Multiple communication im multihop radio networks
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STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Greedy strikes back: improved facility location algorithms
Journal of Algorithms
Analysis of a local search heuristic for facility location problems
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Power consumption in packet radio networks
Theoretical Computer Science
Proceedings of the 2003 ACM symposium on Applied computing
On the power assignment problem in radio networks
Mobile Networks and Applications - Discrete algorithms and methods for mobile computing and communications
Approximating k-hop minimum-spanning trees
Operations Research Letters
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On the bounded-hop MST problem on random Euclidean instances
Theoretical Computer Science
Analysis of the bounded-hops converge-cast distributed protocol in ad-hoc networks
ALGOSENSORS'07 Proceedings of the 3rd international conference on Algorithmic aspects of wireless sensor networks
A distributed protocol for the bounded-hops converge-cast in ad-hoc networks
ADHOC-NOW'06 Proceedings of the 5th international conference on Ad-Hoc, Mobile, and Wireless Networks
Weighted broadcast in linear radio networks
AAIM'06 Proceedings of the Second international conference on Algorithmic Aspects in Information and Management
Divide and conquer is almost optimal for the bounded-hop MST problem on random euclidean instances
SIROCCO'05 Proceedings of the 12th international conference on Structural Information and Communication Complexity
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The paper studies the problem of computing a minimal energy-cost range assignment in an ad-hoc wireless network which allows a set S of stations located in the 2-dimensional Euclidean space to perform accumulation (all-to-one) operations towards some root station b in at most h hops (2-Dim Min h-Accumulation Range Assignment problem). We experimentally investigate the behavior of fast and easy-to-implement heuristics for the 2-Dim Min h-Accumulation Range Assignment problem on instances obtained by choosing at random n points in a square of side length L. We compare the performance of an easy-to-implement, very fast heuristic with those of three simple heuristics based on classical greedy algorithms (Prim's and Kruskal's ones) defined for the Minimum Spanning Tree problem. The comparison is carried out over thousands of random instances in several different situations depending on: the distribution of the stations in the plane, their density, the energy cost function.