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Mobile-Edge Computing Versus Centralized Cloud Computing Over a Converged FiWi Access Network

The advent of Internet of Things and 5G applications renders the need for integration of both centralized cloud computing and emerging mobile-edge computing (MEC) with existing network infrastructures to enhance storage, processing, and caching capabilities in not only centralized but also distribut...

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Bibliographic Details
Published in:IEEE eTransactions on network and service management 2017-09, Vol.14 (3), p.498-513
Main Authors: Rimal, Bhaskar Prasad, Dung Pham Van, Maier, Martin
Format: Article
Language:English
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Summary:The advent of Internet of Things and 5G applications renders the need for integration of both centralized cloud computing and emerging mobile-edge computing (MEC) with existing network infrastructures to enhance storage, processing, and caching capabilities in not only centralized but also distributed fashions for supporting both delay-tolerant and mission-critical applications. This paper investigates performance gains of centralized cloud and MEC enabled integrated fiber-wireless (FiWi) access networks. A novel unified resource management scheme incorporating both centralized cloud and MEC computation offloading activities into the underlying FiWi dynamic bandwidth allocation process is proposed. Both MEC and cloud traffic are scheduled outside the transmission slot of FiWi traffic by leveraging time division multiple access. An analytical framework is developed to model packet delay, response time efficiency, gain-offload overhead ratio, and communication-to-computation ratio for both cloud and broadband access traffic. In addition, given the importance of reliability in optical backhaul and MEC, this paper develops a probabilistic survivability analysis model to assess the impact of both fiber cuts and MEC server failures. The obtained results demonstrate the feasibility of implementing conventional cloud and MEC in FiWi access networks, without affecting network performance of broadband access traffic.
ISSN:1932-4537
1932-4537
DOI:10.1109/TNSM.2017.2706085