Maximizing Network Lifetime of Broadcasting Over Wireless Stationary Ad Hoc Networks

Kang, Intae; Poovendran, Radha

doi:10.1007/s11036-005-4445-5

Cited by 57 publications

(66 citation statements)

References 38 publications

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“…In [6], Mavinkurve et al introduced the reachability graph associated with T , which contains the arc (u, w) if and only if the power assignment to u is sufficient for u to reach w. The reachability graph is equivalent to the term topology in [3].…”

Section: Reachability Graphsmentioning

confidence: 99%

A fast local search method for minimum energy broadcast in wireless ad hoc networks

Bauer

Haugland

Yuan

2009

Operations Research Letters

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Section: Reachability Graphsmentioning

confidence: 99%

A fast local search method for minimum energy broadcast in wireless ad hoc networks

Bauer

Haugland

Yuan

2009

Operations Research Letters

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“…Kang and Poovendran [4] discuss several problems related to dynamic lifetime maximisation, such as non-uniform energy levels. They also emphasise the importance of considering the minmax energy metric rather than the more often addressed minimum total energy metric for maximising network lifetime.…”

Section: Introductionmentioning

confidence: 99%

“…For a discussion of the two different objectives, minimising total transmission power and minimising maximum transmission power, see e.g. [2,4].…”

Section: Introductionmentioning

confidence: 99%

Distributed Computation of Maximum Lifetime Spanning Subgraphs in Sensor Networks

Haanpää¹,

Schumacher²,

Thaler³

et al. 2007

Mobile Ad-Hoc and Sensor Networks

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Abstract. We present a simple and efficient distributed method for determining the transmission power assignment that maximises the lifetime of a data-gathering wireless sensor network with stationary nodes and static power assignments. Our algorithm determines the transmission power level inducing the maximum-lifetime spanning subgraph of a network by means of a distributed breadth-first search for minmax-power communication paths, i.e. paths that connect a given reference node to each of the other nodes so that the maximum transmission power required on any link of the path is minimised. The performance of the resulting Maximum Lifetime Spanner (MLS) protocol is validated in a number of simulated networking scenarios. In particular, we study the performance of the protocol in terms of the number of required control messages, and compare it to the performance of a recently proposed Distributed Min-Max Tree (DMMT) algorithm. For all network scenarios we consider, MLS outperforms DMMT significantly. We also discuss bringing down the message complexity of our algorithm by initialising it with the Relative Neighbourhood Graph (RNG) of a transmission graph rather than the full graph, and present an efficient distributed method for reducing a given transmission graph to its RNG.

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“…Kang and Poovendran [9] discuss several problems related to dynamic lifetime maximization, such as the issue of non-uniform energy levels. They also emphasize the importance of considering the minmax energy metric rather than the more often addressed minimum total energy metric for the purpose of maximizing network lifetime.…”

Section: Related Workmentioning

confidence: 99%

“…For a discussion of the two different objectives, minimizing total transmission power and minimizing maximum transmission power, see e.g. [4,9].…”

Section: Related Workmentioning

confidence: 99%

Lifetime Maximization in Wireless Sensor Networks by Distributed Binary Search

Schumacher¹,

Orponen²,

Thaler³

et al.

Lecture Notes in Computer Science

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Abstract. We consider the problem of determining the transmission power assignment that maximizes the lifetime of a data-gathering wireless sensor network with stationary nodes and static transmission power levels. We present a simple and efficient distributed algorithm for this task that works by establishing the minimum power level at which the network stays connected. The algorithm is based on a binary search over the range of feasible transmission power levels and does not require prior knowledge of network topology. We study the performance of the resulting BSpan protocol by network simulations and compare the number of control messages required by BSpan to two other recently proposed methods, the Distributed Min-Max Tree (DMMT) and Maximum Lifetime Spanner (MLS) algorithms. We find that BSpan outperforms both DMMT and MLS significantly.

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Maximizing Network Lifetime of Broadcasting Over Wireless Stationary Ad Hoc Networks

Cited by 57 publications

References 38 publications

A fast local search method for minimum energy broadcast in wireless ad hoc networks

A fast local search method for minimum energy broadcast in wireless ad hoc networks

Distributed Computation of Maximum Lifetime Spanning Subgraphs in Sensor Networks

Lifetime Maximization in Wireless Sensor Networks by Distributed Binary Search

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