Transport Layer CachingMechanisms and Optimization ICCRG meeting @ IETF-85, Atlanta, GA, USA              Nestor Tiglao   ...
Outline     Background     Transport layer caching model     Main results     Related IETF work     Congestion Contro...
Poor TCP Performance in Wireless Multi-hop Networks   Higher bit error rates and packet loss   Underlying MAC protocols ...
Proposed Solutions   Distributed TCP Caching (Dunkels et al., 2004)   TCP Support for Sensor Networks (Braun et al., 200...
Transport Layer Caching Model   Analyze benefit of intermediate caching in lossy    networks, e.g., wireless sensor netwo...
Analytical Results   Reliable delivery   Based on DTSN semantic – DATA, NACK, MACK (MAC    –layer ACK)   RTS/CTS disabl...
Analytical ResultsSingle flow: Cost vs. Cache Size                   ICCCRG @ IETF85, Altanta, GA, USA   7
Analytical ResultsSingle flow: Cost vs. Hop Length                   ICCCRG @ IETF85, Altanta, GA, USA   8
Analytical ResultsSingle flow: Cost vs. Retry Limit                    ICCCRG @ IETF85, Altanta, GA, USA   9
Analytical ResultsConcurrent flows: Cache Partitioning   Caching weight assigned to flow i at node n, in   At each node...
Cache Partitioning Example                  Raw weights                                                                Nor...
Concurrent FlowsGrid Topology                   ICCCRG @ IETF85, Altanta, GA, USA   12
Concurrent flows: 10x10 Grid NetworkUniform Error Rates     C n  20     li  9                 ICCCRG @ IETF85, Altanta, ...
Concurrent FlowsNon-uniform Error Rates   Heuristic: assign higher weight to flows experiencing    higher error rates and...
Concurrent Flows : 10x10 Square NetworkNon-uniform Error Rates  vertical   0.2  C n  20  li  9                     ICC...
Concurrent Flows : 9x5 RectangularNon-uniform Error Rates   vertical   0.2   C n  20   li  9                      ICCC...
Concurrent Flows : 10x10 GridConvergecast Pattern  1 sink node  99 source nodes  C n  20                    ICCCRG @ IETF...
Simulation Results   ns-2 simulator   Performance evaluation     Better energy efficiency     Improve goodput     Bet...
CA-TCP (draft-sarolahti-irtf-catcp-00)   TCP options     Cachable segments are supplied with a “Content Label”     TCP ...
Congestion Control   Window-based/Rate-based     AIMD approach   Bandwidth Delay Product (BDP-based)     BDPs represen...
Congestion ControlDependency on BDPReference: [6]                 ICCCRG @ IETF85, Altanta, GA, USA   21
Summary  Transport layer caching can significantly improve   performance in loss recovery  Cache partitioning is crucial...
Thank you!
References 1.   Nestor Michael C. Tiglao, António M. Grilo, An analytical model for transport layer caching in      wirele...
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Transport Layer Caching Mechanisms and Optimization

  1. 1. Transport Layer CachingMechanisms and Optimization ICCRG meeting @ IETF-85, Atlanta, GA, USA Nestor Tiglao INESC-ID/IST nestor.tiglao@inesc-id.pt
  2. 2. Outline  Background  Transport layer caching model  Main results  Related IETF work  Congestion Control  Summary ICCCRG @ IETF85, Altanta, GA, USA 2
  3. 3. Poor TCP Performance in Wireless Multi-hop Networks  Higher bit error rates and packet loss  Underlying MAC protocols (exponential back-off, hidden/exposed nodes)  TCP end-to-end error and congestion control mechanisms TCP Segment loss TCP ACK lossReference: [3] ICCCRG @ IETF85, Altanta, GA, USA 3
  4. 4. Proposed Solutions  Distributed TCP Caching (Dunkels et al., 2004)  TCP Support for Sensor Networks (Braun et al., 2007)Reference: [3] ICCCRG @ IETF85, Altanta, GA, USA 4
  5. 5. Transport Layer Caching Model  Analyze benefit of intermediate caching in lossy networks, e.g., wireless sensor networks  Probabilistic model  Link-layer component  Transport-layer component  Define: Probability of Effective Progress of the packet, PEPi (t , h) ICCCRG @ IETF85, Altanta, GA, USA 5
  6. 6. Analytical Results  Reliable delivery  Based on DTSN semantic – DATA, NACK, MACK (MAC –layer ACK)  RTS/CTS disabled  Performance metric: Transmission cost, ci  Function of cache size, C n  Effective error probability associated with the transmission of a packet taking into account the maximum number of MAC retries,  ICCCRG @ IETF85, Altanta, GA, USA 6
  7. 7. Analytical ResultsSingle flow: Cost vs. Cache Size ICCCRG @ IETF85, Altanta, GA, USA 7
  8. 8. Analytical ResultsSingle flow: Cost vs. Hop Length ICCCRG @ IETF85, Altanta, GA, USA 8
