Implementation and evaluation of a simulation system based on particle swarm optimisation for node placement problem in wireless mesh networks
View/Open
Cita com:
hdl:2117/89934
Document typeArticle
Defense date2016
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial
property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public
communication or transformation of this work are prohibited without permission of the copyright holder
Abstract
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.
CitationSakamoto, S., Oda, T., Ikeda, M., Barolli, L., Xhafa, F. Implementation and evaluation of a simulation system based on particle swarm optimisation for node placement problem in wireless mesh networks. "International journal of communication networks and distributed systems", 2016, vol. 17, núm. 1, p. 1-13.
ISSN1754-3916
Publisher versionhttp://www.inderscience.com/offer.php?id=77935
Collections
Files | Description | Size | Format | View |
---|---|---|---|---|
authorFinalVersion.pdf | 1013,Kb | View/Open |