The Research Of Node Sleep-scheduling Algorithm In Wireless Sensor Network

With the development of information technologies, it is possible to integrate the computing, communication, networking and sensing into one tiny embedded device, Wireless sensor network is a new research area embedded of those technologies. Wireless sensor network is an important research area of Ubiquitous Computing. Integrated with sensor unit, data processor unit and communication module, tiny sensor nodes can work to form a self-organization network, to sample the environment data or monitor the environment. The research of the wireless sensor network gradually gets the focus from the industrial and academe. It has a great application future in the military and civil area. But it also has many challenges in actual applications, one of its key question is that the node's physics size determine its limited battery capacity. Moreover, since sensors are often intended to work in remote or hostile environment, it is undesirable or impossible to recharge or replace the battery power of all the sensors. Reducing the energy consumption in the RF module is the key to save energy. Because in the transmitting mode, RF module energy consumption is the highest, while in sleep mode, it consumes least energy. So reducing redundant communication and scheduling the redundant nodes to sleep can reduce energy consumption.A node sleep-scheduling, which has suggested that each node follows a periodic cycle of active/sleep radio states, selecting some nodes as working nodes by redundant nodes judging algorithm every turn, to reduce whole network energy consumption, obviously the most important part above them is the judging of redundant nodes. So this paper suggests a node sleep-scheduling basing on network density self-adaptive and verifies that this way not only reduce its complexity, but also making it adjust its algorithm by density self-adaptive. The simulation results show that this algorithm reduce the judging active nodes, prolonging the network lifetime, achieving the consumption objective.Besides, this paper changes its coverage model, and puts this density self-adaptive redundant nodes judging algorithm in probability coverage model. Moreover this model offsets the shortage of original model (0-1 coverage model), which reckon without existing interfere factor such as electromagnetism, background noise and so on. The simulation results verify that a node sleep-scheduling basing on density self-adaptive nodes judging algorithm in probability coverage model selecting a little more nodes than 0-1 coverage model, but it can greatly improve the probability of network coverage and more accurately defined the network's coverage ability.