Research On Energy-hole Avoiding Algorithm In Wireless Sensor Networks

Wireless sensor network is an emerging next-generation sensor network. It is expected to establish ubiquitous networks, which will pervade every aspect of society and life, affect or change people's work and life styles greatly. It has novelty and great prospects of potential applications. As a new technique of data acquisition and processing, the wireless sensor network is in the ascendant and becoming the hot area for the research institutions and enterprises.Wireless sensor node as a micro-device, has limited power supply energy. So the energy consumption of the node has a direct impact on the lifetime of the node. Energy-hole problem comes about in wireless sensor networks mostly due to the uneven energy consumption. Eventually, it causes that the network lifetime will be prematurely ended.This thesis investigates the energy-hole problem in the wireless sensor network and proposes a new way to solve it. Based on coronas model, network lifetime is redefined and the new dynamic coronas-dividing idea is introduced. This thesis transforms the energy-hole problem into the dynamic longest-shortest coronas lifetime problem successfully. Moreover, the mathematical model of that problem is well constructed. To the dynamic longest-shortest coronas problem, its ultimate focus is making the shortest coronas lifetime longest.Based on the immune optimization algorithm and antibody clonal selection theory, this thesis proposes an ICSA (Immune Clonal Selection Algorithm)-based energy-hole avoidance algorithm, which can helps to prolong the lifetime of the network by searching for best coronas width and approximate optimal transmission range list. First, this thesis gives the coding way of antibodies, the specific design of antibody division operator, immune cloning operator and other immune operators. It also brings in non-uniform antibody population size and non-uniform maximum number of iterations. Then the thesis investigates the performance of algorithm, ensuring that the solution of algorithm has a good quality and the algorithm has a faster convergence speed. Finally, the effectiveness of the algorithm is proved by simulation results. Compared with AASTRL, this solution balances the energy depletion and improves the network lifetime effectively.