概率模型下线性规划优化覆盖方案

覆盖率不仅是评价无线传感器网络体系性能重要标准之一，也是无线传感器网络所研究的一项重点课题.为此，提出了一种复杂动态参数模型下优化覆盖算法，该算法通过对动态参数覆盖模型的计算，给出了传感器节点覆盖的期望值和公差的求解过程以及对所关注目标节点进行首次覆盖后的期望值证明过程.在网络能量方面，则通过节点状态调度策略对通信路径进行优化，证明节点能量衰减过程中，似然拟合函数极限存在的意义，实现了传感器节点能量的有效匹配，抑制了传感器节点能量的消耗，证明了优化后整个监测区域传感器节点覆盖函数之间关系.仿真实验表明，本算法不仅提高了覆盖和网络服务质量，而且有效地抑制了网络能量开销，延长网络生存周期.

Novel Linear Programming Optimal Coverage Scheme Based on Probability Model

Coverage rate is not only an important criterion to evaluate the performance of wireless sensors networks but also an important research topic in wireless sensors network area. In this paper, we present an optimized coverage algorithm based on dynamic parameter model, by which the calculation process of the expected value and variance of sensor node coverage are derived. The algorithm gives the proof of expected value of the target node that is covered for the first time. In terms of network energy, the communication path is optimized by node status scheduling strategy. It proves the significance of the limit of likelihood fit function in node energy decay process, also it realizes efficient match and constrains the decay of sensor nodes energy, proving the relationship between the sensor coverage functions of the whole monitoring area. Simulation results show that this algorithm improves the coverage and quality of network service, and extends the network lifetime by restraining network energy cost effectively.