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A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

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arxiv 1906.08452 v2 pith:VYN4W3SR submitted 2019-06-20 cs.NI cs.DCcs.ITmath.IT

classification cs.NIcs.DCcs.ITmath.IT
keywords applicationscomputingnetworkcompute-intensiveedgemobiletechnologyusers
verification ladder T0 review T1 audit T2 compute T3 formal

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Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research.

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Cited by 1 Pith paper

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  1. Efficient Resource Allocation for Mobile-Edge Computing Networks with NOMA: Completion Time and Energy Minimization

    cs.IT 2019-08 conditional novelty 5.0 of 10

    A joint completion-time and energy minimization framework for multi-group NOMA-based mobile-edge computing, with iterative, bisection, and convex-equivalent algorithms.

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