Performance Comparison of Mesh Router Replacement Methods by WMN-PSOHC Simulation System Considering Linearly Decreasing Inertia Weight Method and Linearly Decreasing Vmax Method

Author(s):  
Shinji Sakamoto ◽  
Admir Barolli ◽  
Seiji Ohara ◽  
Leonard Barolli ◽  
Shusuke Okamoto
2021 ◽  
pp. 1-16
Author(s):  
Admir Barolli ◽  
Kevin Bylykbashi ◽  
Ermioni Qafzezi ◽  
Shinji Sakamoto ◽  
Leonard Barolli ◽  
...  

Wireless Mesh Networks (WMNs) are gaining a lot of attention from researchers due to their advantages such as easy maintenance, low upfront cost and high robustness. Connectivity and stability directly affect the performance of WMNs. However, WMNs have some problems such as node placement problem, hidden terminal problem and so on. In our previous work, we implemented a simulation system to solve the node placement problem in WMNs considering Particle Swarm Optimization (PSO) and Distributed Genetic Algorithm (DGA), called WMN-PSODGA. In this paper, we compare chi-square and uniform distributions of mesh clients for different router replacement methods. The router replacement methods considered are Constriction Method (CM), Random Inertia Weight Method (RIWM), Linearly Decreasing Inertia Weight Method (LDIWM), Linearly Decreasing Vmax Method (LDVM) and Rational Decrement of Vmax Method (RDVM). The simulation results show that for chi-square distribution the mesh routers cover all mesh clients for all router replacement methods. In terms of load balancing, the method that achieves the best performance is RDVM. When using the uniform distribution, the mesh routers do not cover all mesh clients, but this distribution shows good load balancing for four router replacement methods, with RIWM showing the best performance. The only method that shows poor performance for this distribution is LDIWM. However, since not all mesh clients are covered when using uniform distribution, the best scenario is chi-square distribution of mesh clients with RDVM as a router replacement method.


2008 ◽  
Vol 17 (02) ◽  
pp. 401-409
Author(s):  
YUTTHAPONG TUPPADUNG ◽  
WERASAK KURUTACH

This paper presents an optimal feeder-switch relocation that is applied by modified Particle Swarm Optimization (MPSO). An inertia weight in Particle Swarm Optimization (PSO) is modified to find the best patterns of distribution configuration. MPSO performance is evaluated by comparison with the conventional inertia weight method. Six different benchmark functions with asymmetric initial range settings are selected as testing functions. A nonlinear inertia weight function is applied in this paper. The results of the experiment illustrate the advantage of MPSO. The optimal feeder-switch relocation in a radial distribution system is used to evaluate the MPSO performance. The results show that MPSO can identify suitable switch locations, based on minimum customer interruption costs.


Sign in / Sign up

Export Citation Format

Share Document