Performance analysis of hybrid evolutionary optimization algorithms for multipath routing in wireless sensor networks

Abstract

newline The development made in wireless sensor networks is immense and numerous protocols were developed to synchronize the operations of the network models Several factors like congestion mechanism packet delivery survival of nodes network lifetime optimal path determination and minimal execution time and so on are to be observed and maintained on a linear scale for the performance of the network to be on a superior side But due to high data transfer rate and population of the end-users increases day byday in an extraordinary manner the wireless sensor network WSN models comes across relatively higher problems in complete congestion of the network side To handle this difficulty in the past years many protocols has been developed to stream line the congestion control and ensure effective packet delivery at the end-user side is done The growth of evolutionary optimization algorithm has gone to several heights and due to their capability in achieving optimal solutions; they are widely employed in numerous science and engineering applications Evolutionary optimization algorithms are basically inspired by the social behaviour of humans and other species that occur in nature These nature inspired behaviours of species result in the development of algorithmic models so as to achieve optimal solutions with minimal computation cost In this thesis novel hybrid evolutionary optimization algorithms and their variants are developed and applied to design an effective multipath routing of wireless sensor network models Reasonable multipath routing mechanism is an ultimatum need to determine optimal path with best accuracy rates in data transmission rates newline newline