Skip to content

Advertisement

EURASIP Journal on Wireless Communications and Networking
EURASIP Journal on Wireless Communications and Networking Cover Image
  • Research Article
  • Open Access

On Traffic Load Distribution and Load Balancing in Dense Wireless Multihop Networks

EURASIP Journal on Wireless Communications and Networking20072007:016932

https://doi.org/10.1155/2007/16932

©  E. Hyytiä and J. Virtamo 2007

  • Received: 29 September 2006
  • Accepted: 13 March 2007
  • Published:

Abstract

We study the load balancing problem in a dense wireless multihop network, where a typical path consists of a large number of hops, that is, the spatial scales of a typical distance between source and destination and mean distance between the neighboring nodes are strongly separated. In this limit, we present a general framework for analyzing the traffic load resulting from a given set of paths and traffic demands. We formulate the load balancing problem as a minmax problem and give two lower bounds for the achievable minimal maximum traffic load. The framework is illustrated by considering the load balancing problem of uniformly distributed traffic demands in a unit disk. For this special case, we derive efficient expressions for computing the resulting traffic load for a given set of paths. By using these expressions, we are able to optimize a parameterized set of paths yielding a particularly flat traffic load distribution which decreases the maximum traffic load in the network by in comparison with the shortest-path routing.

Keywords

  • Information System
  • Lower Bound
  • Spatial Scale
  • General Framework
  • Unit Disk

[1234567891011121314151617]

Authors’ Affiliations

(1)
The Telecommunications Research Center Vienna (ftw.), Donau-City Strasse 1, Vienna, 1220, Austria
(2)
Networking Laboratory, Helsinki University of Technology, P.O. Box 3000, 02015 TKK, Finland

References

  1. Jacquet P: Geometry of information propagation in massively dense ad hoc networks. Proceedings of the 5th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc '04), May 2004, Roppongi Hills, Tokyo, Japan 157-162.View ArticleGoogle Scholar
  2. Toumpis S, Tassiulas L: Optimal deployment of large wireless sensor networks. IEEE Transactions on Information Theory 2006,52(7):2935-2953.MathSciNetView ArticleMATHGoogle Scholar
  3. Toumpis S: Optimal design and operation of massively dense wireless networks. Proceedings of Workshop on Interdisciplinary Systems Approach in Performance Evaluation and Design of Computer & Communication Systems (INTER-PERF '06), October 2006, Pisa, ItalyGoogle Scholar
  4. Hyytiä E, Virtamo J: On load balancing in a dense wireless multihop network. Proceedings of the 2nd Conference on Next Generation Internet Design and Engineering (NGI '06), April 2006, València, Spain 72-79.Google Scholar
  5. Sirkeci-Mergen B, Scaglione A: A continuum approach to dense wireless networks with cooperation. Proceedings of the 24th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '05), March 2005, Miami, Fla, USA 4: 2755-2763.View ArticleGoogle Scholar
  6. Pham PP, Perreau S: Performance analysis of reactive shortest path and multi-path routing mechanism with load balance. Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '03), March-April 2003, San Francisco, Calif, USA 1: 251-259.Google Scholar
  7. Ganjali Y, Keshavarzian A: Load balancing in ad hoc networks: single-path routing vs. multi-path routing. Proceedings of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '04), March 2004, Hong Kong 2: 1120-1125.Google Scholar
  8. Dousse O, Baccelli F, Thiran P: Impact of interferences on connectivity in ad hoc networks. IEEE/ACM Transactions on Networking 2005,13(2):425-436.View ArticleGoogle Scholar
  9. Gupta P, Kumar PR: The capacity of wireless networks. IEEE Transactions on Information Theory 2000,46(2):388-404. 10.1109/18.825799MathSciNetView ArticleMATHGoogle Scholar
  10. Kalantari M, Shayman M: Routing in wireless ad hoc networks by analogy to electrostatic theory. Proceedings of IEEE International Conference on Communications (ICC '04), June 2004, Paris, France 7: 4028-4033.Google Scholar
  11. Johnson DB, Maltz DA: Dynamic source routing in ad hoc wireless networks. In Mobile Computing. Volume 353. Kluwer Academic, Dordrecht, The Netherlands; 1996:153-181. chapter 10.1007/978-0-585-29603-6_5View ArticleGoogle Scholar
  12. Bettstetter C, Wagner C: The spatial node distribution of the random waypoint mobility model. Proceedings of German Workshop on Mobile Ad Hoc Networks (WMAN '02), March 2002, Ulm, Germany 41-58.Google Scholar
  13. Bettstetter C, Resta G, Santi P: The node distribution of the random waypoint mobility model for wireless ad hoc networks. IEEE Transactions on Mobile Computing 2003,2(3):257-269. 10.1109/TMC.2003.1233531View ArticleGoogle Scholar
  14. Navidi W, Camp T: Stationary distributions for the random waypoint mobility model. IEEE Transactions on Mobile Computing 2004,3(1):99-108. 10.1109/TMC.2004.1261820View ArticleGoogle Scholar
  15. Hyytiä E, Virtamo J: Random waypoint mobility model in cellular networks. Wireless Networks 2007,13(2):177-188. 10.1007/s11276-006-4600-3View ArticleGoogle Scholar
  16. Bell GI, Glasstone S: Nuclear Reactor Theory. Van Nostrand Reinhold, New York, NY, USA; 1970.Google Scholar
  17. Hyytiä E, Lassila P, Virtamo J: Spatial node distribution of the random waypoint mobility model with applications. IEEE Transactions on Mobile Computing 2006,5(6):680-694.View ArticleGoogle Scholar

Copyright

© E. Hyytiä and J. Virtamo 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement