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Future Edge Cloud and Edge Computing for Internet of Things Applications
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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“In smart city surveillance systems, edge nodes are typically positioned between the monitoring devices and the cloud server [24].”
From A Survey of Video Surveillance Systems in Smart City (2023) · cites this paper as [24]
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Cites
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
The case for vm-based cloudlets in mobile computing
Satyanarayanan, M., Bahl, P., Caceres, R., & Davies, N. (2009) · IEEE Pervasive Computing · doi:10.1109/mprv.2009.82 · Cited by 3,660
Fog and IoT: An Overview of Research Opportunities
Chiang, M., & Zhang, T. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2584538 · Cited by 2,362
MAUI: making smartphones last longer with code offload
Cuervo, E., Balasubramanian, A., Cho, D.-K., Wolman, A., Saroiu, S., Chandra, R., & Bahl, P. (2010) · Proceedings of the 8th international conference on Mobile systems, applications, and services · doi:10.1145/1814433.1814441 · Cited by 2,281
(2011) · doi:10.1145/1966445.1966473 · Cited by 1,870
A survey on mobile edge computing
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
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
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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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Metadata
- Authors
- Pan, J., & McElhannon, J.
- Affiliations
- University of Missouri–St. Louis (US)
- ORCID
- Pan, Jianli
- Venue
- IEEE Internet of Things Journal
- Published
- 2018-02
- Volume
- 5
- Issue
- 1
- Pages
- 439-449
- ISSN
- 2327-4662 (ISSN-L)
- 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
- 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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