Price-based resource allocation in wireless ad hoc networks

Yuan Xue, Baochun Li, Klara Nahrstedt

Research output: Chapter in Book/Report/Conference proceedingChapter


The shared-medium multi-hop nature of wireless ad hoc networks poses fundamental challenges to the design of an effective resource allocation algorithm to maximize the aggregated utility of flows, while maintaining basic fairness among multiple flows. When previously proposed scheduling algorithms have been shown to perform well in providing fair shares of bandwidth among single-hop wireless flows, they did not consider multi-hop flows with an end-to-end perspective. Moreover, the resource allocation strategies employed in the wireline network can not be applied directly in the context of ad hoc networks due to the unique characteristic of location dependent contention and spatial reuse of the shared wireless channel. In this paper, we propose a price-based resource allocation model to achieve maximized aggregated utility (i.e., social welfare) of flows. Our original contributions are: First, we propose to use maximal clique-associated shadow prices for wireless channel access coordination, rather than link-associated price for wireline link access arbitration. Second, we present a new pricing policy for end-to-end multi-hop flow. Using this model, different fairness goals can be realized in ad hoc networks for end-to-end flows. With a two-tier distributed and iterative algorithm, scarce channel capacity is allocated fairly among multi-hop flows from an end-to-end perspective, using shadow prices as the mechanism to arbitrate channel access. Through extensive analysis and simulation results, we show that our proposed algorithm is able to fairly distribute resources among multi-hop flows, while simultaneously maximizing the aggregated utility of flows globally.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsKevin Jeffay, Ion Stoica, Klaus Wehrle
Number of pages18
ISBN (Print)3540402810, 9783540402817
StatePublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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