Discrete gbest-guided artificial bee colony algorithm for cloud service composition

Abstract

The widespread application of cloud computing creates massive application services on the Internet, which is a new challenge for the models and algorithms of cloud service composition. This paper proposes a new method for cloud service composition. Time attenuation function is added into the service composition model, and service composition is formalized as a nonlinear integer programming problem. Moreover, the Discrete Gbest-guided Artificial Bee Colony (DGABC) algorithm is proposed, which simulates the search for the optimal service composition solution through the exploration of bees for food. Experiments show that the service composition model with the time attenuation function can make the quality of service more consistent with the current characteristics of services. Compared with other algorithms, the DGABC algorithm has advantages in terms of the quality of solution and efficiency, especially for the large-scale data, and it can obtain a near-optimal solution within a short period of time.