A New Ant Algorithm for Optimal Service Selection with End-to-End QoS Constraints

Abstract

In this paper, we study the dynamic service composition becomes a decision problem on which component services should be selected under the E2E-to-End Quality of Service constraints. This problem is modeled is a nonlinear optimization problem under several constraints. We have two approaches to solve this problem. The first approach is local selection which is an efficient strategy with polynomial time complexity but can not handle global constraints. The second approach is the traditional global selection approach based on integer linear programming can handle global constraints, but its poor performance renders it inappropriate for practical applications with dynamic requirements. To overcome this disadvantage, in this study we proposed a novel Min-Max Ant System algorithm with the new utilities heuristic information to search the global approximate optimal. Our goal focus on its efficiency in terms of execution time and the quality in terms of the obtained best solution fitness value. The experiment results show that our algorithm is efficiency and feasibility more than the recently proposed related algorithms.