- Title
- The role of edge computing in internet of things
- Creator
- Hassan, Najmul; Gillani, Saira; Ahmed, Ejaz; Yaqoob, Ibrar; Imran, Muhammad
- Date
- 2018
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/182358
- Identifier
- vital:16108
- Identifier
-
https://doi.org/10.1109/MCOM.2018.1700906
- Identifier
- ISBN:0163-6804 (ISSN)
- Abstract
- Remarkable advancements in embedded systems- on-a-chip have significantly increased the number of commercial devices that possess sufficient resources to run full-fledged operating systems. This change has extended the potential of the IoT. Many early IoT devices could only collect and send data for analysis. However, the increasing computing capacity of today's devices allow them to perform complex computations on-site, resulting in edge computing. Edge computing extends cloud computing capabilities by bringing services close to the edge of a network and thus supports a new variety of services and applications. In this work, we investigate, highlight, and report on recent advances in edge computing technologies with respect to measuring their impact on IoT. We establish a taxonomy of edge computing by classifying and categorizing existing literature, and by doing so, we reveal the salient and supportive features of different edge computing paradigms for IoT. Moreover, we present the key requirements for the successful deployment of edge computing in IoT and discuss a few indispensable scenarios of edge computing in IoT. Several open research challenges are also outlined. © 1979-2012 IEEE.
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- IEEE Communications Magazine Vol. 56, no. 11 (2018), p. 110-115
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2018 IEEE
- Subject
- 4006 Communications Engineering; 4606 Distributed Computing and Systems Software
- Reviewed
- Funder
- Imran’s work is supported by the Deanship of Scientific Research at King Saud University through Research Group No. (RG # 1435-051).
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