Energy Optimization for Large Scale Wireless Sensor Network using Real-Time Dynamics

Abstract

depletion in Wireless Sensor Network (WSN) is one of the most focused research area in wireless network which is yet to witness a potentially significant mitigation techniques for ensuring substantial energy preservation. Owing to the resource constraints as well as low computational capability of the sensor mote, usually the existing energy conservation techniques finds its quite challenging to encapsulate variables of entire problem space. Hence, for the purpose of better mathematical formulation for energy efficiency solutions, it is necessary that all the real-time constraints should be empirically considered. Therefore, this paper presents a novel optimization technique that ensures sustainance of optimal network lifetime in large scale WSN considering the real-time dynamics. The outcome accomplished from the study is compared with standard and most frequently adopted energy- efficient hierarchical routing algorithm to find that proposed system meets better criteria of energy preservation in large scale network. focused on solving the energy issue in order to maximize the lifetime of the WSN. However, very few of the prior work have received recognition. Out of the majority of the work introduced in the past, LEACH (3) is considered as highly standard and benchmarked formulation till data. May be this is one of the reason, why 97% of the outcome of the existing research work focusing on energy issues is compared with LEACH algorithm. Although there are various versions of LEACH algorithm, but major research communities select LEACH model as the standard work because of the design of the radio model and energy model. Various components that maps with the physical entities in the sensor mote is considered in the LEACH protocol. However, various studies also proved that LEACH is not the appropriate protocol to mitigate the energy issues. Hence, this fact gave rise to various other research work addressing the similar energy issues using Artificial Neural Network (4), Genetic Algorithm (5), Fuzzy Logic (6), Swarm Intelligence (7), game theory (8) and many other advanced technologies. However, till date none of the prior studies has managed to optimize the cumulative network lifetime of the WSN. This study therefore attempts to investigate the root cause of the energy depletion and introduces an empirical formulation that assist to optimize the cumulative network exponentially. The proposed study digs into the energy model preliminarily where the various constraints of the sensor motes were discussed with mathematical variables and optimization condition has been derived. Not only this, the model also considers a fact that if the cluster head is appropriately selected and ensures participation of other cluster heads too, exclusively in large scale wireless sensor network, than there is a fair possibilities of energy optimization in cost effective manner. Section-2 gives an overview of related work which identifies all the major research work being done in this area. Section 3 highlights problem formulation of the proposed study considering various real-time constraints and limitation of WSN. Section 4 discusses about the proposed model. Section 5 discusses about the implementation technique and result discussion. This section also discusses about the algorithm that has been used for the study along with various outcome of the study for the purpose of analyzing the effectiveness of the outcome. Finally, Section 6 summarizes the present paper.