1,469 research outputs found

    Implementation and evaluation of a simulation system based on particle swarm optimisation for node placement problem in wireless mesh networks

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    With the fast development of wireless technologies, wireless mesh networks (WMNs) are becoming an important networking infrastructure due to their low cost and increased high speed wireless internet connectivity. This paper implements a simulation system based on particle swarm optimisation (PSO) in order to solve the problem of mesh router placement in WMNs. Four replacement methods of mesh routers are considered: constriction method (CM), random inertia weight method (RIWM), linearly decreasing Vmax method (LDVM) and linearly decreasing inertia weight method (LDIWM). Simulation results are provided, showing that the CM converges very fast, but has the worst performance among the methods. The considered performance metrics are the size of giant component (SGC) and the number of covered mesh clients (NCMC). The RIWM converges fast and the performance is good. The LDIWM is a combination of RIWM and LDVM. The LDVM converges after 170 number of phases but has a good performance.Peer ReviewedPostprint (author's final draft

    Node placement in Wireless Mesh Networks: a comparison study of WMN-SA and WMN-PSO simulation systems

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    (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.With the fast development of wireless technologies, Wireless Mesh Networks (WMNs) are becoming an important networking infrastructure due to their low cost and increased high speed wireless Internet connectivity. In our previous work, we implemented a simulation system based on Simulated Annealing (SA) for solving node placement problem in wireless mesh networks, called WMN-SA. Also, we implemented a Particle Swarm Optimization (PSO) based simulation system, called WMN-PSO. In this paper, we compare two systems considering calculation time. From the simulation results, when the area size is 32 × 32 and 64 × 64, WMN-SA is better than WMN-PSO. When the area size is 128 × 128, WMN-SA performs better than WMN-PSO. However, WMN-SA needs more calculation time than WMN-PSO.Peer ReviewedPostprint (author's final draft

    Performance evaluation of WMN-GA for different mutation and crossover rates considering number of covered users parameter

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    Node placement problems have been long investigated in the optimization field due to numerous applications in location science and classification. Facility location problems are showing their usefulness to communication networks, and more especially from Wireless Mesh Networks (WMNs) field. Recently, such problems are showing their usefulness to communication networks, where facilities could be servers or routers offering connectivity services to clients. In this paper, we deal with the effect of mutation and crossover operators in GA for node placement problem. We evaluate the performance of the proposed system using different selection operators and different distributions of router nodes considering number of covered users parameter. The simulation results show that for Linear and Exponential ranking methods, the system has a good performance for all rates of crossover and mutation.Peer ReviewedPostprint (published version

    Conception des réseaux maillés sans fil à multiples-radios multiples-canaux

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    GĂ©nĂ©ralement, les problĂšmes de conception de rĂ©seaux consistent Ă  sĂ©lectionner les arcs et les sommets d’un graphe G de sorte que la fonction coĂ»t est optimisĂ©e et l’ensemble de contraintes impliquant les liens et les sommets dans G sont respectĂ©es. Une modification dans le critĂšre d’optimisation et/ou dans l’ensemble de contraintes mĂšne Ă  une nouvelle reprĂ©sentation d’un problĂšme diffĂ©rent. Dans cette thĂšse, nous nous intĂ©ressons au problĂšme de conception d’infrastructure de rĂ©seaux maillĂ©s sans fil (WMN- Wireless Mesh Network en Anglais) oĂč nous montrons que la conception de tels rĂ©seaux se transforme d’un problĂšme d’optimisation standard (la fonction coĂ»t est optimisĂ©e) Ă  un problĂšme d’optimisation Ă  plusieurs objectifs, pour tenir en compte de nombreux aspects, souvent contradictoires, mais nĂ©anmoins incontournables dans la rĂ©alitĂ©. Cette thĂšse, composĂ©e de trois volets, propose de nouveaux modĂšles et algorithmes pour la conception de WMNs oĂč rien n’est connu Ă  l’ avance. Le premiervolet est consacrĂ© Ă  l’optimisation simultanĂ©e de deux objectifs Ă©quitablement importants : le coĂ»t et la performance du rĂ©seau en termes de dĂ©bit. Trois modĂšles bi-objectifs qui se diffĂ©rent principalement par l’approche utilisĂ©e pour maximiser la performance du rĂ©seau sont proposĂ©s, rĂ©solus et comparĂ©s. Le deuxiĂšme volet traite le problĂšme de placement de passerelles vu son impact sur la performance et l’extensibilitĂ© du rĂ©seau. La notion de contraintes de sauts (hop constraints) est introduite dans la conception du rĂ©seau pour limiter le dĂ©lai de transmission. Un nouvel algorithme basĂ© sur une approche de groupage est proposĂ© afin de trouver les positions stratĂ©giques des passerelles qui favorisent l’extensibilitĂ© du rĂ©seau et augmentent sa performance sans augmenter considĂ©rablement le coĂ»t total de son installation. Le dernier volet adresse le problĂšme de fiabilitĂ© du rĂ©seau dans la prĂ©sence de pannes simples. PrĂ©voir l’installation des composants redondants lors de la phase de conception peut garantir des communications fiables, mais au dĂ©triment du coĂ»t et de la performance du rĂ©seau. Un nouvel algorithme, basĂ© sur l’approche thĂ©orique de dĂ©composition en oreilles afin d’installer le minimum nombre de routeurs additionnels pour tolĂ©rer les pannes simples, est dĂ©veloppĂ©. Afin de rĂ©soudre les modĂšles proposĂ©s pour des rĂ©seaux de taille rĂ©elle, un algorithme Ă©volutionnaire (mĂ©ta-heuristique), inspirĂ© de la nature, est dĂ©veloppĂ©. Finalement, les mĂ©thodes et modĂšles proposĂ©s on Ă©tĂ© Ă©valuĂ©s par des simulations empiriques et d’évĂ©nements discrets.Generally, network design problems consist of selecting links and vertices of a graph G so that a cost function is optimized and all constraints involving links and the vertices in G are met. A change in the criterion of optimization and/or the set of constraints leads to a new representation of a different problem. In this thesis, we consider the problem of designing infrastructure Wireless Mesh Networks (WMNs) where we show that the design of such networks becomes an optimization problem with multiple objectives instead of a standard optimization problem (a cost function is optimized) to take into account many aspects, often contradictory, but nevertheless essential in the reality. This thesis, composed of three parts, introduces new models and algorithms for designing WMNs from scratch. The first part is devoted to the simultaneous optimization of two equally important objectives: cost and network performance in terms of throughput. Three bi-objective models which differ mainly by the approach used to maximize network performance are proposed, solved and compared. The second part deals with the problem of gateways placement, given its impact on network performance and scalability. The concept of hop constraints is introduced into the network design to reduce the transmission delay. A novel algorithm based on a clustering approach is also proposed to find the strategic positions of gateways that support network scalability and increase its performance without significantly increasing the cost of installation. The final section addresses the problem of reliability in the presence of single failures. Allowing the installation of redundant components in the design phase can ensure reliable communications, but at the expense of cost and network performance. A new algorithm is developed based on the theoretical approach of "ear decomposition" to install the minimum number of additional routers to tolerate single failures. In order to solve the proposed models for real-size networks, an evolutionary algorithm (meta-heuristics), inspired from nature, is developed. Finally, the proposed models and methods have been evaluated through empirical and discrete events based simulations
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