Cited by 874IoT and Edge/Fog ComputingSoftware-Defined Networks and 5GEnergy Efficiency in Computing

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Future Edge Cloud and Edge Computing for Internet of Things Applications

Pan, Jianli, McElhannon, James·2018·IEEE Internet of Things Journal

DOI 10.1109/jiot.2017.2767608

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Abstract

The Internet is evolving rapidly toward the future Internet of Things (IoT) which will potentially connect billions or even trillions of edge devices which could generate huge amount of data at a very high speed and some of the applications may require very low latency. The traditional cloud infrastructure will run into a series of difficulties due to centralized computation, storage, and networking in a small number of datacenters, and due to the relative long distance between the edge devices and the remote datacenters. To tackle this challenge, edge cloud and edge computing seem to be a promising possibility which provides resources closer to the resource-poor edge IoT devices and potentially can nurture a new IoT innovation ecosystem. Such prospect is enabled by a series of emerging technologies, including network function virtualization and software defined networking. In this survey paper, we investigate the key rationale, the state-of-the-art efforts, the key enabling technologies and research topics, and typical IoT applications benefiting from edge cloud. We aim to draw an overall picture of both ongoing research efforts and future possible research directions through comprehensive discussions.

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Untitled work
McKeown (2008) · doi:10.1145/1355734.1355746 · Cited by 8,513
Fog computing and its role in the internet of things
Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012) · Proceedings of the first edition of the MCC workshop on Mobile cloud computing · doi:10.1145/2342509.2342513 · Cited by 6,244
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Untitled work
(2011) · doi:10.1145/1966445.1966473 · Cited by 1,870
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Ahmed, A., & Ahmed, E. (2016) · International Conference on Intelligent Systems and Control · doi:10.1109/isco.2016.7727082 · Cited by 611
COMET: code offload by migrating execution transparently
Gordon, M. S., Jamshidi, D. A., Mahlke, S. A., Mao, Z. M., & Xu, C. (2012) · doi:10.5555/2387880.2387890 · Cited by 370
Odessa
Ra, M.-R., Sheth, A. N., Mummert, L., Pillai, P. S., Wetherall, D. J., & Govindan, R. (2011) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/1999995.2000000 · Cited by 360
Femto clouds: leveraging mobile devices to provide cloud service at the edge
Habak, K., Ammar, M., Harras, K. A., & Zegura, E. (2015) · 2015 IEEE 8th International Conference on Cloud Computing · doi:10.1109/cloud.2015.12 · Cited by 291

Show all 17 references

Research works printed but not linked: 11

2016, Openstack Free and Open-Source Software Cloud Computing Platform
2016, The mobile-edge computing initiative
2016, Nest IoT Devices
2016, Looking Beyond the Internet
2014, Network Functions Virtualization (NFV) Introductory White Paper Virtualization Requirements
2016, Oculus Rift Helmet Next Generation Virtual Reality
2014, Software-Defined Networking The New Norm for Networks White Paper
2010, CEO to Shareholders 50 Billion Connections 2020
2015, Northbound Interface Working Group Charter
2015, Draft Deliverable of Network Softwarization for IMT-2020 Networks IMT-I-096r1
2014, Northbound Interface—Wikipedia the Free Encyclopedia

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Authors: Pan, J., & McElhannon, J.
Affiliations: University of Missouri–St. Louis (US)
ORCID: Pan, Jianli
Venue: IEEE Internet of Things Journal
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 2018-02
Volume: 5
Issue: 1
Pages: 439-449
ISSN: 2327-4662 (ISSN-L)
DOI: 10.1109/jiot.2017.2767608
OpenAlex: W2766401293
Cited by: 868
References: 17
Citations by year: 2026: 47 · 2025: 89 · 2024: 114 · 2023: 104 · 2022: 105 · 2021: 145 · 2020: 143 · 2019: 86 · 2018: 34
FWCI: 48.10
Type: journal article
Language: en
Open access: closed
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations: IEEE Internet of Things Journal (publishedVersion)
Funders: National Security Agency (H98230-17-1-0393, H98230-17-1-0352)
University of Missouri System Research Board Award
Topics: Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
Keywords: edge-cloud computing, edge computing, Internet of Things, low latency, network function virtualization, software-defined networking, IoT applications, resource-constrained edge devices

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Future Edge Cloud and Edge Computing for Internet of Things Applications

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