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Open AccessJournal ArticleDOI

Mobile Edge Computing: A Survey

TLDR
The definition of MEC, its advantages, architectures, and application areas are provided; where the security and privacy issues and related existing solutions are also discussed.
Abstract
Mobile edge computing (MEC) is an emergent architecture where cloud computing services are extended to the edge of networks leveraging mobile base stations. As a promising edge technology, it can be applied to mobile, wireless, and wireline scenarios, using software and hardware platforms, located at the network edge in the vicinity of end-users. MEC provides seamless integration of multiple application service providers and vendors toward mobile subscribers, enterprises, and other vertical segments. It is an important component in the 5G architecture which supports variety of innovative applications and services where ultralow latency is required. This paper is aimed to present a comprehensive survey of relevant research and technological developments in the area of MEC. It provides the definition of MEC, its advantages, architectures, and application areas; where we in particular highlight related research and future directions. Finally, security and privacy issues and related existing solutions are also discussed.

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Mobile Edge Computing: A
Survey
architecture, applications, approaches and challenges
Nasir Abbas
Master’s Thesis Autumn 2016


Mobile Edge Computing: A Survey
Nasir Abbas
December 12, 2016

ii

Abstract
Mobile edge computing (MEC) is an emergent architecture where cloud
computing services are extended to the edge of networks into the mobile
base stations. As a promising edge technology, it can be applied to mobile,
wireless and wireline scenarios, using software and hardware platforms,
located at the network edge in the vicinity of end users. MEC provides
seamless integration of multiple application service providers and vendors
towards mobile subscribers, enterprises and other vertical segments. It is
an important component in the proposed 5G architecture that supports
variety of innovative applications and services where ultra low latency
is required. However, there are some challenges exists in the MEC eco
system. To address these challenges, first off need to understand the
network infrastructure of MEC, cloud and cellular network.
Some questions and problems are addressed in this thesis that outlines
the importance and challenges of MEC deployment. Impact of MEC
integration with the traditional mobile and cloud network appears in
this paper. A survey has been presented that contributes in general
understanding of mobile edge computing (MEC). Readers will have
an overview of MEC, such as definition, advantages, architectures and
applications. Moreover, related research and future directions are pointed
out in this thesis. Finally, security and privacy issues and their possible
solutions are also discussed.
iii

Citations
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Journal ArticleDOI

Energy Efficient Relay Selection and Resource Allocation in D2D-Enabled Mobile Edge Computing

TL;DR: The proposed algorithm is a low-complexity algorithm which is associated with the root finding method and can not only achieve the optimal solution with less time cost, but also improve the energy efficiency and network capacity.
Journal ArticleDOI

Information fusion for edge intelligence: A survey

TL;DR: In this paper , the authors provide a comprehensive investigation of four representative scenarios assisted by information fusion at the edge, i.e., multisource information fusion, real-time information fusion and event-driven information fusion.
Journal ArticleDOI

Market Analysis of MEC-Assisted Beyond 5G Ecosystem

TL;DR: In this article, the authors proposed a revenue maximization model for private (local) telecom operators and cloud service owners to minimize the cost from the end-user perspective while satisfying the latency requirement.
Journal ArticleDOI

Radio and computing resource allocation with energy harvesting devices in mobile edge computing environment

TL;DR: A time average computation rate maximization (TACRM) algorithm that allows the joint allocation of radio and computation resources and can effectively improve the system performance and outperforms the benchmark schemes is proposed.
Journal ArticleDOI

Enabling Machine Learning with Service Function Chaining for Security Enhancement at 5G Edges

TL;DR: An elastic framework to integrate ML with virtualized SFC, aiming at smart and efficient provision of different services at MEC and an ML-based anomaly detection algorithm used as a kind of service policy for SFC classifiers, which guides the latter for quick traffic classification and subsequent redirections of attack flows are proposed.
References
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ReportDOI

The NIST Definition of Cloud Computing

Peter Mell, +1 more
TL;DR: This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.
Journal ArticleDOI

Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications

TL;DR: An overview of the Internet of Things with emphasis on enabling technologies, protocols, and application issues, and some of the key IoT challenges presented in the recent literature are provided and a summary of related research work is provided.
Journal ArticleDOI

Recent advances in augmented reality

TL;DR: This work refers one to the original survey for descriptions of potential applications, summaries of AR system characteristics, and an introduction to the crucial problem of registration, including sources of registration error and error-reduction strategies.
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.
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