Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Joint congestion control and distributed scheduling for throughput guarantees in wireless networks

Published: 17 December 2010 Publication History

Abstract

We consider the problem of throughput-optimal cross-layer design of wireless networks. We propose a joint congestion control and scheduling algorithm that achieves a fraction 1/dI(G) of the capacity region, where dI(G) depends on certain structural properties of the underlying connectivity graph G of the wireless network, and also on the type of interference constraints. For a wide range of wireless networks, dI(G) can be upper bounded by a constant, independent of the number of nodes in the network. The scheduling element of our algorithm is the maximal scheduling policy. Although this scheduling policy has been considered in several previous works, the challenges underlying its practical implementation in a fully distributed manner while accounting for necessary message exchanges have not been addressed in the literature. In this article, we propose two algorithms for the distributed implementation of the maximal scheduling policy accounting for message exchanges, and analytically show that they still can achieve the performance guarantee under the 1-hop and 2-hop interference models. We also evaluate the performance of our cross-layer solutions in more realistic network settings with imperfect synchronization under the Signal-to-Interference-Plus-Noise Ratio (SINR) interference model, and compare with the standard layered approaches such as TCP over IEEE 802.11b DCF networks.

Supplementary Material

Sharma Appendix (a5-sharma-apndx.pdf)
Online appendix to joint congestion control and distributed scheduling for throughput guarantees in wireless networks on article 5.

References

[1]
Balakrishnan, H., Barrett, C. L., Kumar, V. S. A., Marathe, M. V., and Thite, S. 2004. The distance-2 matching problem and its relationship to the MAC-layer capacity of ad hoc wireless networks. IEEE J. Select. Areas Comm. 22, 6, 1069--1079.
[2]
Bui, L., Eryilmaz, A., Srikant, R., and Wu, X. 2006. Joint asynchronous congestion control and distributed scheduling for multi-hop wireless networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).
[3]
Chaporkar, P., Kar, K., and Sarkar, S. 2005. Throughput guarantees through maximal scheduling in wireless networks. In 43rd Annual Allerton Conference on Communications, Control, and Computing.
[4]
Eryilmaz, A., Ozdaglar, A., Shah, D., and Modiano, E. 2009. Distributed cross-layer algorithms for the optimal control of multi-hop wireless networks. IEEE/ACM Trans. Netw. 18, 2, 638--651.
[5]
Gast, M. S. 2005. 802.11 Wireless Networks: The Definitive Guide. O'Reilly Media, Inc.
[6]
Georgiadis, L., Neely, M. J., and Tassiulas, L. 2006. Resource allocation and cross-layer control in wireless networks. Found. Trends Netw. 1, 1, 1--144.
[7]
Hajek, B. and Sasaki, G. 1988. Link scheduling in polynomial time. IEEE Trans. Inform. Theory 34, 5, 910--917.
[8]
Hoepman, J.-H. 2004. Simple distributed weighted matchings. Arxiv preprint cs.DC/0410047.
[9]
Joo, C., Lin, X., and Shroff, N. B. 2008. Understanding the capacity region of the greedy maximal scheduling algorithm in multi-hop wireless networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).
[10]
Joo, C. and Shroff, N. B. 2007. Performance of random access scheduling schemes in multi-hop wireless networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).
[11]
Kelly, F., Maulloo, A., and Tan, D. 1998. Rate control in communication networks: Shadow prices, proportional fairness and stability. J. Oper. Res. Soc. 49, 237--252.
[12]
Lin, X. and Rasool, S. 2006. Constant-time distributed scheduling policies for ad hoc wireless networks. In Proceedings of the IEEE Conference on Decision and Control (CDC).
[13]
Lin, X. and Shroff, N. B. 2005. The impact of imperfect scheduling on cross-layer rate control in multihop wireless networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).
[14]
Lin, X., Shroff, N. B., and Srikant, R. 2008. On the connection-level stability of congestion-controlled communication networks. IEEE Trans. Inform. Theory 54, 5, 2317--2338.
[15]
Low, S. H. and Lapsley, D. E. 1999. Optimization flow control—I: Basic algorithm and convergence. IEEE/ACM Trans. Netw. 7, 6, 861--874.
[16]
McKeown, N. 1995. Scheduling algorithms for input-queued cell switches. Ph.D. thesis, University of California at Berkeley.
[17]
Modiano, E., Shah, D., and Zussman, G. 2006. Maximizing throughput in wireless networks via gossiping. Sigmetrics Perform. Eval. Rev. 34, 1, 27--38.
[18]
Neely, M. J., Modiano, E., and Li, C. 2008. Fairness and optimal stochastic control for heterogeneous networks. IEEE/ACM Trans. Netw. 16, 2, 396--409.
[19]
Neely, M. J., Modiano, E., and Rohrs, C. E. 2003. Power allocation and routing in multibeam satellites with time-varying channels. IEEE/ACM Trans. Netw. 11, 1, 138--152.
[20]
Peleg, D. 2000. Distributed Computing: A Locality-Sensitive Approach. Society for Industrial and Applied Mathematics, Philadelphia, PA.
[21]
Sarkar, S. and Tassiulas, L. 2005. End-to-End bandwidth guarantees through fair local spectrum share in wireless ad-hoc networks. IEEE Trans. Autom. Control 50, 9, 1246--1259.
[22]
Sharma, G., Joo, C., Mazumdar, R. R., and Shroff, N. B. 2009. Appendix to joint congestion control and distributed scheduling for throughput guarantees in wireless networks. ACM Trans. Model. Comput. Simul. 21, 1.
[23]
Sharma, G., Joo, C., and Shroff, N. B. 2006a. Distributed scheduling schemes for throughput guarantees in wireless networks. In Proceedings of the 44th Annual Allerton Conference on Communications, Control, and Computing.
[24]
Sharma, G., Mazumdar, R. R., and Shroff, N. B. 2006b. Maximum weighted matching with interference constraints. In Proceedings of the IEEE FAWN Conference.
[25]
Sharma, G., Mazumdar, R. R., and Shroff, N. B. 2006c. On the complexity of scheduling in wireless networks. In Proceedings of the ACM International Conference on Mobile Computing and Networking (MobiCom).
[26]
Stolyar, A. L. 2005. Maximizing queueing network utility subject to stability: Greedy primal-dual algorithm. Queu. Syst. 50, 4, 401--457.
[27]
Tassiulas, L. 1998. Linear complexity algorithms for maximum throughput in radio networks and input queued switches. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).
[28]
Tassiulas, L. and Ephremides, A. 1992a. Jointly optimal routing and scheduling in packet radio networks. IEEE Trans. Inform. Theory 38, 1, 165--168.
[29]
Tassiulas, L. and Ephremides, A. 1992b. Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks. IEEE Trans. Autom. Control 37, 12, 1936--1948.
[30]
Wu, X., Srikant, R., and Perkins, J. R. 2007. Scheduling Efficiency of Distributed Greedy Scheduling Algorithms in Wireless Networks. IEEE Trans. Mobile Comput. 6, 6, 595--605.
[31]
Xiao, L., Johansson, M., and Boyd, S. 2004. Simultaneous routing and resource allocation via dual decomposition. IEEE Trans. Comm. 52, 7, 1136--1144.
[32]
Yaiche, H., Mazumdar, R., and Rosenberg, C. 2000. A Game-theoretic Framework for Bandwidth Allocation and Pricing in Broadband Networks. IEEE/ACM Trans. Netw. 8, 5, 667--678.

