深圳大学学报(理工版)
深圳大學學報(理工版)
심수대학학보(리공판)
JOURNAL OF SHENZHEN UNIVERSITY (SCIENCE & ENGINEERING)
2010年
1期
49-55
,共7页
蔡华利%刘鲁%樊坤%王理
蔡華利%劉魯%樊坤%王理
채화리%류로%번곤%왕리
计算机应用%离散二进制粒子群优化%web服务%QoS属性%多目标优化
計算機應用%離散二進製粒子群優化%web服務%QoS屬性%多目標優化
계산궤응용%리산이진제입자군우화%web복무%QoS속성%다목표우화
computer application%binary particle swarm optimization(BPSO)%web services%quality of service (QoS) attributes%multi-objective optimization
为解决web服务的优化选择,提出一种基于离散二进制粒子群算法(binary particle swarm optimization,BPSO)的web服务推荐策略.用数学方法阐述基于服务质量(quality of service,QoS)的业务组合,将业务单元组合转换到服务组合,给出不同服务组合模式下的QoS属性值计算公式,提出web服务集和嵌套概念,对具有嵌套模式的服务组合进行逐一遍历.将基于QoS的web服务组合优化问题看成是多目标优化决策问题,提出基于BPSO的web服务组合优化数学模型,利用目标加权法简化多目标决策问题.对BPSO进行改进,构建了基于BPSO的web服务推荐仿真系统,仿真表明,该方法高效可行.
為解決web服務的優化選擇,提齣一種基于離散二進製粒子群算法(binary particle swarm optimization,BPSO)的web服務推薦策略.用數學方法闡述基于服務質量(quality of service,QoS)的業務組閤,將業務單元組閤轉換到服務組閤,給齣不同服務組閤模式下的QoS屬性值計算公式,提齣web服務集和嵌套概唸,對具有嵌套模式的服務組閤進行逐一遍歷.將基于QoS的web服務組閤優化問題看成是多目標優化決策問題,提齣基于BPSO的web服務組閤優化數學模型,利用目標加權法簡化多目標決策問題.對BPSO進行改進,構建瞭基于BPSO的web服務推薦倣真繫統,倣真錶明,該方法高效可行.
위해결web복무적우화선택,제출일충기우리산이진제입자군산법(binary particle swarm optimization,BPSO)적web복무추천책략.용수학방법천술기우복무질량(quality of service,QoS)적업무조합,장업무단원조합전환도복무조합,급출불동복무조합모식하적QoS속성치계산공식,제출web복무집화감투개념,대구유감투모식적복무조합진행축일편력.장기우QoS적web복무조합우화문제간성시다목표우화결책문제,제출기우BPSO적web복무조합우화수학모형,이용목표가권법간화다목표결책문제.대BPSO진행개진,구건료기우BPSO적web복무추천방진계통,방진표명,해방법고효가행.
To optimize the web services selection process, a method based on binary particle swarm optimization (BPSO) for recommending web services was proposed. The process composition, based on quality of service (QoS), was mathematically described and transformed into service composition. The formulas for calculating the QoS attributes in different service compositions were provided. Each service composition in the nested format was traversed by introducing the web services sets and nested formats. Treated as a multi-objective optimization decision problem, QoS-based web services selection was simplified by weighted summation. Finally, the web services recommendation simulation system was developed based on the improved BPSO. Three experiments demonstrate the proposed method is feasible and effective.