Harvested Energy Adaptive Load Balancing in WSNs

Abstract

The distribution of wireless sensor network field in modern life brings special requirements in routing protocols. The routing algorithms for being efficient in Wireless Sensor Network (WSN) should satisfy the features of energy consumption optimization and extension of network lifetime.The objective of routing algorithms in energy harvesting wireless sensor network area is not to extend network's lifetime, but also to maximize the workload. This thesis report a comprehensive thesis work on both energy efficient and energy harvesting routing algorithms in WSN field. There are few Energy Harvesting Wireless Sensor Network (EH-WSN) routing algorithms that are mentioned in literature. In this paper we have defined some analysis metrics and implemented a simulator which fully satisfy the requirement The behavioral analysis of chosen algorithms in the case of different scenarios are completely reported in this thesis. In this work we have used ALB as the base technique and improved it using the energy harvesting concept, hence making HEALB i.e. Harvesting energy based ALB. The subject of this paper is a kinetic energy generator which converts mechanical energy in the form of vibrations present in the application environment into electrical energy. Kinetic energy is typically converted into electrical energy using electromagnetic, piezoelectric or electrostatic transduction mechanisms [3]. Vibrations are an attractive source since the energy present can be harvested by compact inertial devices that benefit from a high Q-factor amplifying the base excitation amplitude. Suitable vibrations can be found in numerous applications including common household goods(fridges, washing machines, microwave ovens), industrial plant equipment, moving vehicles such as automobiles and aeroplanes and structures such as buildings and bridges [4]. Human-based applications are characterized by low frequency high amplitude displacements [5, 6]. The amount of energy generated by this approach fundamentally depends upon the quantity and form of the kinetic energy available in the application environment and the efficiency of the generator and the power