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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

Integration of ICN and MEC in 5G and Beyond Networks: Mutual Benefits, Use Cases, Challenges, Standardization, and Future Research

TL;DR: This paper discusses and elaborate on Information-Centric Networking (ICN) MEC integration to provide a comprehensive survey with a forward-looking perspective for B5G networks, and deduce lessons learned from related works for both 5G and beyond networks.
Proceedings ArticleDOI

Task Offloading with Uncertain Processing Cycles

TL;DR: In this article, the authors proposed an energy minimization solution with probabilistic deadline guarantee to task offloading problem in mobile edge computing (MEC), where the number of required processing cycles of a task is usually unknown in advance.
Journal ArticleDOI

Edge-enabled Mobile Crowdsensing to Support Effective Rewarding for Data Collection in Pandemic Events

TL;DR: In this article, an edge-anabled mobile crowdsensing platform, called ParticipAct, exploits edge nodes to compute possible dangerous crowd situations and a federated blockchain network to store reward states.
Journal ArticleDOI

Energy-Efficient Real-Time Heart Monitoring on Edge–Fog–Cloud Internet of Medical Things

TL;DR: In this article , a distributed multi-output convolutional neural network (CNN) architecture is used to decrease the energy consumption and latency between the edge fog/cloud, which achieves an accuracy of 99.2% on the well-known MIT-BIH Arrhythmia Data Set.
Proceedings ArticleDOI

Smart Food Scanner System Based on Mobile Edge Computing

TL;DR: A smart application, built on top of mobile edge computing concept, to enables users to measure and analyse their food intake and support nutritional decision-making and can be used as an interactive appliance by users with minimum dependency and usage of their mobile phones.
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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