Adaptive Resource Allocation Optimization in Heterogeneous Mobile Cloud Systems

2015 IEEE 2nd International Conference on Cyber Security and Cloud Computing Pub Date : 2015-11-03 DOI:10.1109/CSCloud.2015.60

Longbin Chen, Yucong Duan, Meikang Qiu, Jian Xiong, Keke Gai

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引用次数: 25

Abstract

Recent growth of cloud computing has driven the development of Heterogeneous Cloud Federation (HCF) that has been considered an approach of improving the diversity of cloud systems by enable cloud users to select resources provided by different service providers. Using this mechanism can divide a complicate task into a group of sub-tasks in order to increase the efficiency of application executions, which can support simultaneously executing different cloud systems. One of the resource allocation mechanisms is to schedule tasks among cloud providers. However, current challenge of implementing this mechanism is to generate an efficient task scheduling. We consider mobile cloud computing an adaptive approach for increasing the utilizations of mobile devices. Addressing this dimension, we propose our solution named Mobile Cloud-based Heterogeneous Resource Allocation Model (MC-HRAM), which is designed to minimize the execution time. The main algorithm used in the proposed model is Dynamic Heterogeneous Task Assignments Algorithm (DHTA). Our experimental evaluation has proved that our proposed schema has an advantage of saving execution time.

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异构移动云系统中的自适应资源分配优化

最近云计算的增长推动了异构云联盟(HCF)的发展，它被认为是一种通过使云用户能够选择由不同服务提供商提供的资源来改善云系统多样性的方法。使用这种机制可以将复杂的任务划分为一组子任务，以提高应用程序执行的效率，从而支持同时执行不同的云系统。资源分配机制之一是在云提供商之间调度任务。然而，实现该机制目前面临的挑战是如何生成有效的任务调度。我们认为移动云计算是一种提高移动设备利用率的自适应方法。为了解决这个问题，我们提出了一个名为移动云异构资源分配模型(MC-HRAM)的解决方案，该解决方案旨在最大限度地减少执行时间。该模型使用的主要算法是动态异构任务分配算法(DHTA)。实验结果表明，该方案具有节省执行时间的优点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2015 IEEE 2nd International Conference on Cyber Security and Cloud Computing

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