Lifetime Optimization In Wireless Sensor Network

Wireless sensor network is the combination of information collection, transmission and processing. Wireless sensor network combined the sensor technology, embedded technology, wireless communication, and distributed information processing and micro-electro-mechanism system. It can monitor environment and collect information in real time with all kinds of integrated micro-sensor. Then it would process the collected information by embedded unit and finally transport it to terminal user by multi-hop wireless ad hoc network which constructed randomly. So the conception of the omnipresent computing constructed. However, new incoming problem followed with the birth of the wireless sensor network. As known that the sensor network relies on the battery for it power. And it is impossible for recharging and replacing the battery in sensor. Therefore, the problem how to maximize lifetime of wireless sensor network attracted researchers' attention. They proposed their optimization model and cross-layer strategy. In the article, author firstly analyzes current layer-based optimal methods for wireless sensor network and laid emphasis on the physical, link and routing optimization. Then we compare the strategy of cross-layer optimization and layer optimization.According to the analysis and summary of the current lifetime optimization in wireless sensor network, the article redefines the lifetime of wireless sensor network: lifetime is the time that one of the articulation nodes runs out of energy. Then by analyzing the character of the wireless sensor network, we built the system model and bring forward the cross-layer design for revolving-based lifetime optimization in wireless sensor network (joint routing, physical and link layer). However, we found that the optimal problem is dynamic and hard to be computed. So we define the general set of articulation nodes and make some essential deduction for the optimal problem in order to make it mathematically feasible. Finally, we calculate the optimization problem and found that our algorithm prolong the network lifetime in some extent.