Research of Resource Scheduling based on ACA-GA in the Cloud Computing

다국어 초록 (Multilingual Abstract)

How to better conduct research resource scheduling has long been a research direction of cloud computing. This paper, aiming at slow convergence and easiness of falling local optimum of ant colony algorithm,has integrated genetic algorithm into the ant colony algorithm and obtained hybrid algorithm (ACA -GA); in the initial solution of the ant colony algorithm, it has adopted selection, crossover and mutation operations of genetic algorithm to obtain an effective initial solution; secondly, it has used the perception threshold of ant colony algorithm path setting to regulate individual selection optimal path; finally, it has improved volatile factor so as to significantly improve the updating efficiency of pheromone. The algorithm in the paper proved that the performance of the algorithm has been also significantly improved through classical test functions. Cloudsim platform shows that, the algorithm above mentioned reduces the time and cost spent in resource scheduling of, hence has some promotional value.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Resource Scheduling Model of Cloud Computing Based on QoS
• 3. Description of Basic Algorithms
• 3.1 Basic Ant Colony Algorithm
• 3.2 Genetic Algorithm
• 4. Hybrid Algorithm Based on Ant Colony Algorithm and Genetic Algorithm in Cloud Computing
• 4.1 Initialize Ant Colony Algorithm with Genetic Algorithm
• 4.2 Sensory Threshold Setting — Path Selection
• 4.3 Improvement of Pheromone Play Factor P
• 4.4 Algorithm Description
• 5. Analysis of Simulation Experiment
• 5.1. Comparison of Performance with Basic Ant Colony Algorithm and Genetic Algorithm
• 5.2 Comparison with other Intelligent Algorithms in Cloud Computing
• 5.3. User QOS Analysis
• 6. Conclusion
• References