M.A. Thesis:

Cloud resource scheduling based on the Loin optimization algorithm (LOA)

Cloud computing is undeniable in today's world of information technology and more of the technology is being introduced today. One of the most important issues and challenges in the cloud computing field is related to the scheduling of tasks and the resources allocation. In the cloud environment problem like energy consumption load balancing and the speed with which applications are executed will be an effective and timely way for the user to schedule tasks and tasks well. The need for proper time scheduling in the cloud environment is to execute resource allocation tasks effectively. In fact the problem of resources allocating in the cloud environment is a matter of NP-Hard. So far researchers have presented various methods based on collective intelligence algorithms. In this research it is attempted to provide better performance in resources allocating and scheduling by providing an effective model based on lion optimization algorithm. The lion optimization algorithm is able to provide the appropriate solutions for NP-Hard issues in a convenient structure for group problem searching space. The simulation results in Chapter 4 show that the proposed method in this study is more effective than resources allocating and scheduling tasks in the cloud environment in comparison with the Ant colony algorithm.

Keywords: cloud computing, resource allocation, task scheduling, lion optimization algorithm