基于IDSQ的自适应动态协同自组织算法

Adaptively dynamic collaborative self-organization algorithm based on IDSQ

在无线传感器网络中传感器节点相互协同完成感知任务,以传感器量测的信息效用与获取量测的能量消耗来折中地选择参与节点,但用户对服务质量(QoS)的需求并没有在节点选择时得以体现.为此,提出一种自适应动态协同自组织算法(A-DCS).该算法能根据用户给定的精度需求,自适应地选择簇首,确定参与感知任务的簇成员顺序和个数,并计算相应的能量消耗.以目标跟踪为应用背景的仿真结果表明,在跟踪精度和能量消耗2个指标下,该算法优于信息驱动传感器查询(IDSQ)和动态协同自组织(DCS).

Sensors should be selected elaborately to fulfil the sensing task in wireless sensor networks, sensor selection is based on the tradeoff between information utility achieved by the sensor measure and energy overhead to fetch the measure. But the users＇ requirements for quality of service（QoS） aren＇t yet involved in the process of sensor collaboration. Therefore, an algorithm, adaptively dynamic collaborative self-organization（A-DCS）, is proposed. According to the given accuracy, the cluster header can be select and the sequence and number of cluster member can be made adaptively, and the corresponding energy consumption is computed. This algorithm is then adapted to the specific application of target tracking. Simulation results show that this algorithm is superior to information driven sensor querying（IDSQ） and dynamic collaborative selforganization（DCS） based on the tracking accuracy and the energy consumption.