A hybrid genetic algorithm for the minimum energy broadcast problem in wireless ad hoc networks

Singh, Alok; Bhukya, Wilson Naik

doi:10.1016/j.asoc.2009.12.027

Cited by 29 publications

(30 citation statements)

References 8 publications

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“…This genetic algorithm used the rank selection scheme, different crossover operators (partially matched crossover, order crossover and position-based crossover) and different mutation operators (swap mutation, shift mutation and insert mutation). Singh et al [22] proposed a hybrid genetic approach to the minimum-energy broadcast problem. They adopted the different crossover operators and mutation operators with the ones used in [21].…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Algorithm for Broadcasting in Ad Hoc Wireless Sensor Networks

Xiong

Huang

Cheng

et al. 2013

Sensors

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Broadcasting is a common and basic operation used to support various network protocols in wireless networks. To achieve energy-efficient broadcasting is especially important for ad hoc wireless sensor networks because sensors are generally powered by batteries with limited lifetimes. Energy consumption for broadcast operations can be reduced by minimizing the number of relay nodes based on the observation that data transmission processes consume more energy than data reception processes in the sensor nodes, and how to improve the network lifetime is always an interesting issue in sensor network research. The minimum-energy broadcast problem is then equivalent to the problem of finding the minimum Connected Dominating Set (CDS) for a connected graph that is proved NP-complete. In this paper, we introduce an Efficient Minimum CDS algorithm (EMCDS) with help of a proposed ordered sequence list. EMCDS does not concern itself with node energy and broadcast operations might fail if relay nodes are out of energy. Next we have proposed a Minimum Energy-consumption Broadcast Scheme (MEBS) with a modified version of EMCDS, and aimed at providing an efficient scheduling scheme with maximized network lifetime. The simulation results show that the proposed EMCDS algorithm can find smaller CDS compared with related works, and the MEBS can help to increase the network lifetime by efficiently balancing energy among nodes in the networks.

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Section: Related Workmentioning

confidence: 99%

Energy-Efficient Algorithm for Broadcasting in Ad Hoc Wireless Sensor Networks

Xiong

Huang

Cheng

et al. 2013

Sensors

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“…Genetic Algorithm (GA) [11], Evolutionary Local Search (ELS) [21], Iterated Local Search (ILS) [22], Hybrid Genetic Algorithm (HGA) [23], and Ant Colony Optimization (ACO) [24,25].…”

Section: Meta-heuristic Algorithmsmentioning

confidence: 99%

“…HGA [23] used the permutation encoding proposed by Xiang et al [11]. It is a steady-state GA and again takes rshrink as the local search procedure.…”

Section: Meta-heuristic Algorithmsmentioning

confidence: 99%

Particle swarm optimization for the minimum energy broadcast problem in wireless ad-hoc networks

Hsiao

Chiang

2012

2012 IEEE Congress on Evolutionary Computation

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In this paper, we propose a novel approach based on particle swarm optimization (PSO) for solving the minimum energy broadcast (MEB) problem, which has been proven to be NP-complete. Wireless sensor networks (WSNs) have attracted large intention in recent years due to its powerful ability. One crucial issue in WSN is energy saving because of the limited battery resource. The MEB problem is one of the important scenarios in WSN, where a node needs to broadcast packets to all other nodes in the network. The objective is to minimize power consumption of all nodes in the network. Here we take advantage of fast and guided convergence characteristics of PSO to solve the MEB problem. For applying PSO to the MEB problem, we use the power degree to define the particle position. We go a step further to analyze one well-known local search mechanism: rshrink and propose an improved version. The experimental results show that the proposed approach is able to compete and even outperform state-of-the-art works.

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“…Recently, evolutionary algorithms like genetic algorithms have been used to optimize the design of broadcasting algorithms. In [31], the authors solve the wellknown minimum energy broadcast NP-hard problem using a hybrid evolutionary algorithm. The idea determines the set of forwarder nodes in a MANET that guarantees maximum dissemination with the minimum energy consumption.…”

Section: Broadcasting Algorithmsmentioning

confidence: 99%

A Survey on the Application of Evolutionary Algorithms for Mobile Multihop Ad Hoc Network Optimization Problems

Reina

Ruiz

Ciobanu

et al. 2016

International Journal of Distributed Sensor Networks

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Evolutionary algorithms are metaheuristic algorithms that provide quasioptimal solutions in a reasonable time. They have been applied to many optimization problems in a high number of scientific areas. In this survey paper, we focus on the application of evolutionary algorithms to solve optimization problems related to a type of complex network like mobile multihop ad hoc networks. Since its origin, mobile multihop ad hoc network has evolved causing new types of multihop networks to appear such as vehicular ad hoc networks and delay tolerant networks, leading to the solution of new issues and optimization problems. In this survey, we review the main work presented for each type of mobile multihop ad hoc network and we also present some innovative ideas and open challenges to guide further research in this topic.

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A hybrid genetic algorithm for the minimum energy broadcast problem in wireless ad hoc networks

Cited by 29 publications

References 8 publications

Energy-Efficient Algorithm for Broadcasting in Ad Hoc Wireless Sensor Networks

Energy-Efficient Algorithm for Broadcasting in Ad Hoc Wireless Sensor Networks

Particle swarm optimization for the minimum energy broadcast problem in wireless ad-hoc networks

A Survey on the Application of Evolutionary Algorithms for Mobile Multihop Ad Hoc Network Optimization Problems

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