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Proceedings ArticleDOI

Joint allocation of computation and communication resources in multiuser mobile cloud computing

TLDR
This paper proposes a method to jointly optimize the transmit power, the number of bits per symbol and the CPU cycles assigned to each application in order to minimize the power consumption at the mobile side, under an average latency constraint dictated by the application requirements.
Abstract
Mobile cloud computing is offering a very powerful storage and computational facility to enhance the capabilities of resource-constrained mobile handsets. However, full exploitation of the cloud computing capabilities can be achieved only if the allocation of radio and computational capabilities is performed jointly. In this paper, we propose a method to jointly optimize the transmit power, the number of bits per symbol and the CPU cycles assigned to each application in order to minimize the power consumption at the mobile side, under an average latency constraint dictated by the application requirements. We consider the case of a set of mobile handsets served by a single cloud and we show that the optimization leads to a one-to-one relationship between the transmit power and the percentage of CPU cycles assigned to each user. Based on our optimization, we propose then a computation scheduling technique and verify the stability of the computations queue. Then we show how these queues are affected by the degrees of freedom of the channels between mobile handsets and server.

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Journal ArticleDOI

A Survey on Mobile Edge Computing: The Communication Perspective

TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management is provided in this paper, where a set of issues, challenges, and future research directions for MEC are discussed.
Posted Content

A Survey on Mobile Edge Computing: The Communication Perspective

TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management and recent standardization efforts on MEC are introduced.
Journal ArticleDOI

Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing

TL;DR: In this article, a game theoretic approach for computation offloading in a distributed manner was adopted to solve the multi-user offloading problem in a multi-channel wireless interference environment.
Journal ArticleDOI

Mobile Edge Computing: A Survey on Architecture and Computation Offloading

TL;DR: This paper describes major use cases and reference scenarios where the mobile edge computing (MEC) is applicable and surveys existing concepts integrating MEC functionalities to the mobile networks and discusses current advancement in standardization of the MEC.
Journal ArticleDOI

Mobile Edge Computing: A Survey on Architecture and Computation Offloading

TL;DR: In this paper, the authors present a survey of the research on computation offloading in mobile edge computing (MEC), focusing on user-oriented use cases and reference scenarios where the MEC is applicable.
References
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Journal ArticleDOI

The Case for VM-Based Cloudlets in Mobile Computing

TL;DR: The results from a proof-of-concept prototype suggest that VM technology can indeed help meet the need for rapid customization of infrastructure for diverse applications, and this article discusses the technical obstacles to these transformations and proposes a new architecture for overcoming them.
Book

Resource Allocation and Cross Layer Control in Wireless Networks

TL;DR: In this article, the authors present abstract models that capture the cross-layer interaction from the physical to transport layer in wireless network architectures including cellular, ad-hoc and sensor networks as well as hybrid wireless-wireline.
Journal ArticleDOI

Cloud Computing for Mobile Users: Can Offloading Computation Save Energy?

TL;DR: The cloud heralds a new era of computing where application services are provided through the Internet, but is it the ultimate solution for extending such systems' battery lifetimes?
Proceedings ArticleDOI

ThinkAir: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading

TL;DR: This paper proposes ThinkAir, a framework that makes it simple for developers to migrate their smartphone applications to the cloud and enhances the power of mobile cloud computing by parallelizing method execution using multiple virtual machine (VM) images.
Journal ArticleDOI

A Survey of Computation Offloading for Mobile Systems

TL;DR: An overview of the background, techniques, systems, and research areas for offloading computation is provided, and directions for future research are described.
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