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Particle swarm optimization and artificial bee colony algorithm for clustering and mobile based software-defined wireless sensor networks
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AbstractWith the development of the internet of things, people pay more and more attention to wireless sensor networks. Designing the energy efficient routing is an essential objective for wireless sensor networks. Cluster routing is one of the most popular routing protocols to enhance the network lifetime. However, hotspot problem always exists in cluster-based routing protocol. The task of this study is designing a cluster routing protocol with mobile base station which aims at balancing the energy consumption and prolonging the network lifetime. In this article, we design a particle swarm optimization and artificial bee colony algorithm for clustering and mobile based software-defined wireless sensor networks. The software defined network architecture is used to reduce the energy overhead and computation overhead in sensor nodes. Particle swarm optimization-based cluster routing algorithm is used to calculate the cluster heads and the sojourn locations of base station. Artificial bee colony algorithm-based traversal path algorithm is used to design the move path of the base station. Comparing with relevant protocols, the proposed protocol reduces the energy consumption, enhances the network lifetime and reduces the control overhead.
Title: Particle swarm optimization and artificial bee colony algorithm for clustering and mobile based software-defined wireless sensor networks
Description:
AbstractWith the development of the internet of things, people pay more and more attention to wireless sensor networks.
Designing the energy efficient routing is an essential objective for wireless sensor networks.
Cluster routing is one of the most popular routing protocols to enhance the network lifetime.
However, hotspot problem always exists in cluster-based routing protocol.
The task of this study is designing a cluster routing protocol with mobile base station which aims at balancing the energy consumption and prolonging the network lifetime.
In this article, we design a particle swarm optimization and artificial bee colony algorithm for clustering and mobile based software-defined wireless sensor networks.
The software defined network architecture is used to reduce the energy overhead and computation overhead in sensor nodes.
Particle swarm optimization-based cluster routing algorithm is used to calculate the cluster heads and the sojourn locations of base station.
Artificial bee colony algorithm-based traversal path algorithm is used to design the move path of the base station.
Comparing with relevant protocols, the proposed protocol reduces the energy consumption, enhances the network lifetime and reduces the control overhead.
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