulator • Transit stub network model • Visualisation plug-ins Pan • Pastry-like routing CovAdv • Siena-like pub/sub • Static set of neighbours • Acyclic topology Hermes • Pub/sub

  8. Routing Efficiency • Overlay networks used in experiments • Hermes: Sequential addition to closest existing broker w.r.t latency • CovAdv: Pre-computed minimum spanning tree Latency per notification (500 brokers; single subscriber per broker) • Quality of the overlay • Decreases  tree is more populated • CovAdv (closest broker) has worst latency • CovAdv (min span) is optimal • Hermes is in between

  9. Space Efficiency and Distribution Routing table sizes • Hermes does not broadcast advertisements • Hermes has slightly less subscription state due to better routing • Converge to same value as tables become full Routing table distribution • CovAdv: Majority of broker has 20 routing table entries • Hermes: No broker has more than 15; some have none

  10. Message Complexity Message numbers (Advs, Subs, Pubs) (100 event types) • Hermes sends fewer publications than CovAdv due to its better routing • Hermes sends moresubscriptions than CovAdv due to RNs • Number of advertisements staysconstant

  11. Conclusions • Self-managing & adaptive overlay networks are needed • Distributed Hash Tables are helpful • Evaluation through simulation • Contrast different kinds of pub/sub approaches • Peer-to-peer routing with RNs is efficient • Future Work • Fault-tolerance • Dynamic network environments

  12. Thank You Any Questions?

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