<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>
Over the recent decades, the nature of multi-core processors caused changing the serial programming model to parallel mode. There are several programming languages for the parallel multi-core processors and processors with different architectures that these languages have faced programmers to challenges to achieve higher performance. In addition, different scheduling methods in the programming languages for the multi-core processors have the significant impact on the efficiency of the programming languages. Therefore, this article addresses the investigation of the conventional scheduling techniques in the programming languages of multi-core processors which allows the researcher to choose more suitable programing languages by comparing efficiency than application. Several languages such as Cilk++، OpenMP، TBB and PThread were studied, and their scheduling efficiency has been investigated by running Quick-Sort and Merge-Sort algorithms as well.
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