Mobile Agent Service Selection Based On Ant Colony Algorithm

Migrating workflow system framework is composed of a migrating workflow management unit and a number of local area networks to establish friendly relations of trust composed. Migrating workflow management machine to perform workflow engine, each LAN consists of a docking station connected to the server and the number of its working machine. Docking station server core mission is in accordance with certain preferred instance selection mechanism for the migration suitable job position, so migrating instance migrate to the appropriate location to perform work tasks carried, in general, migrating instance Mobile Agent paradigm is constructed. Mobile Agent refers to a program to replace or perform some other task procedures, it can choose to run their own place and time to interrupt its execution under specific circumstances, to move to another device recovery, and returns the result. Mobile Agent has the autonomy, mobility, collaboration, security, and intelligence and other characteristics.Mobile Agent service under the chosen target is to meet the needs of mobile Agent running case, choose the best quality of service for mobile working position Agent. Mobile Agent are able to provide the basis for their operational needs and quality of service for each working position, gradually choose the most suitable working position time, consideration, and finally complete the task sequence. Ant Colony Algorithm since the1990s has been successfully applied to solve a variety of multi-objective optimization problem, the algorithm has a parallel, positive feedback and heuristic search and other features. Firstly, the establishment of service selection problem multi-objective optimization model, and the ant colony algorithm to solve the problem of mobile Agent service selection, and finally through the experiment to verify the feasibility of the algorithm.This article includes the following three aspects:(1) The basic principles and application of ant colony algorithm is described in detail, for the aspects of a comprehensive exposition of QoS-based service selection problem, transforming from a problem model, service selection strategy, combined with the current study gives a solution service options commonly used algorithm problem;(2) For Mobile Agent service selection problem has been described, the introduction of quality of service (QoS) concept to define various parameters for the calculation of the parameters to be discussed, given the formal description of the model, the Mobile Agent service selection problem into a multi-objective programming problems;(3) Through the state transition rule, pheromones and other aspects of improvements designed ant colony algorithm for multi-objective problems. The time complexity of the algorithm and space complexity is analyzed on the convergence of the algorithm is proved. The main categories in the model has been designed, and by choosing seven different sets of parameters of the simulation experiment results verify the feasibility of the algorithm, effectiveness and convergence.