1 / 27

Distributed Monitoring of Mesh Networks

Distributed Monitoring of Mesh Networks. Elizabeth Belding-Royer Mobility Management and Networking (MOMENT) Lab Dept. of Computer Science University of California, Santa Barbara Joint work with Krishna Ramachandran and Kevin Almeroth. Motivation: Monitoring.

cynara
Télécharger la présentation

Distributed Monitoring of Mesh Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Distributed Monitoring of Mesh Networks Elizabeth Belding-Royer Mobility Management and Networking (MOMENT) Lab Dept. of Computer Science University of California, Santa Barbara Joint work with Krishna Ramachandran and Kevin Almeroth

  2. Motivation: Monitoring • crucial for robust network operation • benefits to network operators, system designers, researchers • essential for evolving network technologies • critical last piece in the product conception-design-development-improvement loop • helps bridge the gap between the expected (simulations) and the unexpected (real-world)

  3. The Big Picture • Deployment • UCSB 25 node mesh network (NSF WHYNET project) • Monitoring and Measurement (DAMON) • UCSB mesh • IETF meetings • LocustWorld, IV deployments • 11,000 AODV nodes in 50+ countries • Simulation models • movement models • traffic models • AODV refinement

  4. The Big Picture • Deployment • UCSB 25 node mesh network (NSF WHYNET project) • Monitoring and Measurement (DAMON) • UCSB mesh • IETF meetings • LocustWorld, IV deployments • 11,000 AODV nodes in 50+ countries • Simulation models • movement models • traffic models • AODV refinement

  5. Outline • DAMON Design and Architecture • DAMON Implementation • DAMON@IETF • Conclusions

  6. Design Challenges • Device mobility • Resource constraints • Fluctuating link quality • Short-lived network connections

  7. Network State Pervasiveness Pervasiveness tradeoffs Design Choices: Pervasiveness of Monitoring Solution • Strategy of using a centralized network element fails • no hierarchical structure to mobile networks • mobility • Monitoring mobile networks requires pervasive solution • nodes participate in monitoring • Amount of pervasiveness • complete coverage strategy • limited coverage strategy

  8. Analysis Effort Pervasiveness Pervasiveness tradeoffs Design Choices: Pervasiveness of Monitoring Solution • Strategy of using a centralized network element fails • no hierarchical structure to mobile networks • mobility • Monitoring mobile networks requires pervasive solution • nodes participate in monitoring • Amount of pervasiveness • complete coverage strategy • limited coverage strategy

  9. Additional Design Choices • Number of data sinks • single sink? • multiple sinks? • Temporal property of monitoring information • determined by monitoring requirements • classifications • time dependent information, e.g. topology information • time independent information, e.g. packet logs • require differentiated handling of data

  10. DAMON: Distributed Architecture for MONitoring mobile networks • Overview • agents within network collect information • information stored at sinks • sink auto-discovery • resiliency to sink failures

  11. Architecture • Agents within network send monitoring information to sinks • Sinks emanate periodic beacons • facilitates auto-discovery and resiliency to sink failures

  12. Sink Auto-discovery • beacons contain agent instructions and hop count • agents use hop count to choose primary sink

  13. Sink Auto-discovery • Proximity-based association (hop count) • simple, low overhead • but, can lead to uneven distribution of agents to sinks • Tradeoff between beaconing frequency and sink detection latency

  14. Time dependent i.e., energy left on a device, neighbors typically small in size packaged into time dependent digests (TDDs) transmitted to sink frequently unreliable transmission Time independent i.e., packet logs, daily traffic statistics typically large in size broken into small-sized chunks called time independent digests (TIDs) reliable transmission Monitoring Information

  15. Client Framework Digest Classifier File Server • Packet Classifier: categorizes packets based on types, dispatches to appropriate packet handler • Beacon Listener: handles beacons • TDD dispatcher: handles received TDDs • Collectors: summarize routing table info or link quality estimates in TDDs and TIDs Collector1 … Collectorn Beacon Listener Packet Classifier TDD Dispatcher TID Dispatcher Network

  16. Client Framework Digest Classifier File Server • Digest Classifier: delivers digests created by Collectors to appropriate module • TDD Dispatcher for immediate transmission to sink • File Server for TIDs for later delivery to sink • TID Dispatcher: periodically retrieves digests for transmission to sink Collector1 … Collectorn Beacon Listener Packet Classifier TDD Dispatcher TID Dispatcher Network

  17. DAMON Implementation • Goals: • monitor ad hoc network behavior • monitor AODV performance • metrics of interest • throughput • traffic distribution • control packet overhead • mobility patterns • Implementations for Linux and Microsoft Windows

  18. DAMON Information Collection • AODV control packet summaries • RREQ, RREP, RERR, Hello • received packet counters • UDP payload and timestamp • Topology data • routing table deltas • AODV-NEIGHBOR TDDs sent every minute • Data traffic statistics • IP source and destination • application protocol type • packet size

  19. 58th IETF Meeting in Minneapolis, MN, November 9-14, 2003 Deployment goals: validate DAMON design track IETF topology evaluate AODV performance observe traffic/mobility patterns AODV Implementation Linux, Windows (thanks Intel!) 130+ downloads 20+ simultaneous ad hoc network members Network configuration complete coverage strategy one gateway provided Internet connectivity to ad hoc network users one sink deployed to collect information ad hoc network co-located with 23 IETF APs nodes used tool called PUDL to avoid unidirectional links DAMON@IETF

  20. PUDL • Periodic Uni-Directional Link detector • periodic unicast probes between each neighbor pair • sequence numbers used to measure reliability • under some threshold (40%), link filtered from AODV

  21. DAMON@IETF: Network Topology

  22. Network Troubleshooting • Connectivity problems with gateway reported during 13:00-15:30 IETF session on November 11th

  23. Lessons from Connectivity Information • No correlation between reception of unicast and broadcast packets • Routing protocols should select routes based on how reliably a path delivers unicast packets • Relying on thresholds to avoid unidirectional links can eliminate links that are necessary for connectivity

  24. Traffic Distribution Per Protocol, With Link Filtering Per Protocol, Without Link Filtering

  25. AODV Traffic Distribution

  26. Conclusions • Monitoring essential for robust network operation • DAMON overcomes challenges associated with mobile network monitoring • Future work: more DAMON deployments and analysis tools

  27. http://moment.cs.ucsb.edu/DAMON • Funding provided by NSF and Intel Corporation

More Related