无线传感器网络(ε,δ)-近似Top-k查询处理算法

(ε,δ)-approximate Top-k query processing algorithm in wireless sensor networks

提出一种适合于任意数据分布的基于抽样的(ε,δ)–近似Top-k查询处理算法。其中,ε≥0和0≤δ<1分别是相对误差界和失败概率界。理论分析表明,对于任意ε≥0和0≤δ<1,该算法返回的查询结果的相对误差界大于ε/(1+ε)的概率小于δ。于是,该算法可以达到任意精度。同时,还给出了支持近似Top-k查询的优化的抽样算法,并通过节点上的数据过滤技术来减少通信能量的消耗。理论分析和仿真结果表明,提出的算法能量消耗低并且计算复杂度低。

A sampling based approximate Top-k algorithm was proposed that is adaptive for any data distribution.δ≥0 and 0≤δ1 are respectively relative error bound and failure probability bound.The theoretical analysis demonstrates that for any δ≥0 and 0≤δ1 the probability that the relative error bound of the results returned by this algorithm is larger than ε/（1＋ε） is less than δ.So the proposed algorithm can reach arbitrary precision.Furthermore,an optimal sampling algorithm was proposed that supported the approximate Top-k query,and through the technique of data filtering the en-ergy consumption of communication was reduced.Theoretical analysis and simulation show that the proposed algorithm is efficient and consumes little energy.