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Power Efficient Range Assignment for Symmetric Connectivity in Static Ad Hoc Wireless Networks

Identifieur interne : 006212 ( Main/Exploration ); précédent : 006211; suivant : 006213

Power Efficient Range Assignment for Symmetric Connectivity in Static Ad Hoc Wireless Networks

Auteurs : E. Althaus [Allemagne] ; G. C Linescu [États-Unis] ; I. I. M Ndoiu [États-Unis] ; S. Prasad [États-Unis] ; N. Tchervenski [États-Unis] ; A. Zelikovsky [États-Unis]

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RBID : ISTEX:9A6A42775281B93B7C08ED2FF9EEADA6AA233A4E

English descriptors

Abstract

Abstract: In this paper we study the problem of assigning transmission ranges to the nodes of a static ad hoc wireless network so as to minimize the total power consumed under the constraint that enough power is provided to the nodes to ensure that the network is connected. We focus on the Min-Power Symmetric Connectivity problem, in which the bidirectional links established by the transmission ranges are required to form a connected graph. Implicit in previous work on transmission range assignment under asymmetric connectivity requirements is the proof that Min-Power Symmetric Connectivity is NP-hard and that the MST algorithm has a performance ratio of 2. In this paper we make the following contributions: (1) we show that the related Min-Power Symmetric Unicast problem can be solved efficiently by a shortest-path computation in an appropriately constructed auxiliary graph; (2) we give an exact branch and cut algorithm based on a new integer linear program formulation solving instances with up to 35–40 nodes in 1 hour; (3) we establish the similarity between Min-Power Symmetric Connectivity and the classic Steiner Tree problem in graphs, and use this similarity to give a polynomial-time approximation scheme with performance ratio approaching 5/3 as well as a more practical approximation algorithm with approximation factor 11/6; and (4) we give the results of a comprehensive experimental study comparing new and previously proposed heuristics with the above exact and approximation algorithms.

Url:
DOI: 10.1007/s11276-005-5275-x


Affiliations:


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