Based On Artificial Immune-mixed And Colony Algorithm Of WSN Path Optimization Research

Wireless Sensor network (WSN) is different from the traditional network, it is formedby many Sensor nodes in self-organization, and widely used in military, environment,household and other fields. Each sensor node has low cost, low power consumption,multi-function, small volume, etc. But at the same time also has the limitation energy, andthe node non-renewable and other defects. These nodes are usually placed in the unmannedmonitoring or human inaccessible environment, coordinated to complete informationacquisition, data transmission, and other important work. In wireless sensor network mostof energy is consumed in stage of communication. And communication energyconsumption is related to the length of information transmission path, and the size of theinformation be delivered in two factors. Therefore, in the design of wireless sensornetwork path optimization algorithm, need to consider how the algorithm can effectivelyoptimized the length of the path between wireless sensor nodes, as far as possible to reducethe energy consumption.Intelligent algorithm is more and more be known, they are applied in every aspect inthe field of computer buy the excellent performance. This article chose the artificialimmune algorithm and ant colony algorithm to do in-depth research, and introduces theprinciple of artificial immune algorithm and ant colony algorithm, concept, and thealgorithm flow. Mainly describes the artificial immune-ant colony algorithm, the basicprinciple, algorithm flow, and some important parameters and formulas, and wirelesssensor network model, mathematical model and algorithm in wireless sensor network pathoptimization in the implementation, the important function of introduction, main code.This article success in fuse the artificial immune algorithm and ant colony algorithm,making up for the lack of artificial immune algorithm in using the feedback information ofthe system, improving the rate of convergence of the algorithm. Moreover the algorithmhas been used in the variety of mutation operator, to prevent the algorithm trapped in localoptimal solution, to ensure the diversity of understanding. According to the characteristicof wireless sensor network, putting a new formula of affinity, effective guarantee theconvergence of the algorithm. Lots of experiments show that the artificial immune and ant colony algorithm can efficiently optimize the path of the wireless sensor network (WSN),reduce the information of energy consumption caused by transmission long path.