Service Composition Instantiation Based on Cross-Modified Artificial Bee Colony Algorithm  

作　　者：Lei Huo Zhiliang Wang 

机构地区：[1]School of Automation, University of Science and Technology Beijing [2]School of Computer and Science, University of Science and Technology Beijing

出　　处：《China Communications》2016年第10期233-244,共12页中国通信（英文版）

基　　金：supported by a grant from the Project "Multifunctional mobile phone R & D and industrialization of the Internet of things" supported by the Project of the Provincial Department of research (2011A090200008);partly supported by National Science and Technology Major Project (No. 2010ZX07102-006);the National Basic Research Program of China (973 Program) (No. 2011CB505402);the Major Program of the National Natural Science Foundation of China (No. 61170117);the National Natural Science Foundation of China (No.61432004);the National Key Research and Development Program (No.2016YFB1001404)

摘　　要：Internet of things(IoT) imposes new challenges on service composition as it is difficult to manage a quick instantiation of a complex services from a growing number of dynamic candidate services. A cross-modified Artificial Bee Colony Algorithm(CMABC) is proposed to achieve the optimal solution services in an acceptable time and high accuracy. Firstly, web service instantiation model was established. What is more, to overcome the problem of discrete and chaotic solution space, the global optimal solution was used to accelerate convergence rate by imitating the cross operation of Genetic algorithm(GA). The simulation experiment result shows that CMABC exhibited faster convergence speed and better convergence accuracy than some other intelligent optimization algorithms.Internet of things （IoT） imposes new challenges on service composition as it is difficult to manage a quick instantiation of a complex services from a growing number of dynamic candidate services. A cross-modified Artificial Bee Colony Algorithm （CMABC） is proposed to achieve the optimal solution services in an acceptable time and high accu- racy. Firstly, web service instantiation model was established. What is more, to overcome the problem of discrete and chaotic solution space, the global optimal solution was used to accelerate convergence rate by imitating the cross operation of Genetic algorithm （GA）. The simulation experiment result shows that CMABC exhibited faster convergence speed and better convergence accuracy than some other intelligent optimization algorithms.

关 键 词：optimization of service composition optimal service instantiation artificial bee colony algorithm swarm algorithm cross strategy 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]