Cited By

View all
  • (2022)Distributed and Local Scheduling Algorithms for mmWave Integrated Access and BackhaulIEEE/ACM Transactions on Networking10.1109/TNET.2022.315436730:4(1749-1764)Online publication date: 17-Mar-2022
  • (2022)Congestion Avoidance Using Enhanced Blue AlgorithmWireless Personal Communications10.1007/s11277-022-10028-1128:3(1963-1984)Online publication date: 9-Sep-2022
  • (2019)Tree Sampling for Detection of Information Source in Densely Connected NetworksElectronics10.3390/electronics80505878:5(587)Online publication date: 27-May-2019
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Modeling and Computer Simulation
ACM Transactions on Modeling and Computer Simulation  Volume 21, Issue 1
December 2010
183 pages
ISSN:1049-3301
EISSN:1558-1195
DOI:10.1145/1870085
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 December 2010
Accepted: 01 October 2009
Revised: 01 September 2009
Received: 01 June 2009
Published in TOMACS Volume 21, Issue 1

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Cross-layer design
  2. distributed algorithm
  3. maximal scheduling
  4. wireless communication systems simulation and modeling

Qualifiers

  • Research-article
  • Research
  • Refereed

Funding Sources

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)6
  • Downloads (Last 6 weeks)0
Reflects downloads up to 30 Aug 2024

Other Metrics

Citations

Cited By

View all
  • (2022)Distributed and Local Scheduling Algorithms for mmWave Integrated Access and BackhaulIEEE/ACM Transactions on Networking10.1109/TNET.2022.315436730:4(1749-1764)Online publication date: 17-Mar-2022
  • (2022)Congestion Avoidance Using Enhanced Blue AlgorithmWireless Personal Communications10.1007/s11277-022-10028-1128:3(1963-1984)Online publication date: 9-Sep-2022
  • (2019)Tree Sampling for Detection of Information Source in Densely Connected NetworksElectronics10.3390/electronics80505878:5(587)Online publication date: 27-May-2019
  • (2018)I-CSMA: A Link-Scheduling Algorithm for Wireless Networks Based on Ising ModelIEEE Transactions on Control of Network Systems10.1109/TCNS.2017.26735395:3(1038-1050)Online publication date: Sep-2018
  • (2017)Providing Guaranteed Protection in Multi-Hop Wireless Networks with Interference ConstraintsIEEE Transactions on Mobile Computing10.1109/TMC.2017.269600116:12(3502-3512)Online publication date: 1-Dec-2017
  • (2017)Improving the queue size and delay performance with the I-CSMA link scheduling algorithmComputer Networks10.1016/j.comnet.2017.04.011122(105-119)Online publication date: Jul-2017
  • (2016)Distributed greedy approximation to maximum weighted independent set for scheduling with fading channelsIEEE/ACM Transactions on Networking10.1109/TNET.2015.241786124:3(1476-1488)Online publication date: 1-Jun-2016
  • (2016)The research on improvement of narrowband radio channel communication protocol based on fountain codes2016 6th International Conference on Electronics Information and Emergency Communication (ICEIEC)10.1109/ICEIEC.2016.7589696(97-100)Online publication date: Jun-2016
  • (2016)Joint Best Price-CQI Product Scheduling and Congestion Control for LTECanadian Journal of Electrical and Computer Engineering10.1109/CJECE.2016.253876439:4(255-267)Online publication date: Nov-2017
  • (2015)Optimal Multicast Control for Simple Network CodingIEEE Transactions on Vehicular Technology10.1109/TVT.2014.234226164:6(2375-2386)Online publication date: Jun-2015
  • Show More Cited By

View Options

Get Access

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media