A Comparison Study of Constriction and Linearly Decreasing Vmax Replacement Methods for Wireless Mesh Networks by WMN-PSOHC-DGA Simulation System

The Wireless Mesh Networks (WMNs) are becoming an important networking infrastructure because they have many advantages such as low cost and increased high speed wireless Internet connectivity. In our previous work, we implemented a Particle Swarm Optimization (PSO) and Hill Climbing (HC) based hybrid simulation system, called WMN-PSOHC, and a simulation system based on Genetic Algorithm (GA), called WMN-GA, for solving node placement problem in WMNs. Then, we implemented a hybrid simulation system based on PSOHC and distributed GA (DGA), called WMN-PSOHC-DGA. In this paper, we analyze the performance of WMNs using WMN-PSOHC-DGA simulation system considering Constriction Method (CM) and Linearly Decreasing Vmax Method (LDVM). Simulation results show that a good performance is achieved for CM compared with the case of LDVM.

[1]  Leonard Barolli,et al.  Performance Evaluation of WMNs by WMN-PSOHC System Considering Random Inertia Weight and Linearly Decreasing Inertia Weight Replacement Methods , 2019, IMIS.

[2]  Fatos Xhafa,et al.  Implementation and evaluation of a simulation system based on particle swarm optimisation for node placement problem in wireless mesh networks , 2016, Int. J. Commun. Networks Distributed Syst..

[3]  C. Siva Ram Murthy,et al.  Node Placement Algorithm for Deployment of Two-Tier Wireless Mesh Networks , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[4]  Leonard Barolli,et al.  Implementation of an intelligent hybrid simulation systems for WMNs based on particle swarm optimization and simulated annealing: performance evaluation for different replacement methods , 2019, Soft Comput..

[5]  Leonard Barolli,et al.  Design and Implementation of a Hybrid Intelligent System Based on Particle Swarm Optimization, Hill Climbing and Distributed Genetic Algorithm for Node Placement Problem in WMNs: A Comparison Study , 2018, 2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA).

[6]  Leonard Barolli,et al.  Performance Evaluation of WMN-PSOHC and WMN-PSO Simulation Systems for Node Placement in Wireless Mesh Networks: A Comparison Study , 2017, EIDWT.

[7]  Leonard Barolli,et al.  Performance Analysis of WMNs by WMN-PSOHC-DGA Simulation System Considering Random Inertia Weight and Linearly Decreasing Vmax Router Replacement Methods , 2019, CISIS.

[8]  Dharma P. Agrawal,et al.  Efficient Mesh Router Placement in Wireless Mesh Networks , 2007, 2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems.

[9]  Leonard Barolli,et al.  Performance Evaluation of WMNs by WMN-PSOSA System Considering Chi-square and Exponential Client Distributions , 2019, AINA.

[10]  Leonard Barolli,et al.  Implementation of Intelligent Hybrid Systems for Node Placement Problem in WMNs Considering Particle Swarm Optimization, Hill Climbing and Simulated Annealing , 2018, Mob. Networks Appl..

[11]  Fatos Xhafa,et al.  Implementation of a New Replacement Method in WMN-PSO Simulation System and Its Performance Evaluation , 2016, 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA).

[12]  Leonard Barolli,et al.  Performance evaluation of a QoS-aware fuzzy-based CAC for LAN access , 2016, Int. J. Space Based Situated Comput..

[13]  Maolin Tang,et al.  Gateways Placement in Backbone Wireless Mesh Networks , 2009, Int. J. Commun. Netw. Syst. Sci..

[14]  Leonard Barolli,et al.  A WLAN triage testbed based on fuzzy logic and its performance evaluation for different number of clients and throughput parameter , 2019 .

[15]  Albert A. Groenwold,et al.  A Study of Global Optimization Using Particle Swarms , 2005, J. Glob. Optim..

[16]  Leonard Barolli,et al.  Performance Evaluation of Intelligent Hybrid Systems for Node Placement in Wireless Mesh Networks: A Comparison Study of WMN-PSOHC and WMN-PSOSA , 2017, IMIS.

[17]  Leonard Barolli,et al.  Design and Implementation of a Hybrid Intelligent System Based on Particle Swarm Optimization and Distributed Genetic Algorithm , 2018, EIDWT.

[18]  Leonard Barolli,et al.  A Testbed for Admission Control in WLAN: A Fuzzy Approach and Its Performance Evaluation , 2016, BWCCA.

[19]  Leonard Barolli,et al.  Performance Evaluation of WMN-PSOSA Considering Four Different Replacement Methods , 2018, EIDWT.

[20]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[21]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[22]  Tarek M. Mahmoud,et al.  Solving the Wireless Mesh Network Design Problem using Genetic Algorithm and Simulated Annealing Optimization Methods , 2014 .

[23]  Catherine Rosenberg,et al.  Single Gateway Placement in Wireless Mesh Networks , 2008 .

[24]  Ian F. Akyildiz,et al.  Wireless mesh networks: a survey , 2005, Comput. Networks.

[25]  Fatos Xhafa,et al.  An Integrated Simulation System Considering WMN-PSO Simulation System and Network Simulator 3 , 2016, BWCCA.

[26]  M. Hannikainen,et al.  Genetic Algorithm to Optimize Node Placement and Configuration for WLAN Planning , 2007, 2007 4th International Symposium on Wireless Communication Systems.

[27]  Yoshikazu Fukuyama,et al.  A Hybrid Particle Swarm Optimization for Distribution State Estimation , 2002, IEEE Power Engineering Review.

[28]  Leonard Barolli,et al.  Performance Analysis of WMNs by WMN-PSODGA Simulation System Considering Load Balancing and Client Uniform Distribution , 2019, IMIS.

[29]  Leonard Barolli,et al.  Performance Analysis of WMNs by WMN-PSODGA Simulation System Considering Weibull and Chi-square Client Distributions , 2019, AINA.

[30]  Leonard Barolli,et al.  Performance Evaluation of WMNs by WMN-PSOSA Simulation System Considering Constriction and Linearly Decreasing Vmax Methods , 2017, 3PGCIC.

[31]  Leonard Barolli,et al.  Performance Evaluation of WMNs by WMN-PSOSA Simulation System Considering Constriction and Linearly Decreasing Inertia Weight Methods , 2017, NBiS.

[32]  Leonard Barolli,et al.  Performance analysis of two Wireless Mesh Network architectures by WMN-SA and WMN-TS simulation systems , 2017, J. High Speed Networks.

[33]  Leonard Barolli,et al.  Performance Analysis of Simulation System Based on Particle Swarm Optimization and Distributed Genetic Algorithm for WMNs Considering Different Distributions of Mesh Clients , 2018, IMIS.

[34]  Leonard Barolli,et al.  A Testbed for Admission Control in WLANs: Effects of RSSI on Connection Keep-Alive Time , 2017, 2017 31st International Conference on Advanced Information Networking and Applications Workshops (WAINA).

[35]  Leonard Barolli,et al.  Performance analysis of WMNs by WMN-GA simulation system for two WMN architectures and different TCP congestion-avoidance algorithms and client distributions , 2018, Int. J. Commun. Networks Distributed Syst..