Using an evolutionary algorithm to optimize the broadcasting methods in mobile ad hoc networks

Abdou, Wahabou; Henriet, Adrien; Bloch, Christelle; Dhoutaut, Dominique; Charlet, Damien; Spies, François

doi:10.1016/j.jnca.2011.01.004

Cited by 39 publications

(20 citation statements)

References 7 publications

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“…In addition, GAME uses a parallel evaluation procedure based on a master-slave model. Although this model allowed the reduction in terms of the duration of the experimentations in previous work in the field of mobile networks [1]. Nevertheless, designing an asynchronous version of GAME would be very interesting.…”

Section: Resultsmentioning

confidence: 99%

“…The parallelization allows GAME to tackle problems with complex objective functions or with objective functions requiring simulation to assess their values. A variant of GAME, named ESBEA, has been applied, for instance, to a constrained optimization problem containing four objective functions evaluated by simulation, in the field of ad hoc mobile communication networks [1].…”

Section: Selection Operatormentioning

confidence: 99%

See 1 more Smart Citation

Multi-Pareto-Ranking Evolutionary Algorithm

Bloch¹,

Charlet²,

Spies³

2012

Evolutionary Computation in Combinatorial Optimization

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Abstract. This paper proposes a new multi-objective genetic algorithm, called GAME, to solve constrained optimization problems. GAME uses an elitist archive, but it ranks the population in several Pareto fronts. Then, three types of fitness assignment methods are defined: the fitness of individuals depends on the front they belong to. The crowding distance is also used to preserve diversity. Selection is based on two steps: a Pareto front is first selected, before choosing an individual among the solutions it contains. The probability to choose a given front is computed using three parameters which are tuned using the design of experiments. The influence of the number of Pareto fronts is studied experimentally. Finally GAME's performance is assessed and compared with three other algorithms according to the conditions of the CEC 2009 competition.

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Section: Resultsmentioning

confidence: 99%

Section: Selection Operatormentioning

confidence: 99%

Multi-Pareto-Ranking Evolutionary Algorithm

Bloch¹,

Charlet²,

Spies³

2012

Evolutionary Computation in Combinatorial Optimization

Self Cite

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“…The following schemes use artificial intelligence to adjust the forwarding probability of nodes. In [2] a genetic algorithm is used to calculate the forwarding probability. Other parameters such as number of repeats that a given node retransmits an incoming packet, delay between repeats, and Time To Live (TTL) for a packet, are taken into consideration to evaluate the fitness function.…”

Section: P Busy ð40þmentioning

confidence: 99%

A survey on probabilistic broadcast schemes for wireless ad hoc networks

et al. 2015

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a b s t r a c tBroadcast or flooding is a dissemination technique of paramount importance in wireless ad hoc networks. The broadcast scheme is widely used within routing protocols by a wide range of wireless ad hoc networks such as mobile ad hoc networks, vehicular ad hoc networks, and wireless sensor networks, and used to spread emergency messages in critical scenarios after a disaster scenario and/or an accidents. As the type broadcast scheme used plays an important role in the performance of the network, it has to be selected carefully. Though several types of broadcast schemes have been proposed, probabilistic broadcast schemes have been demonstrated to be suitable schemes for wireless ad hoc networks due to a range of benefits offered by them such as low overhead, balanced energy consumption, and robustness against failures and mobility of nodes. In the last decade, many probabilistic broadcast schemes have been proposed by researchers. In addition to reviewing the main features of the probabilistic schemes found in the literature, we also present a classification of the probabilistic schemes, an exhaustive review of the evaluation methodology including their performance metrics, types of network simulators, their comparisons, and present some examples of real implementations, in this paper.

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“…For example, Bikakis et al [6] present motivating scenarios for designing a context exchange and retrieval system for ambient intelligence environments. Bakhouya et al and Abdou et al discuss how context dissemination can benefit the communication in Vehicular Ad Hoc Networks [7,8]. Similarly, Abdou et al proposes a novel communication strategy.…”

Section: Context Retrieval and Disseminationmentioning

confidence: 99%

Automated context dissemination for autonomic collaborative networks through semantic subscription filter generation

Latré

Famaey

Strassner

et al. 2013

Journal of Network and Computer Applications

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The current manual management of services and applications in today's telecommunication networks is becoming increasingly complicated. In the Future Internet, management is assumed to be automated by introducing an autonomic layer of distributed management elements. These distributed management elements need to collaborate with each other to ensure end-to-end quality guarantees. In this article, we focus on the context dissemination between such collaborative management elements. Context dissemination is the exchange of all relevant management data and knowledge between the elements. Collaborating elements typically generate large amounts of context and it is important to filter this continuous stream. We propose a context dissemination approach that automates the context exchange between elements. The approach enables the automated generation of semantic subscription filters. Subscription filters allow an element to define where, how, and when context needs to be requested from other entities. Moreover, the proposed approach allows making the subscription filter generation dependent on the context. We present algorithms that intelligently filter the knowledge that is stored in the ontology. The results show that the generation of subscription filters can be done in the order of tens of milliseconds.

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Using an evolutionary algorithm to optimize the broadcasting methods in mobile ad hoc networks

Cited by 39 publications

References 7 publications

Multi-Pareto-Ranking Evolutionary Algorithm

Multi-Pareto-Ranking Evolutionary Algorithm

A survey on probabilistic broadcast schemes for wireless ad hoc networks

Automated context dissemination for autonomic collaborative networks through semantic subscription filter generation

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