Resource allocation in cloud computing using advanced imperialist competitive algorithm

Abstract

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p>Cloud computing makes possible free access to computing resources and high-level services for performing complex calculations and mass storage of information on the Internet. Resource management is one of the most important tasks of cloud providers, which is known as resource allocation. Heterogeneous resources and diverse requests at different time intervals makes it difficult to solve resources allocation problems and is considered as a NP-hard problem. Providing an efficient algorithm for resources allocation to satisfy the cloud providers and customers has always attracted much attention of researchers. Heuristic methods have always introduced as a good model for problem solving. However, most algorithms suffer from early convergence. This paper proposes a new approach based on imperialist competitive algorithm (ICA) which emphasizes the optimization of resource allocation in reducing time, cost and energy consumption. The proposed approach has been able to improve the early convergence of colonial competition algorithm by combining with the Tabu Search Algorithm to achieve an optimal solution at an acceptable time. The evaluated results show more efficiency performance than several relevant effective algorithms.</p></div></div></div>

Systematic mapping study of economic and business models of cloud services

“…The research enhancing provisioning in the area of business model in IaaS for the CSP. The work in [25] is resource allocation in cloud computing using advanced imperialist competitive algorithm. The work focused on providing an efficient algorithm for resources allocation to satisfy the cloud providers and customers.…”

Courses timetabling based on hill climbing algorithm

“…In this new approach, the hard constraints are already satisfied during the initial state as fulfillment of the soft constraints commences while, in the process, maintaining the hard constraints from any violations. In [12,13] a class-oriented representation of Timetable is used, which implicitly avoids classroom contentions, the instructor-oriented representation of timetable is used which implicitly avoids instructors time table contentions. In this paper, both Class-oriented and Instructor-oriented representations of a timetable, which avoid class clashes and instructor clashes are used in parallel.…”