Abstract
The ever increasing number of users in Wireless Mesh Networks (WMNs) setups consequently represents an upsurge in competitions for available services. Consequently, services are clogged and ran over WMNs, which further leads to poor Quality of Service (QoS). Quick and timely discovery of available services becomes an essential parameter in optimizing performance of WMNs. In this paper therefore, we present a Priority-based Service Discovery Model (PSDM) using Swarm Intelligence in WMNs. We use the Particle Swarm Optimization (PSO) algorithm to dynamically define and prioritize services supported by the network. Additionally, the Ant Colony Optimization (ACO) algorithm is used to choose the shortest path when each transmitter has to be searched to identify if it possesses the requested services. We have designed and implemented the PSDM using Network Simulator 2 (NS-2) tool. Consequently, we realized throughput of 80%, service availability of 96% in some instances, and an average delay of 1.8 ms.
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We would like to give thanks to Tshwane University of Technology for financial support.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Ndlovu, L., Lall, M., Kogeda, O.P. (2018). A Priority-Based Service Discovery Model Using Swarm Intelligence in Wireless Mesh Networks. In: Bissyande, T., Sie, O. (eds) e-Infrastructure and e-Services for Developing Countries. AFRICOMM 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 208. Springer, Cham. https://doi.org/10.1007/978-3-319-66742-3_20
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DOI: https://doi.org/10.1007/978-3-319-66742-3_20
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