Constant-Time Distributed Scheduling Policies for Ad Hoc Wireless Networks

We propose two new distributed scheduling policies for ad hoc wireless networks that can achieve provable capacity regions. Known scheduling policies that guarantee comparable capacity regions are either centralized or need computation time that increases with the size of the network. In contrast, the unique feature of the proposed distributed scheduling policies is that they are constant-time policies, i.e., the time needed for computing a schedule is independent of the network size. Hence, they can be easily deployed in large networks

[1]  Y. Chow.  On a Strong Law of Large Numbers for Martingales , 1967 .

[2]  Kenneth Steiglitz,et al.  Combinatorial Optimization: Algorithms and Complexity , 1981 .

[3]  Alon Itai,et al.  A Fast and Simple Randomized Parallel Algorithm for Maximal Matching , 1986, Inf. Process. Lett..

[4]  David Peleg,et al.  Distributed Computing: A Locality-Sensitive Approach , 1987 .

[5]  Bruce E. Hajek,et al.  Link scheduling in polynomial time , 1988, IEEE Trans. Inf. Theory.

[6]  P. R. Kumar,et al.  Dynamic instabilities and stabilization methods in distributed real-time scheduling of manufacturing systems , 1990 .

[7]  P. R. Kumar,et al.  Distributed scheduling based on due dates and buffer priorities , 1991 .

[8]  Leandros Tassiulas,et al.  Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks , 1992 .

[9]  Jr. C. Humes,et al.  A regulator stabilization technique: Kumar-Seidman revisited , 1994, IEEE Trans. Autom. Control..

[10]  J. Dai.  On Positive Harris Recurrence of Multiclass Queueing Networks: A Unified Approach Via Fluid Limit Models , 1995 .

[11]  Bruce Hajek,et al.  Scheduling nonuniform traffic in a packet-switching system with small propagation delay , 1997, TNET.

[12]  Alessandro Panconesi,et al.  On the distributed complexity of computing maximal matchings , 1997, SODA '98.

[13]  Leandros Tassiulas,et al.  Linear complexity algorithms for maximum throughput in radio networks and input queued switches , 1998, Proceedings. IEEE INFOCOM '98, the Conference on Computer Communications. Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies. Gateway to the 21st Century (Cat. No.98.

[14]  Panganamala Ramana Kumar,et al.  RHEINISCH-WESTFÄLISCHE TECHNISCHE HOCHSCHULE AACHEN , 2001 .

[15]  Balaji Prabhakar,et al.  The throughput of data switches with and without speedup , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[16]  J. Borwein,et al.  Convex Analysis And Nonlinear Optimization , 2000 .

[17]  Marco Ajmone Marsan,et al.  On the stability of input-queued switches with speed-up , 2001, TNET.

[18]  Atilla Eryilmaz,et al.  Stable scheduling policies for broadcast channels , 2002, Proceedings IEEE International Symposium on Information Theory,.

[19]  Atilla Eryilmaz,et al.  Stable scheduling policies for fading wireless channels , 2003, IEEE International Symposium on Information Theory, 2003. Proceedings..

[20]  Rene L. Cruz,et al.  Optimal routing, link scheduling and power control in multihop wireless networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[21]  Eytan Modiano,et al.  Dynamic power allocation and routing for time varying wireless networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[22]  S. Shakkottai,et al.  Hop-by-hop congestion control over a wireless multi-hop network , 2007, IEEE INFOCOM 2004.

[23]  Madhav V. Marathe,et al.  The distance-2 matching problem and its relationship to the MAC-Layer capacity of ad hoc wireless networks , 2004, IEEE Journal on Selected Areas in Communications.

[24]  Ness B. Shroff,et al.  The impact of imperfect scheduling on cross-layer rate control in wireless networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[25]  Eytan Modiano,et al.  Dynamic power allocation and routing for time-varying wireless networks , 2005 .

[26]  R. Srikant,et al.  Stable scheduling policies for fading wireless channels , 2005, IEEE/ACM Transactions on Networking.

[27]  R. Srikant,et al.  Regulated Maximal Matching: A Distributed Scheduling Algorithm for Multi-Hop Wireless Networks With Node-Exclusive Spectrum Sharing , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[28]  Stefan Hougardy,et al.  A linear-time approximation algorithm for weighted matchings in graphs , 2005, TALG.

[29]  Leandros Tassiulas,et al.  End-to-end bandwidth guarantees through fair local spectrum share in wireless ad-hoc networks , 2005, IEEE Transactions on Automatic Control.

[30]  R. Srikant,et al.  Scheduling Efficiency of Distributed Greedy Scheduling Algorithms in Wireless Networks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[31]  Eytan Modiano,et al.  Enabling distributed throughput maximization in wireless mesh networks: a partitioning approach , 2006, MobiCom '06.

[32]  Eytan Modiano,et al.  Maximizing throughput in wireless networks via gossiping , 2006, SIGMETRICS '06/Performance '06.

[33]  Koushik Kar,et al.  Achieving Queue-Length Stability Through Maximal Scheduling in Wireless Networks , 2006 .

[34]  Rayadurgam Srikant,et al.  Queue Length Stability of Maximal Greedy Schedules in Wireless Networks , 2006 .

[35]  Ness B. Shroff,et al.  Maximum weighted matching with interference constraints , 2006, Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW'06).

[36]  Xiaojun Lin,et al.  The impact of imperfect scheduling on cross-Layer congestion control in wireless networks , 2006, IEEE/ACM Transactions on Networking.

[37]  Xiaojun Lin,et al.  Constant-Time Distributed Scheduling Policies for Ad Hoc Wireless Networks , 2006, CDC.

[38]  J. Walrand,et al.  Sufficient conditions for stability of longest-queue-first scheduling: second-order properties using fluid limits , 2006, Advances in Applied Probability.

[39]  R. Srikant,et al.  Low-Complexity Distributed Scheduling Algorithms for Wireless Networks , 2007, INFOCOM.

[40]  Sanjay Shakkottai,et al.  Hop-by-Hop Congestion Control Over a Wireless Multi-Hop Network , 2004, IEEE/ACM Transactions on Networking.

[41]  Kyomin Jung,et al.  Low Delay Scheduling in Wireless Network , 2007, 2007 IEEE International Symposium on Information Theory.

[42]  Ness B. Shroff,et al.  Performance of Random Access Scheduling Schemes in Multi-Hop Wireless Networks , 2006, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[43]  E. Modiano,et al.  Distributed Throughput Maximization in Wireless Mesh Networks via Pre-Partitioning , 2008, IEEE/ACM Transactions on Networking.

[44]  Saikat Ray,et al.  Arbitrary Throughput Versus Complexity Tradeoffs in Wireless Networks Using Graph Partitioning , 2008, IEEE Transactions on Automatic Control.

[45]  Koushik Kar,et al.  Throughput and Fairness Guarantees Through Maximal Scheduling in Wireless Networks , 2008, IEEE Transactions on Information Theory.

[46]  Prasanna Chaporkar,et al.  Throughput Guarantees Through Maximal Scheduling in Wireless Networks , 2008 .

[47]  Xiaojun Lin,et al.  The Impact of Imperfect Scheduling on Cross-Layer Rate Control in Multihop Wireless Networks , 2022 .