بهینه سازی فرا ابتکار ترکیبی برای شبکه های حسگر بی سیم (WSN)
Abstract
1- Introduction
2- Network energy model
3- Proposed technique
4- Experimental set-up and results
5- Conclusions
References
Abstract
Energy efficiency has recently turned out to be primary issue in wireless sensor networks. Sensor networks are battery powered, therefore become dead after a certain period of time. Thus, improving the data dissipation in energy efficient way becomes more challenging problem in order to improve the lifetime for sensor devices. The clustering and tree based data aggregation for sensor networks can enhance the network lifetime of wireless sensor networks. Hybrid Ant colony optimization (ACO) and particle swarm optimization (PSO) based energy efficient clustering and tree based routing protocol is proposed. Initially, clusters are formed on the basis of remaining energy, then, hybrid ACOPSO based data aggregation will come in action to improve the inter-cluster data aggregation further. Extensive analysis demonstrates that proposed protocol considerably enhances network lifetime over other techniques.
Introduction
With the advent of Wireless Sensor Networks, inaccessible environments can be easily monitored. It is a powerful tool to gather data in many applications like military surveillance, battle-field, forestry, oceanography, temperature, pressure, humidity, etc. [1]. WSNs contain number of sensor nodes which are connected together and to a base station. WSNs include sensing of data through sensor nodes, processing of data, and transmission to base station. Charging and reinstallation of sensor nodes do not possible in difficult environments. So, energy conservation is a big challenge in WSNs. Recently, researchers gave a solution to this problem by organizing the nodes into clusters and enhance the life-time of WSNs [2]. Further, routing protocols are implemented in cluster WSNs to guide the selection of Cluster Heads (CHs) and discover best route to save the energy of nodes [3]. A typical cluster based wireless sensor network is shown in Fig. 1. Nayak and Anurag Devulapalli [4] utilized fuzzy logic based clustering technique to reduce the energy consumption rate further. In this method, size of cluster is optimized through Fuzzy inference engine (Mamdani’s rule). The appropriate selection of CHs reduces the energy consumption and enhances the life of network. Gong et al. [5] designed a routing protocol ETARP (i.e., Energy Efficient Trust-Aware Routing Protocol for Wireless Sensor Networks) to reduce the energy consumption and increase the security during communication among nodes in WSNs. The selection of route between sensor nodes is based on utility theory. Shi et al. [6] addressed the issue of mobile sinks like route maintenance in WSNs by introducing dynamic layered routing protocol. The distribution frequencies and scopes of routing updates are minimized using the combination of dynamic anchor selection and dynamic layered Voronoi scoping.