Nature inspired heuristic algorithms for mobile data gathering in wireless sensor networks

Abstract

Wireless Sensor Network applications are more popular and gaining importance nowadays with the recent development of the Internet of Things, fabrication technologies, miniaturization and cheaper sensors. The design of a sensor network is influenced by several factors like network topology, power consumption, scalability, transmission medium, hardware constraint which introduces numerous design challenges. The majority of the research challenges in sensor network is due to the limited battery energy available on each sensor node which limits the lifetime of the network. Sensing, processing and data transmission are the common tasks that happen in each sensor node in a sensor network among which data transmission newlineconsumes more energy than event sensing which have a direct impact on the lifetime of the network. The amount of energy consumption depends on the distance between sensor nodes while data transmission. In order to reduce the energy consumption, a mobile sink approach is employed to collect data from sensor nodes using single hop transmission reducing the energy consumption. In this thesis, priority based rendezvous planning algorithm for wireless sensor networks under delay constraints was formulated. Rendezvous approach is one in which a set of rendezvous point nodes was selected based on their priority value and mobile sink was made to visit the selected rendezvous point nodes. The priority is calculated based on the number of packets to transmit and the hop count to the nearest rendezvous point. The rendezvous points were selected using a tour refinement procedure constrained by the maximum allowable delay during data collection. The experimental results show that the proposed work reduced the energy consumption, improved the packet delivery ratio, and took less execution time. newline newline