Abstract
Clustering techniques in wireless sensor networks have been widely utilized for their good performance in reducing energy dissipation and prolonging network lifetime. Once the cluster heads have been decided, the allocation of member nodes in the cross coverages formed by two or more clusters is critical to keep an energy balance on the cluster heads. In earlier studies, however, the allocation of member nodes simply depends on the distance or degree (the node number within the cluster heads’ communication radius) and, therefore, could cause imbalance to the cluster heads’ load and further degrade the whole wireless sensor network. To maintain the load balance of the cluster heads, in this article, game theory is introduced into the allocation problem of the member nodes. Before using the game theory approach, the number and distribution of cluster heads are first checked. If the cover rate of the cluster heads is low, then the node(s) uncovered by any cluster are randomly selected as new cluster head(s) to attain the cover rate required in the article. Furthermore, the number of cluster heads in a monitoring region is restricted. Finally, a game-based, energy-balance method is proposed and applied in the cluster-based routing protocols to improve their performance. For verification, the proposed method is embedded into the localized game theoretical clustering algorithm and hybrid, game theory–based and distributed clustering algorithm, which are two game theory and typical cluster-based routing protocols. The experimental results show that both of the improved protocols do balance the loads of the cluster heads and achieve better performance than their original versions in spanning the lifetime and balancing the energy in wireless sensor networks.
Highlights
Wireless sensor networks (WSNs) have attracted broad attention from many research communities in recent years for their good performance
It is important to devise a Game theory (GT)-based and energy-balance protocol between the minimization of the energy expenditure and the effective provision of necessary services.[6] clustered routing for selfish sensors (CROSS)[17] is the first protocol to use the GT to find the optimal cluster head (CH) in the clustering routing
We mainly use GT to analyse the optimal allocation of member nodes (MNs) in cross coverages by two or more clusters after the election of the CHs
Summary
Wireless sensor networks (WSNs) have attracted broad attention from many research communities in recent years for their good performance. Each node must provide services for the global interest In this situation, it is important to devise a GT-based and energy-balance protocol between the minimization of the energy expenditure and the effective provision of necessary services.[6] clustered routing for selfish sensors (CROSS)[17] is the first protocol to use the GT to find the optimal CHs in the clustering routing. We mainly use GT to analyse the optimal allocation of MNs in cross coverages by two or more clusters after the election of the CHs. In addition, in the CH-selection phase, the number and the distribution of the CHs are considered to be important factors that affect the network performance. We apply GT to determine the allocation of the sensor nodes in the cross coverage by two or more clusters Their appropriate allocation makes the CHs and the whole network have better energy balance. All of the considerations are devoted to constructing an energy-efficient network
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