On the Interdependence of Congestion and Contention in Wireless Sensor Networks

1. On the Interdependence of Congestion and Contention in Wireless Sensor Networks

2. Outline • Wireless Sensor Networks (WSN) • Congestion and contention in WSN • Related Work • Goals • Evaluation Environment • Results • Conclusions

3. Several thousand nodes Distance of tens of feet Densities as high as 20 nodes/m2 Sink Internet, Satellite, UAV Sink Task Manager Wireless Sensor Networks • I.F.Akyildiz, W.Su, Y. Sankarasubramaniam, E. Cayirci, • “Wireless Sensor Networks: A Survey”, Computer Networks Journal, March 2002. • I.F.Akyildiz, M.C. Vuran, O. B. Akan, W. Su, • “Wireless Sensor Networks: A Survey REVISITED” Computer Networks Journal, 2005.

4. Wireless Sensor Networks (WSN) • Characterized by the collaborative information transmission of densely deployed nodes • High density leads to • Local contention • Network-wide congestion • In fact, the level of local contention and the network congestion are closely coupled due to the multi-hop nature of sensor networks

5. Network Congestion • Network congestion • leads to waste of communication resources • leads to waste of energy resources • hampers event detection reliability at the sink • The WSN architecture employs unique sources for congestion • Communication in a shared wireless medium • Multi-hop nature of WSN • Limited buffer size

6. Main Sources for Congestion • Channel Contention and Interference • Contention occurs between • different flows • different packets of a flow • Outgoing channel capacity becomes time variant • High density exacerbates the impact of contention • Number of Event Sources • Higher number of event sources improve event detection efficiency • Closely located source nodes increase contention • Increased number of flows increase congestion

7. Main Sources for Congestion (2) • Packet Collisions • Packet drops due to collisions may indicate lower congestion level • Reporting Rate • Increasing reporting rate causes network congestion even if local contention is minimized • Many-to-one Nature • Event communication between multiple sources and single sink causes bottleneck around the sink A comprehensive analysis of network congestion and local contention is required for WSN

8. Related Work • In [1], channel load information is incorporated into congestion detection and control mechanisms. • [2] proposes transmission control scheme for use at the MAC layer. • In [3], congestion detection is performed through buffer occupancy measurements. • In [4], the backoff window of each node is linked to its local congestion state. • It has been advocated in [5] that MAC layer support is beneficial in congestion detection and control algorithms. [1] C. Y. Wan, et.al., “CODA: Congestion Detection and Avoidance in Sensor Networks,” in Proc. ACM SENSYS 2003, November 2003. [2] A. Woo, et.al., “A Transmission Control Scheme for Media Access in Sensor Networks,” in Proc. ACM MOBICOM 2001, pp.221-235, 2001. [3] O. B. Akan and I. F. Akyildiz, “ESRT: Event-to-Sink Reliable Transport for Wireless Sensor Networks,” to appear in IEEE/ACM Trans. Networking, October 2005. [4] I. Aad, et.al., “Differentiation Mechanisms for IEEE 802.11,” in Proc. IEEE INFOCOM 2001, pp. 209-218, April 2001. [5] B. Hull, et.al., “Techniques for Mitigating Congestion in Sensor Networks,” in Proc. ACM SENSYS 2004, November 2004.

9. Related Work (2) • Cross-layer approaches in congestion detection and control is necessary in WSN • There is a close coupling between local contention and network-wide congestion • The interdependence of congestion and contention are yet to be studied

10. Goals • In this work, we investigate the interactions between contention resolution and congestion control mechanisms • What are the consequences of independent operations of local contention resolution and end-to-end congestion control mechanisms? • What is the effect of local retransmissions? • What are the effects of network parameters such as buffer sizes of the sensors, number of sources and contention window size? • Can cross layer interaction be performed by preserving the modularity of layered design or are cross-layer designs required?

11. Evaluation Environment and Performance Metrics • ns-2 simulations in a 100x100m2 sensor field • One node selected as sink • Nodes in an event area send information to the sink • Performance Metrics

12. non-congested region transition region rthlow rthhigh congested region Number of Sources • Event radius values 20m, 30m, 40m • As reporting rate is increased reliability drops significantly • Increasing number of sources, i.e., event radius, degrades reliability • A common shape is observed for reliability

13. Number of Sources (2) • Close correlation between MAC layer errors and buffer overflows • Buffer overflows start to build up as MAC layer errors saturate • The maximum value of MAC layer error percentage occurs at rthlow • For higher number of sources, congestion occurs at lower reporting rate

14. Buffer Size • Buffer size values 5, 50, 100, 250 • Change in buffer size has minimal effect on reliability

15. Buffer Size (2) • Increasing buffer length increases percentage of MAC layer errors • Small buffer sizes lead to lower latency • If end-to-end latency is important, lower buffer sizes lead to acceptable reliability • Since contention dominates, smaller buffer sizes are actually beneficial in WSN

16. MAC Layer Retransmissions • Retransmission limit values 4, 7, 10 • Decreasing local reliability affects overall reliability • rthlow occurs at lower values for decreased Rtxmax • Increasing Rtxmax further have minimal effect on reliability

17. MAC Layer Retransmissions (2) • Local reliability level affects MAC layer errors • In the congested region, end-to-end latency increases significantly • Local reliability mechanism has converse effect on end-to-end latency • Latency saturates in congested region and local reliability level affects the saturation reporting rate value

18. Contention Window • Average contention window values for source and router nodes • Source nodes are located close • Increasing reporting rate increases contention • Contention occurs mainly in the vicinity of source nodes • Adjusting initial contention window size, CWmin, may affect network performance

19. Contention Window (2) • Adjusting buffer size and CWmin leads to higher reliability • In non-congested region, lower CWmin size is better • As the reporting rate is increased, increasing CWmin improves reliability by 10% • Adaptive contention window size adjustments lead to efficient results

20. Reasons for Packet Drops • Distribution of packet drops • In non-congested region, packet drops are due to MAC and routing layers • As reporting rate is increased, MAC layer errors saturate and buffer overflows dominate • Adaptive reliability mechanisms are required considering traffic load

21. Energy Efficiency • Energy consumption increases with reporting rate in non-congested and transition regions • Energy consumption saturates in the congested region • Number of sources significantly effect energy consumption

22. Energy Efficiency (2) • Energy consumption is not significantly affected by buffer size or Rtxmax • The effects of these parameters on other performance metrics enable energy-aware, adaptive protocols to be implemented

23. Conclusions • The interdependence between local contention and network-wide congestion is investigated • Higher event resolution vs. higher contention • Increasing number of sources improves event reliability • Higher contention degrades network performance since sources are closely located • Small buffer sizes may be beneficial • For low reliability, low latency demanding applications, smaller buffer size leads to more efficient performance • Local reliability vs. End-to-end reliability • Higher reporting rate can be supported by local reliability • In addition to local reliability, end-to-end congestion and reliability mechanisms required

24. Conclusions (2) • Traffic-aware contention window size • The knowledge of reporting rate enables initial contention window size adjustments • The effect of buffer size change can be given by contention window size adjustments • Adaptive cross-layer reliability mechanism required • Packet drop distribution changes dynamically • Reliability mechanisms need to adopt to sources of drops • Energy efficient adjustments are possible • Energy consumption is minimally affected by buffer size and retransmission limit adjustments • Local interactions directly affect overall network performance