The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.03 - March (2012 vol.11)
pp: 414-426
Changhee Joo , Korea University of Technology and Education, Cheonan
ABSTRACT
In recent years, there has been a significant amount of work done in developing low-complexity scheduling schemes to achieve high performance in multihop wireless networks. A centralized suboptimal scheduling policy, called Greedy Maximal Scheduling (GMS) is a good candidate because its empirically observed performance is close to optimal in a variety of network settings. However, its distributed realization requires high complexity, which becomes a major obstacle for practical implementation. In this paper, we develop simple distributed greedy algorithms for scheduling in multihop wireless networks. We reduce the complexity by relaxing the global ordering requirement of GMS, up to near zero. Simulation results show that the new algorithms approximate the performance of GMS, and outperform the state-of-the-art distributed scheduling policies.
INDEX TERMS
Wireless scheduling, distributed system, greedy algorithm.
CITATION
Changhee Joo, "Local Greedy Approximation for Scheduling in Multihop Wireless Networks", IEEE Transactions on Mobile Computing, vol.11, no. 3, pp. 414-426, March 2012, doi:10.1109/TMC.2011.33
REFERENCES
[1] C. Joo, “A Local Greedy Scheduling Scheme with Provable Performance Guarantee,” Proc. ACM MobiHoc, May 2008.
[2] L. Tassiulas and A. Ephremides, “Stability Properties of Constrained Queueing Systems and Scheduling Policies for Maximal Throughput in Multihop Radio Networks,” IEEE Trans. Automatic Control, vol. 37, no. 12, pp. 1936-1948, Dec. 1992.
[3] X. Lin and N.B. Shroff, “The Impact of Imperfect Scheduling on Cross-Layer Congestion Control in Wireless Networks,” IEEE/ACM Trans. Networking, vol. 14, no. 2, pp. 302-315, Apr. 2006.
[4] R. Preis, “Linear Time 1/2-Approximation Algorithm for Maximum Weighted Matching in General Graphs,” Proc. Symp. Theoretical Aspects of Computer Science, 1999.
[5] J.-H. Hoepman, “Simple Distributed Weighted Matchings,” http://arxiv.org/abs/cs0410047v1, Oct. 2004.
[6] E. Modiano, D. Shah, and G. Zussman, “Maximizing Throughput in Wireless Networks via Gossiping,” Sigmetrics Performance Evaluation Rev., vol. 34, no. 1, pp. 27-38, 2006.
[7] Y. Yi and S. Shakkottai, “Learning Contention Patterns and Adapting to Load/Topology Changes in a MAC Scheduling Algorithm,” Proc. IEEE Workshop Wireless Mess Networks, 2006.
[8] S. Sanghavi, L. Bui, and R. Srikant, “Distributed Link Scheduling with Constant Overhead,” Proc. ACM Sigmetrics Int'l Conf. Measurement and Modeling of Computer Systems, pp. 313-324, June 2007.
[9] A. Eryilmaz, A. Ozdaglar, and E. Modiano, “Polynomial Complexity Algorithms for Full Utilization of Multi-Hop Wireless Networks,” Proc. IEEE INFOCOM, May 2007.
[10] X. Lin and S. Rasool, “Constant-Time Distributed Scheduling Policies for Ad Hoc Wireless Networks,” Proc. IEEE Conf. Decision and Control (CDC '06), Dec. 2006.
[11] A. Gupta, X. Lin, and R. Srikant, “Low-Complexity Distributed Scheduling Algorithms for Wireless Networks,” Proc. IEEE INFOCOM, pp. 1631-1639, May 2007.
[12] C. Joo and N.B. Shroff, “Performance of Random Access Scheduling Schemes in Multi-Hop Wireless Networks,” IEEE/ACM Trans. Networking, vol. 17, no. 5, pp. 1481-1493, Oct. 2009.
[13] L. Bui, A. Eryilmaz, R. Srikant, and X. Wu, “Joint Asynchronous Congestion Control and Distributed Scheduling for Multi-Hop Wireless Networks,” Proc. IEEE INFOCOM, pp. 1-12, Apr. 2006.
[14] A. Eryilmaz and R. Srikant, “Fair Resource Allocation in Wireless Networks Using Queue-Length Based Scheduling and Congestion Control,” Proc. IEEE INFOCOM, Mar. 2005.
[15] C.H. Papadimitriou and K. Steiglitz, Combinatorial Optimization: Algorithms and Complexity. Prentice-Hall, 1982.
