Abstract
The emergence of mobile cloud computing (MCC) brings benefits to mobile users and cloud providers. However, due to the inherent limitations of the device such as battery life time, CPU and memory capacity, a mobile thin client device ( e.g. smart phones, tablets, iWatch, Google Glass, etc ) cannot meet the requirements of some demanding applications. To alleviate this limitation, the mobile device should cooperate with external resources to increase its performance. Recently, current research approaches have been unable to offer an efficient, seamless computing experience. In this paper, we present a comprehensive thin-thick client collaboration that involves conventional desktop or laptop computers, known as thick clients, by allowing the thin client to borrow resources from thick clients, particularly for optimizing data distribution and utilizing MCC resources to meet Service-Level Agreements, Quality-of-Service requirements and cloud service customers’ budget. Our work uses both numerical analysis and simulation to prove that our proposed architecture can improve resource allocation efficiency and achieve better performance than other existing approaches in some cases. DOI: http://dx.doi.org/10.5755/j01.eee.22.1.14113
Highlights
According to Gartner Inc., there were approximately 2.4 billion units of cellular phones and tablets shipped in 2013, outstripping PC sales in the same period, which were less than 315 million shipments [1]
There is a thick client functioning as a centralized management node, known as a broker, which receives all computation requests from users and manages the processor’s profiles as well as the results of the data query returned from virtual machine (VM)
Using the cost in (4) and cumulative distribution function (CDF) F(x), we can calculate the minimum number of VMs which satisfy both Service-Level Agreement (SLA) and the cloud computing (CC)’s budget by applying Algorithm 1
Summary
According to Gartner Inc., there were approximately 2.4 billion units of cellular phones and tablets shipped in 2013, outstripping PC sales in the same period, which were less than 315 million shipments [1]. The paper introduces a selection procedure of suitable algorithms that optimally utilize resource allocation in order to meet expected Service-Level Agreement (SLA) and QoS requirements and the CC budget in order to improve users' cloud computing experience. In these algorithms, we use a multi-user multi-task technique on each virtual machine (VM) and create a group of service images (SIs) from thin clients, integrate them into a multi-user multi-task VM. The last section concludes the paper and suggests future work
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