원문정보
초록
영어
With the growing number of alternative services in the cloud environment, users have put forward new requirements to solve the service dynamic selection problem quickly and efficiently. In this paper, an evaluation model of service process which considers concurrent requests and service association is proposed. This model evaluates the service process from three dimensions which are functional quality dimension, non-functional quality dimension and transactional dimension. To solve the service selection problem efficiently, we first design a novel coding strategy of particle, and then propose an approach based on hybrid particle swarm optimization algorithm which combines the crossover and mutation operators of genetic algorithm. The experimental results show that our proposed approach is feasible and effective.
목차
1. Introduction
2. Problem Statement
3. The Comprehensive Evaluation Model
3.1 Functional Quality
3.2 Non-functional Quality
3.3 Aggregation Functions
3.4 Transactional Properties
3.5 Service Association
3.6 Comprehensive Evaluation Model
4. Service Selection Approach based on Hybrid Particle Swarm Optimization (HPSO-SSA)
4.1 Particle Swarm Optimization
4.2 Coding Strategy
4.3 Crossover and Mutation
4.4 Algorithm Design of HPSO-SSA
5. Experiment and Analysis
5.1 Performance vs. Number of iterations
5.2. Performance vs. Number of Concurrent Processes
6. Conclusion
Acknowledgements
References