传感器网络模糊覆盖

Fuzzy coverage for sensor networks

目前,对传感器网络不确定性覆盖问题的研究主要从概率论和数理统计方法入手。然而实际应用中,传感器的感知能力会受到天气或环境等因素的影响,且随着时间的推移会发生变化,另外人们对实际环境的认知有限也会造成传感器感知信息获取的不完整,所有这些因素导致传感器在感知类属方面客观存在着亦此亦彼的性态,主观认识也必然带有模糊性。对于上述情况,就不能再利用传统的概率论和数理统计方法来解决不确定覆盖问题。为此,通过基于模糊理论对上述情况进行数学建模,提出了感知模糊环的概念,给出了传感器网络的模糊覆盖分析方法,定义了覆盖强度隶属函数和融合算子,并在此基础上分析了确定部署和随机均匀部署情况下的模糊覆盖特性。试验结果表明该模型很好地解决了传感器网络的不确定覆盖问题。

The approaches to coverage problems with uncertainty in sensor networks are mainly based on probability theory and statistics nowadays. However, in practical applications, sensing abilities would be affected by weather or environmental factors and change with time. Also, limited cognition of real environment could lead to imperfect information acquisition. As a result, the coverage problem in real environment is inherently non-deterministic and there is certain degree of fuzziness associated with the sensing coverage. Traditional probability theory and statistics approaches are inappropriate in such situations. Therefore, we adopt fuzzy theory to propose a new notion of sensing fuzzy annulus and provide an analysis approach to fuzzy coverage in sensor networks. The membershi Pfunction and fusion operator for coverage intensity are defined. Based on this model, we investigate its implications for deterministic and random sensor deployment in sensor networks. Numerical and simulation results show that this model has good performance in handling the coverage with uncertainty.