  9. 9. Analytical ResultsSingle flow: Cost vs. Retry Limit ICCCRG @ IETF85, Altanta, GA, USA 9
  10. 10. Analytical ResultsConcurrent flows: Cache Partitioning  Caching weight assigned to flow i at node n, in  At each node, fraction of cache memory allocated to each flow i that crosses the node n in in  Fn n  j 1 j  Cache Partitioning Policies  Uniform  Increasing  Decreasing  U Shape  Inverted U Shape ICCCRG @ IETF85, Altanta, GA, USA 10
  11. 11. Cache Partitioning Example Raw weights Normalized weights Red flow – Uniform Blue flow – Decreasing Green flow – U Shape ICCCRG @ IETF85, Altanta, GA, USA 11
  12. 12. Concurrent FlowsGrid Topology ICCCRG @ IETF85, Altanta, GA, USA 12
  13. 13. Concurrent flows: 10x10 Grid NetworkUniform Error Rates C n  20 li  9 ICCCRG @ IETF85, Altanta, GA, USA 13
  14. 14. Concurrent FlowsNon-uniform Error Rates  Heuristic: assign higher weight to flows experiencing higher error rates and with greater hop length i (k ) i  ( i (k ),i (k 1)   i (k 1),i (k) ) (li ) DATA NACK ICCCRG @ IETF85, Altanta, GA, USA 14
  15. 15. Concurrent Flows : 10x10 Square NetworkNon-uniform Error Rates vertical   0.2 C n  20 li  9 ICCCRG @ IETF85, Altanta, GA, USA 15
  16. 16. Concurrent Flows : 9x5 RectangularNon-uniform Error Rates vertical   0.2 C n  20 li  9 ICCCRG @ IETF85, Altanta, GA, USA 16
  17. 17. Concurrent Flows : 10x10 GridConvergecast Pattern 1 sink node 99 source nodes C n  20 ICCCRG @ IETF85, Altanta, GA, USA 17
  18. 18. Simulation Results  ns-2 simulator  Performance evaluation  Better energy efficiency  Improve goodput  Better delay performance  Can improve fairness (Jain’s fairness index)  Refer to [7] ICCCRG @ IETF85, Altanta, GA, USA 18
  19. 19. CA-TCP (draft-sarolahti-irtf-catcp-00)  TCP options  Cachable segments are supplied with a “Content Label”  TCP ACKs contain “Content Request”  Cache can send segments on behalf of the sender  Perhaps cache partitioning can be explored  Example: CDNs ICCCRG @ IETF85, Altanta, GA, USA 19
  20. 20. Congestion Control  Window-based/Rate-based  AIMD approach  Bandwidth Delay Product (BDP-based)  BDPs represent the maximum amount of unacknowledged data that are allowed in flight at any moment  Multi-hop wireless networks based on spatial reuse, e.g. 802.11 MAC, BDP = 1/4 x path length ICCCRG @ IETF85, Altanta, GA, USA 20
  21. 21. Congestion ControlDependency on BDPReference: [6] ICCCRG @ IETF85, Altanta, GA, USA 21
  22. 22. Summary  Transport layer caching can significantly improve performance in loss recovery  Cache partitioning is crucial  New approaches to congestion control  Possible applications  Enhancements to CA-TCP  Caching-enabled transport protocol for LLNs  Caching in 6LoWPAN fragmentation recovery, http://tools.ietf.org/html/draft-thubert-6lowpan-simple- fragment-recovery-07 ICCCRG @ IETF85, Altanta, GA, USA 22
  23. 23. Thank you!
  24. 24. References 1. Nestor Michael C. Tiglao, António M. Grilo, An analytical model for transport layer caching in wireless sensor networks, Performance Evaluation, Volume 69, Issue 5, May 2012, Pages 227-245, ISSN 0166-5316. 2. Marchi, Bruno, António Grilo, and Mário Nunes. DTSN: distributed transport for sensor networks. Computers and Communications, 2007. ISCC 2007. 12th IEEE Symposium on. IEEE, 2007. 3. Philipp Hurni, Ulrich Bürgi, Markus Anwander, and Torsten Braun. 2012. TCP performance optimizations for wireless sensor networks. In Proceedings of the 9th European conference on Wireless Sensor Networks (EWSN12), Gian Pietro Picco and Wendi Heinzelman (Eds.). Springer- Verlag, Berlin, Heidelberg, 17-32. 4. Dunkels, Adam, et al. Distributed TCP Caching for Wireless Sensor Networks. Proceedings of the 3 rd Annual Mediterranean Ad-Hoc Networks Workshop. 2004. 5. Braun, Torsten, Thiemo Voigt, and Adam Dunkels. TCP support for sensor networks. Wireless on Demand Network Systems and Services, 2007. WONS07. Fourth Annual Conference on. IEEE, 2007. 6. Xia Li; Peng-Yong Kong; Kee-Chaing Chua; , DTPA: A Reliable Datagram Transport Protocol over Ad Hoc Networks, Mobile Computing, IEEE Transactions on , vol.7, no.10, pp.1285-1294, Oct. 2008 7. Tiglao, N; Grilo, A., Optimal Cache Partitioning in Reliable Data Transport for Wireless Sensor Networks, Proceedings of the 4th Workshop on Network Control and Optimization – NETCOOP’10, Ghent, Belgium, pp. 90-96, Nov. 29-Dec. 1, 2010. ICCCRG @ IETF85, Altanta, GA, USA 24

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