Extending Sensor Networks Lifetime Through Energy Efficient Organization

Nguyen, Nguyen; Huynh,

doi:10.1109/wasa.2007.7

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…This variant deals with the question of whether or not a given graph contains three disjoint dominating sets. Nguyen and Huynh [9] proved that the 3-disjoint dominating sets problem remains NP-complete even for the special cases of planar unit disk graphs. Moreover, they introduced and evaluated the performance of four greedy heuristics for the general MDDS problem.…”

Section: Graph Problems Used To Model Wsn Lifetime Maximizationmentioning

confidence: 99%

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A Population-Based Iterated Greedy Algorithm for Maximizing Sensor Network Lifetime

Bouamama

Blum

Pinacho-Davidson

2022

Sensors

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Finding dominating sets in graphs is very important in the context of numerous real-world applications, especially in the area of wireless sensor networks. This is because network lifetime in wireless sensor networks can be prolonged by assigning sensors to disjoint dominating node sets. The nodes of these sets are then used by a sleep–wake cycling mechanism in a sequential way; that is, at any moment in time, only the nodes from exactly one of these sets are switched on while the others are switched off. This paper presents a population-based iterated greedy algorithm for solving a weighted version of the maximum disjoint dominating sets problem for energy conservation purposes in wireless sensor networks. Our approach is compared to the ILP solver, CPLEX, which is an existing local search technique, and to our earlier greedy algorithm. This is performed through its application to 640 random graphs from the literature and to 300 newly generated random geometric graphs. The results show that our algorithm significantly outperforms the competitors.

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Section: Graph Problems Used To Model Wsn Lifetime Maximizationmentioning

confidence: 99%

“…Such a model (or similar models) have been used in a wide range of papers in the literature; for example, see refs. [9][10][11]. For the above-mentioned reasons, our technique organizes the sensor nodes into a number of disjoint dominating sets, which are used-one after the other-for data processing and data forwarding.…”

Section: Introductionmentioning

confidence: 99%

A Population-Based Iterated Greedy Algorithm for Maximizing Sensor Network Lifetime

Bouamama

Blum

Pinacho-Davidson

2022

Sensors

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“…In [10]- [12], the approach of dividing the nodes in non-cooperative wireless networks into disjoint sets and activating them sequentially, one set at a time to carry out network functions (e.g., monitoring, target tracking, etc.). In [10]- [11], the network is divided into sets with the objective of maximizing the coverage (in terms of sensing area or targets-tracking) of each set, and the centralized algorithms activate these sets, one at a time, using only the sensors from the current active set for monitoring all targets and for transmitting the collected data to a sink.…”

Section: Related Workmentioning

confidence: 99%

On the Performance of Alternating Concurrent Cooperative Transmissions in the High Path-Loss Attenuation Regime

Kailas

2012

NPA

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This paper addresses the issue of network broadcasting using alternating concurrent cooperative transmissions for sensor-based wireless networks that are very lossy. The medium access control (MAC)-free broadcast strategy is a simple, energy-efficient, low-overhead form of cooperative diversity-based strategy called the opportunistic large arrays (OLAs), and uses a received power-based threshold to define mutually exclusive sets of nodes during the initial broadcast, such that the union of the sets includes all the nodes in the network or cooperative route. This eliminates the formation of undesirable network coverage holes, a result of the "dead" nodes resulting from repeated usage. This broadcast strategy has been analyzed for wireless channels with γ= 2. The semi-analytical approach presented here investigates network life extensions for γ > 2 by considering two extreme continuum network topologies that correspond to the largest and smallest ratios of nodes (or network areas) used up during a successful broadcast, namely discs and strips, analyzing which will then set the bounds for arbitrary shaped static, cooperative routes or networks.

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“…Based on this later work, Moscibroda and Wattenhöfer [20] defined the MDDS problem as the maximum cluster-lifetime problem and introduced a randomized, distributed algorithm that has-with high probability-a performance ratio of O(log(n)). Nguyen and Huynh [21] demonstrated that the 3-disjoint dominating sets problem remains NP-complete even for planar unit disk graphs and studied the performance comparison of four greedy heuristics for the MDDS problem. In [22], a greedy heuristic of time complexity O(n 3 ) is described.…”

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confidence: 99%

A Greedy Heuristic for Maximizing the Lifetime of Wireless Sensor Networks Based on Disjoint Weighted Dominating Sets

2021

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Dominating sets are among the most well-studied concepts in graph theory, with many real-world applications especially in the area of wireless sensor networks. One way to increase network lifetime in wireless sensor networks consists of assigning sensors to disjoint dominating node sets, which are then sequentially used by a sleep–wake cycling mechanism. This paper presents a greedy heuristic for solving a weighted version of the maximum disjoint dominating sets problem for energy conservation purposes in wireless sensor networks. Moreover, an integer linear programming model is presented. Experimental results based on a large set of 640 problem instances show, first, that the integer linear programming model is only useful for small problem instances. Moreover, they show that our algorithm outperforms recent local search algorithms from the literature with respect to both solution quality and computation time.

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Extending Sensor Networks Lifetime Through Energy Efficient Organization

Cited by 5 publications

References 6 publications

A Population-Based Iterated Greedy Algorithm for Maximizing Sensor Network Lifetime

A Population-Based Iterated Greedy Algorithm for Maximizing Sensor Network Lifetime

On the Performance of Alternating Concurrent Cooperative Transmissions in the High Path-Loss Attenuation Regime

A Greedy Heuristic for Maximizing the Lifetime of Wireless Sensor Networks Based on Disjoint Weighted Dominating Sets

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