CAJ | 학술논문

轮廓查询是近年来信息服务领域的一个研究重点和热点．现有的三阶段算法TPAOSS （Three-Phase Algo-rithm for Optimizing Skyline Scalar ）至少存在如下两个缺陷：（1）在TPAOSS算法的第3阶段中，当网络节点上的对象个数较多时，Bloom filter的长度将呈指数级增长，从而严重影响获取子空间重复值的效率以及占用内存空间的大小；（2） TPAOSS算法只考虑预处理阶段的时间代价，而没有考虑各网络节点进行局部或全局子空间轮廓查询计算的效率．为此，提出一种适合超对等网络（Super-Peer Architecture ，SPA ）的子空间轮廓查询方法EPSSQDN （Efficient Processing of Sub-space Skyline Queries in Distributed Networks ）．EPSSQDN算法有效解决了TPAOSS算法的的两个主要性能问题，并且显著提高了SPA网络中的子空间轮廓查询处理的效率．此外，为了能够进一步降低子空间上轮廓查询的时间开销以及网络节点间的数据传输量，我们给出新颖且有效的优化策略．实验结果表明，EPSSQDN算法比TPAOSS算法更能够缩短SPA网络中子空间轮廓查询的时间开销．
륜곽사순시근년래신식복무영역적일개연구중점화열점．현유적삼계단산법TPAOSS （Three-Phase Algo-rithm for Optimizing Skyline Scalar ）지소존재여하량개결함：（1）재TPAOSS산법적제3계단중，당망락절점상적대상개수교다시，Bloom filter적장도장정지수급증장，종이엄중영향획취자공간중복치적효솔이급점용내존공간적대소；（2） TPAOSS산법지고필예처리계단적시간대개，이몰유고필각망락절점진행국부혹전국자공간륜곽사순계산적효솔．위차，제출일충괄합초대등망락（Super-Peer Architecture ，SPA ）적자공간륜곽사순방법EPSSQDN （Efficient Processing of Sub-space Skyline Queries in Distributed Networks ）．EPSSQDN산법유효해결료TPAOSS산법적적량개주요성능문제，병차현저제고료SPA망락중적자공간륜곽사순처리적효솔．차외，위료능구진일보강저자공간상륜곽사순적시간개소이급망락절점간적수거전수량，아문급출신영차유효적우화책략．실험결과표명，EPSSQDN산법비TPAOSS산법경능구축단SPA망락중자공간륜곽사순적시간개소．
Skyline query has recently received a lot of attention in information service community .The TPAOSS (Three-Phase Algorithm for Optimizing Skyline Scalar ) algorithm has two performance drawbacks :(1 ) in the third phase of TPAOSS ,as the number of objects on net nodes increases ,the length of bloom filter will increases exponentially ,which will seriously influence the efficiency of obtaining replicated values and the occupation size of memory ;(2 ) the TPAOSS algorithm does not consider the computation efficiency of local or global subspace skyline queries in each net node .Motivated by these facts ,we propose EPSSQDN (Efficient Processing of Subspace Skyline Queries in Distributed Networks ) ,an algorithm for efficient processing of subspace sky-line queries in SPA distributed networks .Moreover ,in order to further reduce the computation cost of subspace skyline queries and decrease the volume of data transferred ,we present an efficient optimized techniques .Furthermore ,we present extensive experiments that demonstrate our method is more advantageous than the TPAOSS algorithm .