• Corpus ID: 10299098

Mobile Edge Computing: Survey and Research Outlook

  title={Mobile Edge Computing: Survey and Research Outlook},
  author={Yuyi Mao and Changsheng You and Jun Zhang and Kaibin Huang and Khaled Ben Letaief},
Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in… 

EMM: Energy-Aware Mobility Management for Mobile Edge Computing in Ultra Dense Networks

A novel user-centric energy-aware mobility management scheme, based on Lyapunov optimization and multi-armed bandit theories, that can achieve close-to-optimal delay performance while satisfying the user energy consumption constraint.

Multi-access Edge Computing: A Survey

This paper provides a comprehensive survey of the state-of-the-art research efforts on MEC domain, with focus on the architectural proposals as infrastracture, the issue of the partitioning of processing among the user devices, edge servers, and a cloud, and theissue of the resource management.

Mobile Cooperative Computing: Energy-Efficient Peer-to-Peer Computation Offloading

The optimal offloading is shown to be achieved by the well-known “string-pulling” strategy, graphically referring to pulling a string across the tunnel, and the problem of optimal data partitioning for offloading and local computing at the user is convex.

Joint offloading and computing optimization in wireless powered mobile-edge computing systems

A wireless powered multiuser MEC system, where a multi-antenna access point (AP) (integrated with an MEC server) broadcasts wireless power to charge multiple users and each user node relies on the harvested energy to execute latency-sensitive computation tasks, is considered.

A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges

This paper presents a comprehensive survey of recent developments in MEC-enabled video streaming bringing unprecedented improvement to enable novel use cases, and a detailed review of the state-of-the-art is presented covering novel caching schemes, optimal computation ofoading, cooperative caching and the use of artificial intelligence in M EC-assisted video streaming services.

Geo-partitioning of MEC Resources

This paper proposes a graph-based algorithm that, taking into account a maximum MEC server capacity, provides a partition of MEC clusters, which consolidates as many communications as possible at the edge, and evaluates it with real world spatio-temporal human dynamics.

Energy-Efficient Mobile Cooperative Computing

This paper considers a co-computing system where a user offloads computation of input-data to a helper, and proves that the problem of optimal data partitioning for offloading and local computing at the user is convex.

Joint Service Caching and Task Offloading for Mobile Edge Computing in Dense Networks

An efficient online algorithm, called OREO, is proposed, which jointly optimizes dynamic service caching and task offloading to address a number of key challenges in MEC systems, including service heterogeneity, unknown system dynamics, spatial demand coupling and decentralized coordination.

A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms

A comprehensive survey of emerging computing paradigms from the perspective of end-edge-cloud orchestration is presented to discuss state-of-the-art research in terms of computation offloading, caching, security, and privacy.

Device vs Edge Computing for Mobile Services: Delay-Aware Decision Making to Minimize Power Consumption

  • Meysam Masoudi
  • Computer Science
    IEEE Transactions on Mobile Computing
  • 2021
This paper investigates the power minimization problem for the mobile devices by data offloading in multi-cell multi-user OFDMA mobile edge computing networks and proposes centralized and distributed algorithms for joint power allocation and channel assignment together with decision-making.



A survey on mobile edge computing

  • Arif AhmedE. Ahmed
  • Computer Science
    2016 10th International Conference on Intelligent Systems and Control (ISCO)
  • 2016
In this paper, some of the promising real time Mobile Edge Computing application scenarios are discussed and a state-of-the-art research efforts on Mobile Edge computing domain is presented.

Collaborative Mobile Edge Computing in 5G Networks: New Paradigms, Scenarios, and Challenges

A real-time, context-aware collaboration framework that lies at the edge of the RAN, comprising MEC servers and mobile devices, and amalgamates the heterogeneous resources at theedge is envisions.

Mobile Edge Computing

Future wireless networks will provide communication infrastructure support to this ubiquitous computing paradigm, but at the same time they can also utilize the new-found computing power to drastically improve communication efficiency, expand service variety, shorten service delay, and reduce operation expenses.

Cloud offloading for multi-radio enabled mobile devices

A comprehensive computation offloading solution that uses the multiple radio links available for associated data transfer, optimally through the available radio links and an iterative algorithm that converges to a locally optimal solution is provided.

Challenges on wireless heterogeneous networks for mobile cloud computing

The framework of HetNet for MCC is introduced, identifying the main functional blocks and the current state of the art techniques for each functional block, and the challenges for supporting MCC applications in Het net under this proposed framework are discussed.

Communicating While Computing: Distributed mobile cloud computing over 5G heterogeneous networks

Virtualization makes it possible to run multiple operating systems and multiple applications over the same machine (or set of machines) while guaranteeing isolation and protection of the programs and their data, thus improving the overall system computational efficiency.

Edge computing enabling the Internet of Things

IoT can extend this paradigm to other areas with the use of Software Defined Network (SDN) orchestration to cope with the challenges hindering the IoT real deployment, as it will illustrate in this paper.

Exploring device-to-device communication for mobile cloud computing

Two mobile cloud access schemes are proposed: optimal and periodic access schemes, and the corresponding performance of mobile cloud computing is studied (i.e., mobile cloud size, node's serviceable time percentage, and task success rate).

Fog Computing: Focusing on Mobile Users at the Edge

Fog computing is a lubricant of the combination of cloud computing and mobile applications that extends cloud computing by providing virtualized resources and engaged location-based services to the edge of the mobile networks so as to better serve mobile trafficking.

Mobile Edge Computing: A Taxonomy

A taxonomy for Mobile Edge Computing applications is introduced and chances and limitations from a technical point of view are analyzed and application types which profit from edge deployment are identified and discussed.