中文摘要：

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.

英文摘要：

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 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.