ABSTRACT
We address the problem of balancing the traffic load in multi-hop wireless networks. We consider a point-to-point communicating network with a uniform distribution of source-sink pairs. When routing along shortest paths, the nodes that are centrally located forward a disproportionate amount of traffic. This translates into increased congestion and energy consumption. However, the maximum load can be decreased if the packets follow curved paths. We show that the optimum such routing scheme can be expressed in terms of geometric optics and computed by linear programming. We then propose a practical solution, which we call Curveball Routing which achieves results not much worse than the optimum.
We evaluate our solution at three levels of fidelity: a Java high-level simulator, the ns2 simulator, and the Intel Mirage Sensor Network Testbed. Simulation results using the high-level simulator show that our solution successfully avoids the crowded center of the network, and reduces the maximum load by up to 40%. At the same time, the increase of the expected path length is minimal, i.e., only 8% on average. Simulation results using the ns2 simulator show that our solution can increase throughput on moderately loaded networks by up to 15%, while testbed results show a reduction in peak energy usage by up to 25%. Our prototype suggests that our solution is easily deployable.
- M. Kalantari, M. Shayman, "Design Optimization of Multi-Sink Sensor Networks by Analogy to Electrostatic Theory" IEEE WCNC, 2006Google Scholar
- P. Gupta and P. R. Kumar. The Capacity of Wireless Networks. IEEE Transactions on Information Theory, 2000.Google Scholar
- L. Jinyang, C. Blake, D. De Couto, H. Lee, R. Morris. "Capacity of Ad hoc Wireless Networks", ACM Mobicom 2001 Google ScholarDigital Library
- Rao A. Ratnasamy S., Papadimitriou C., Shenker S., Stoica I., "Geographic Routing without Location Information," presented at ACM Mobicom, 2003. Google ScholarDigital Library
- Wan C.Y. Eisenman S.B., Campbell A.T., "CODA: Congestion Detection and Avoidance in Sensor Networks" ACM SenSys 03. Google ScholarDigital Library
- Hull B. Jamieson K., Balakrishnan H.,"Mitigating Congestion in Wireless Sensor Networks,"ACM SenSys, 04. Google ScholarDigital Library
- Li, X., Kim, Y. J., Govidan, R., AND Hong, W. Multi-dimensional range queries in sensor networks, SenSys 2003 Google ScholarDigital Library
- Demibras, M., Arora, A., AND Gouda, M. A pursuer evader game for sensor networks. In Proc. of the Sixth Symposium on Self-Stabilizing Systems, 2003 Google ScholarDigital Library
- S. Baek and G. de Veciana, Spatial Energy Balancing Large-scale Wireless Multihop Networks, IEEE INFOCOM05Google Scholar
- K. Seada, M. Zuniga, A. Helmy, B. Krishnamachari, Energy-efficient forwarding strategies for geographic routing in lossy wireless sensor networks, ACM Sensys 2004 Google ScholarDigital Library
- ns2 simulator, http://www.isi.edu/nsnam/ns/Google Scholar
- TinyOs, http://www.tinyos.net.Google Scholar
- Jie Gao, Li Zhang, Load Balanced Short Path Routing in Wireless Networks, IEEE Infocom 2004 Google ScholarDigital Library
- G. Yashar and A. Keshavarzian, Load balancing in ad hoc networks: Single-path routing vs. multi-path routing, IEEE Infocom 2004.Google Scholar
- P. Gupta, P. R. Kumar, "Towards an Information Theory of Large Networks: An Achievable Rate Region", IEEE Transactions on Information Theory, 2003 Google ScholarDigital Library
- K. Seada, M. Zuniga, A. Helmy, B. Krishnamachari, "Energy Efficient Forwarding Strategies for Geographic Routing in Lossy Wireless Sensor Networks" ACM Sensys 2004 Google ScholarDigital Library
- Shenker, S.,Ratnasamy, S., Kapr, B., Govindan, R.,Estrin, D. Data-centric storage in sensornets. Sigcomm 2003 Google ScholarDigital Library
- Costas Busch, Malik Magdon Ismail, Jing Xi, Oblivious Routing on Geometric Networks, SPAA 2005 Google ScholarDigital Library
- Intel Mirage testbed, http://mirage.berkeley.intel-research.netGoogle Scholar
- Brad Karp, H. T. Kung, "GPSR: Greedy Perimeter Stateless Routing for Wireless Networks", Mobicom 2000 Google ScholarDigital Library
- Kim Y.J. Govindan R., Karp B. and Shenker S., Geographic Routing Made Practical, presented at Network Systems' Design and Implementation, NSDI, 2005. Google ScholarDigital Library
- Proof for Theorem 1 listed at: www.cs.berkeley.edu/~popa/proof_wireless_disc_load.pdfGoogle Scholar
- Greenstein B., Estrin, D., Govindan, R., Ratnasamy, S., Shenker, S. DIFS: A distributed index for features in sensor networks. In IEEE WSNA 2003.Google ScholarCross Ref
- http://research.microsoft.com/mesh/Google Scholar
- P.P. Pham and Sylvie Perreau, "Performance analysis of reactive shortest path and multi-path routing mechanism with load balance", IEEE Infocom 2003Google Scholar
- E. Hyytiä, P. Lassila, J. Virtamo, "Spatial Node Distribution of the Random Waypoint Mobility Model with Applications", IEEE Transactions on Mobile Computing, vol. 5, no. 6, 2006 Google ScholarDigital Library
- E. Hyytiä, J. Virtamo, "On Load Balancing in a Dense Wireless Multihop Network", NGI 2006, Valencia, SpainGoogle ScholarCross Ref
- J.Bruck, J. Gao, A. Jiang, "MAP: Medial Axis Based Geometric Routing in Sensor Networks", ACM Mobicom 2005 Google ScholarDigital Library
- R. Catanuto, S. Toumpis, G. Morabito, "Opti{c,m}al: Optical/Optimal Routing in Massively Dense Wireless Networks", IEEE Infocom 2007Google Scholar
Index Terms
- Balancing traffic load in wireless networks with curveball routing
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