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

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

A fuzzy-based reliaility for JXTA-overlay P2P platform considering data download speed, peer congestion situation, number of interaction and packet loss parameters

(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.In this paper, we propose and evaluate a new fuzzy-based reliability system for Peer-to-Peer (P2P) communications in JXTA-Overlay platform considering as a new parameter the peer congestion situation. In our system, we considered four input parameters: Data Download Speed (DDS), Peer Congestion Situation (PCS), Number of Interactions (NI) and Packet Loss (PL) to decide the Peer Reliability (PR). We evaluate the proposed system by computer simulations. The simulation results have shown that the proposed system has a good performance and can choose reliable peers to connect in JXTA-Overlay platform.Peer ReviewedPostprint (author's final draft

Effects of population size for location-aware node placement in WMNs: evaluation by a genetic algorithm--based approach

Wireless mesh networks (WMNs) are cost-efficient networks that have the potential to serve as an infrastructure for advanced location-based services. Location service is a desired feature for WMNs to support location-oriented applications. WMNs are also interesting infrastructures for supporting ubiquitous multimedia Internet access for mobile or fixed mesh clients. In order to efficiently support such services and offering QoS, the optimized placement of mesh router nodes is very important. Indeed, such optimized mesh placement can support location service managed in the mesh and keep the rate of location updates low...Peer ReviewedPostprint (author's final draft

Performance analysis of WMNs by WMN-GA simulation system for exponential distribution considering EDCA and DCF

(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.In this paper, we evaluate the performance of WMN using our WMN-GA simulation system considering throughput, delay, jitter and fairness index metrics. For simulations, we used ns-3 and Optimized Link State Routing (OLSR). We compare the performance of Distributed Coordination Function (DCF) and Enhanced Distributed Channel Access (EDCA) for exponential distribution of mesh clients by sending multiple Constant Bit Rate (CBR) flows in the network. The simulation results show that for Hybrid WMN, the throughput of both MAC protocols is higher than I/B WMN. The delay and jitter of Hybrid WMN are lower than I/B WMN. The fairness index of I/B WMN is a little bit higher than Hybrid WMN.Peer ReviewedPostprint (author's final draft

A GA-based simulation system for WMNs: comparison analysis for different number of flows, client distributions, DCF and EDCA functions

In this paper, we compare the performance of Distributed Coordination Function (DCF) and Enhanced Distributed Channel Access (EDCA) for normal and uniform distributions of mesh clients considering two Wireless Mesh Network (WMN) architectures. As evaluation metrics, we consider throughput, delay, jitter and fairness index metrics. For simulations, we used WMN-GA simulation system, ns-3 and Optimized Link State Routing. The simulation results show that for normal distribution, the throughput of I/B WMN is higher than Hybrid WMN architecture. For uniform distribution, in case of I/B WMN, the throughput of EDCA is a little bit higher than Hybrid WMN. However, for Hybrid WMN, the throughput of DCF is higher than EDCA. For normal distribution, the delay and jitter of Hybrid WMN are lower compared with I/B WMN. For uniform distribution, the delay and jitter of both architectures are almost the same. However, in the case of DCF for 20 flows, the delay and jitter of I/B WMN are lower compared with Hybrid WMN. For I/B architecture, in case of normal distribution the fairness index of DCF is higher than EDCA. However, for Hybrid WMN, the fairness index of EDCA is higher than DCF. For uniform distribution, the fairness index of few flows is higher than others for both WMN architectures.Peer ReviewedPostprint (author's final draft

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

(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

Investigation of fitness function weight-coefficients for optimization in WMN-PSO simulation system

(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 Particle Swam Optimization for solving node placement problem in wireless mesh networks, called WMN-PSO. In this paper, we use Size of Giant Component (SGC) and Number of Covered Mesh Clients (NCMC) as metrics for optimization. Then, we analyze effects of weight-coefficients for SGC and NCMC. From the simulation results, we found that the best values of the weight-coefficients for SGC and NCMC are 0.7 and 0.3, respectively.Peer ReviewedPostprint (author's final draft

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

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

A GA-based simulation system for WMNs: performance analysis for different WMN architectures considering transmission rate and OLRS protocol

(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.In this paper, we evaluate the performance of two WMN architectures considering throughput, delay, jitter and fairness index metrics. For simulations, we used ns-3. We compare the performance for two architectures considering transmission rate and OLSR protocol. The simulation results show that for transmission rate 600 and 1200 [kbps], the throughput of Hybrid WMN is higher than I/B WMN. For transmission rate 600 and 1200 [kbps], the delay and jitter of Hybrid WMN is lower than I/B WMN. For transmission rate 600 and 1200 [kbps], the fairness index of I/B WMN is higher than Hybrid WMN.Peer ReviewedPostprint (author's final draft