[16] C. Joo, G. Sharma, N.B. Shroff, and R.R. Mazumdar, “On the Complexity of Scheduling in Wireless Networks,” EURASIP J. Wireless Comm. and Networking, Oct. 2010.
[17] D. Avis, “A Survey of Heuristics for the Weighted Matching Problem,” Networks, vol. 13, no. 4, pp. 475-493, 1983.
[18] M. Leconte, J. Ni, and R. Srikant, “Improved Bounds on the Throughput Efficiency of Greedy Maximal Scheduling in Wireless Networks,” Proc. ACM MobiHoc, pp. 165-174, 2009.
[19] P. Chaporkar, K. Kar, and S. Sarkar, “Throughput Guarantees in Maximal Scheduling in Wireless Networks,” Proc. 43rd Ann. Allerton Conf. Comm., Control and Computing, Sept. 2005.
[20] X. Wu and R. Srikant, “Scheduling Efficiency of Distributed Greedy Scheduling Algorithms in Wireless Networks,” Proc. IEEE INFOCOM, Apr. 2006.
[21] G. Sharma, N.B. Shroff, and R.R. Mazumdar, “Joint Congestion Control and Distributed Scheduling for Throughput Guarantees in Wireless Networks,” Proc. IEEE INFOCOM, pp. 2072-2080, 2007.
[22] L. Jiang and J. Walrand, “A Distributed Algorithm for Optimal Throughput and Fairness in Wireless Networks with a General Interference Model,” Proc. 46th Ann. Allerton Conf. Comm., Control, and Computing, 2008.
[23] P. Marbach and A. Eryilmaz, “A Backlog-Based CSMA-Mechanism to Achieve Fairness and Throughput-Optimality in Multihop Wireless Networks,” Proc. 46th Ann. Allerton Conf. Comm., Control, and Computing, 2008.
[24] J. Ni and R. Srikant, “Distributed CSMA/CA Algorithms for Achieving Maximum Throughput in Wireless Networks,” Proc. Information Theory and Applications Workshop, 2009.
[25] B. Hajek and G. Sasaki, “Link Scheduling in Polynominal Time,” IEEE Trans. Information Theory, vol. 34, no. 5, pp. 910-917, Sept. 1988.
[26] S. Sarkar and L. Tassiulas, “End-to-End Bandwidth Guarantees through Fair Local Spectrum Share in Wireless Ad-Hoc Networks,” Proc. IEEE Conf. Decision and Control (CDC '03), pp. 564-569, Dec. 2003.
[27] E. Leonardi, M. Mellia, F. Neri, and M.A. Marsan, “On the Stability of Input-Queued Switches with Speed-Up,” IEEE/ACM Trans. Networking, vol. 9, no. 1, pp. 104-118, Feb. 2001.
[28] A. Dimakis and J. Walrand, “Sufficient Conditions for Stability of Longest-Queue-First Scheduling: Second-Order Properties Using Fluid Limits,” Advances in Applied Probability, vol. 38, no. 2, pp. 505-521, 2006.
[29] A. Brzezinski, G. Zussman, and E. Modiano, “Enabling Distributed Throughput Maximization in Wireless Mesh Networks: A Partitioning Approach,” Proc. ACM MobiCom, pp. 26-37, 2006.
[30] G. Zussman, A. Brzezinski, and E. Modiano, “Multihop Local Pooling for Distributed Throughput Maximization in Wireless Networks,” Proc. IEEE INFOCOM, Apr. 2008.
[31] C. Joo, X. Lin, and N.B. Shroff, “Understanding the Capacity Region of the Greedy Maximal Scheduling Algorithm in Multi-Hop Wireless Networks,” IEEE/ACM Trans. Networking, vol. 17, no. 4, pp. 1132-1145, Aug. 2009.
[32] C. Joo, X. Lin, and N.B. Shroff, “Greedy Maximal Matching: Performance Limits for Arbitrary Network Graphs under the Node-Exclusive Interference Model,” IEEE Trans. Automatic Control, vol. 54, no. 2, pp. 1132-1145, Aug. 2009.
[33] J.G. Dai, “On Positive Harris Recurrence of Multiclass Queueing Networks: A Unified Approach via Fluid Limit Models,” Annals of Applied Probability, vol. 5, no. 1, pp. 49-77, 1995.
[34] R. Diestel, Graph Theory, third ed. Springer, 2005.
[35] P. Gupta and P.R. Kumar, “Critical Power for Asymptotic Connectivity in Wireless Networks,” Stochastic Analysis, Control, Optimization and Applications: A Volume in Honor of W.H. Fleming, pp. 547-566, Springer, 1998.
19 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool