一种基于预测的目标跟踪传感器网络数据近似存储查询策略

Prediction Based Approximate Schema of Data Storage and Query Processing in Object-tracking Sensor Networks

节能问题是传感器网络设计的一个关键问题,在对目标跟踪传感器网络中的目标位置信息进行存储和查询处理时,也必须通过较低的通信代价来降低消息复杂度,从而达到节能的目的。分析了现存的一些数据存储和数据分发的方法,针对EASE方法查询误差较大的问题,提出了基于预测的近似查询的存储策略(Prediction-based Energyconserving Approximate StoragE,P-EASE),并就EASE方法查询未考虑选择恰当的存储节点的问题,提出了一种基于地理位置的择优查询(Optimal Query)策略。使用半随机步行移动模型和随机路点移动模型进行了仿真实验,比较了P-EASE与EASE算法的消息量、消息复杂度、平均消息复杂度和查询误差。仿真实验证明,P-EASE比EASE查询更精确、能量更高效。

Energy efficiency is one of the most critical issues in the design of wireless sensor networks. In object-trac-king sensor networks, the data storage and query processing should be energy-conserving by decreasing the message complexity. In this paper, current algorithms of data storage and data dissemination were analyzed. By figuring out the shortcomings of EASE, a Prediction-based Energy-conserving Approximate StoragE（P-EASE） was proposed, which re- duces the query error of EASE by prediction and enables a geo-based optimal query algorithm to taking into considera- tion to query the proper storage node. The simulation experiments were conducted with semi-random walk and random waypoint mobility models which compareed the overall messages, message complexity, average message complexity and query error to validate that P-EASE is more energy-conserving than EASE and has less query error as well.