CAJ | 학술논문

Web服务作为一种新型的Web应用模式近年来得到了迅速的发展.如何高效动态地把现存的各种Web服务整合起来以形成新的满足不同用户需求的增值的复杂服务,已成为新的应用需求和研究热点.针对服务选择问题,设计了一种面向动态Web服务选择的离散微粒群算法,并结合服务选择研究背景,提出了3种速度计算算子和一种位置进化方程.针对进化算法容易陷入局部极值这一共同缺陷,定义了微粒无希望/重希望准则,以保证微粒群的多样性,增强全局搜索能力.理论分析和实验结果表明,该算法不仅具有较快的收敛速度,而且具有较好的全局收敛性能;同时说明Max运算在服务选择中具有较好的综合性能.
Web복무작위일충신형적Web응용모식근년래득도료신속적발전.여하고효동태지파현존적각충Web복무정합기래이형성신적만족불동용호수구적증치적복잡복무,이성위신적응용수구화연구열점.침대복무선택문제,설계료일충면향동태Web복무선택적리산미립군산법,병결합복무선택연구배경,제출료3충속도계산산자화일충위치진화방정.침대진화산법용역함입국부겁치저일공동결함,정의료미립무희망/중희망준칙,이보증미립군적다양성,증강전국수색능력.이론분석화실험결과표명,해산법불부구유교쾌적수렴속도,이차구유교호적전국수렴성능;동시설명Max운산재복무선택중구유교호적종합성능.
With the development of Web service theories and technologies, Web service has been spreading rapidly. In order to meet the requirements of different users, multiple services need to be composed. Therefore, how to dynamically and efficiently select appropriate Web services from existing services to build newly value-added and complex services has been a popular research focus. In this paper, a discrete particle swarm optimization (DPSO) algorithm is designed to facilitate the dynamic Web service selection, and combined with the specific meaning of service selection, three kinds of velocity operator and one position evolution equation are proposed. Aimed at the common limitation that evolutionary algorithms are prone to fall into the local optimal solution, no-hope/re-hope criterion is introduced to guarantee the diversity of particle swarm and improve the global search ability. Theoretical analysis and experimental results show that the proposed algorithm not only owns a good globally convergent performance but also has a faster convergent rate. Specially, the service selection method is independent of the candidate services number, which means that the efficiency of service selection will not decrease with the increase of available services. Furthermore, compared with other two velocity operators, the Max operator has best comprehensive properties in the process of service selection.