Swarm intelligence and its applications to wireless ad hoc and sensor networks
Swarm intelligence, as inspired by natural biological swarms, has numerous powerful properties for distributed problem solving in complex real world applications such as optimisation and control. Swarm intelligence properties can be found in natural systems such as ants, bees and birds, whereby the collective behaviour of unsophisticated agents interact locally with their environment to explore collective problem solving without centralised control. Recent advances in wireless communication and digital electronics have instigated important changes in distributed computing. Pervasive computing environments have emerged, such as large scale communication networks and wireless ad hoc and sensor networks that are extremely dynamic and unreliable. The network management and control must be based on distributed principles where centralised approaches may not be suitable for exploiting the enormous potential of these environments. In this thesis, we focus on applying swarm intelligence to the wireless ad hoc and sensor networks optimisation and control problems. Firstly, an analysis of the recently proposed particle swarm optimisation, which is based on the swarm intelligence techniques, is presented. Previous stability analysis of the particle swarm optimisation was restricted to the assumption that all of the parameters are non random since the theoretical analysis with the random parameters is difficult. We analyse the stability of the particle dynamics without these restrictive assumptions using Lyapunov stability and passive systems concepts. The particle swarm optimisation is then used to solve the sink node placement problem in sensor networks. Secondly, swarm intelligence based routing methods for mobile ad hoc networks are investigated. Two protocols have been proposed based on the foraging behaviour of biological ants and implemented in the NS2 network simulator. The first protocol allows each node in the network to choose the next node for packets to be forwarded on the basis of mobility influenced routing table. Since mobility is one of the most important factors for route changes in mobile ad hoc networks, the mobility of the neighbour node using HELLO packets is predicted and then translated into a pheromone decay as found in natural biological systems. The second protocol uses the same mechanism as the first, but instead of mobility the neighbour node remaining energy level and its drain rate are used. The thesis clearly shows that swarm intelligence methods have a very useful role to play in the management and control iv problems associated with wireless ad hoc and sensor networks. This thesis has given a number of example applications and has demonstrated its usefulness in improving performance over other existing methods.