Optimal Provisioning of Resource in a Cloud Service

Cloud service allows enterprise class and individual users to acquire computing resources from large scale data centers of service providers. This cloud service is more involved in purchasing and consuming manners between providers and users than others. However, Cloud service providers charge users for these services. Specifically, to access data from their globally distributed storage edge servers, providers charge users depending on the user’s location and the amount of data transferred. User applications may incur large data retrieval and execution costs. Therefore, optimizing execution time, the cost arising from data transfers between resources as well as execution costs should be taken into account. In this paper, we present a discrete Particle Swarm Optimization (DPSO) approach for tasks allocation. We construct application Amazon EC2 as an example and simulation with Cloud based compute and transmission resources. Experimental studies illustrate that the proposed method is more efficient and surpasses those of mathematical programming and reflecting the actual benefit of saving with the total cost as well as tasks allocation.