An Energy Consumption‐based Dynamic Round Rotation T Ime Optimization For LEACH

Wireless sensor network is a special kind of ad-hoc network for detecting physical phenomena, and then it converts all the information into digital data which can be processed and analyzed. In wireless sensor networks, balancing energy consumption of nodes in the network is an important issue in wireless sensor networks research. Energy consumption balance problems on the network directly affect the performance of all aspects of the entire network.In wireless sensor networks, node’s energy was supplied by batteries, energy is very limited, how to balance the energy consumption of wireless sensor networks is the focus of the study in recent years researchers, a good agreement can extend the life cycle of the network, improve network performance. Which, LEACH protocol is a good energy saving protocol, which uses a clustering method, the data is concentrated in a few nodes for forwarding, saving most of the energy consumption, and took the idea of the cycle to build clusters, The cycle that we build clusters is called a continuous cycle of LEACH, thus balancing the energy consumption of nodes can improve network lifetime. However, the length of the sustain period of time also have a great impact on the energy consumption of the nodes. The main objective of this paper is to find the optimized sustained periods of time based on LEACH protocol, in this time, LEACH protocol can achieve maximum network life cycle. For this purpose, we first studied in the case of static energy consumption and uniform clustering, optimization LEACH sustained period of time. Then considering the problem for real environment of LEACH, the energy consumption of the node that is dynamic, and often uneven clustering, we make some improvements to LEACH protocol, proposing the optimization algorithm with dynamic adjustment sustained period of time to balance the energy consumption of nodes. Finally, based on the optimized calculated theoretical sustained period of time, we analyze a number of network performance indicators to verify the accuracy and validity of the method on NS2 simulation platform.