TY - JOUR
T1 - Edge-Computing-Enabled Smart Cities
T2 - A Comprehensive Survey
AU - Khan, Latif U.
AU - Yaqoob, Ibrar
AU - Tran, Nguyen H.
AU - Kazmi, S. M.Ahsan
AU - Dang, Tri Nguyen
AU - Hong, Choong Seon
N1 - Funding Information:
Manuscript received November 20, 2019; revised February 17, 2020; accepted March 27, 2020. Date of publication April 10, 2020; date of current version October 9, 2020. This work was supported in part by the Institute of Information and Communications Technology Planning and Evaluation (IITP) grant funded by the Korea Government [Ministry of Science and ICT (MSIT), Evolvable Deep Learning Model Generation Platform for Edge Computing] under Grant 2019-0-01287, and in part by MSIT, South Korea, through the Grand Information Technology Research Center Support Program supervised by IITP under Grant IITP-2020-2015-0-00742. (Corresponding author: Choong Seon Hong.) Latif U. Khan, Ibrar Yaqoob, Tri Nguyen Dang, and Choong Seon Hong are with the Department of Computer Science and Engineering, Kyung Hee University, Yongin 17104, South Korea (e-mail: [email protected]).
Funding Information:
C. WATCH The Wide Smart Safe, Robust and Resilient Smart Cities Application Using Fog Computing (WATCH) project is funded by INNOVATE U.K. [189]. It was started on November 1, 2017 and is expected to be completed by 2020. The lead participants of this project are Future Intelligence Ltd. London, and London South Bank University, U.K. The goal of this project is to exploit novel micro data center and telecommunication nodes to provide joint storage resources, local processing, and networking to enable support for user applications in smart cities. Furthermore, they will utilize SDN and network function virtualization (NFV) to enable the formation of interconnected devices islands. This resulted in fogs, which are actually small-scale clouds at the network edge (i.e., edge computing). The main objective of this project is the improvement of smart surveillance by leveraging edge computing.
Publisher Copyright:
© 2014 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - Recent years have disclosed a remarkable proliferation of compute-intensive applications in smart cities. Such applications continuously generate enormous amounts of data which demand strict latency-aware computational processing capabilities. Although edge computing is an appealing technology to compensate for stringent latency-related issues, its deployment engenders new challenges. In this article, we highlight the role of edge computing in realizing the vision of smart cities. First, we analyze the evolution of edge computing paradigms. Subsequently, we critically review the state-of-the-art literature focusing on edge computing applications in smart cities. Later, we categorize and classify the literature by devising a comprehensive and meticulous taxonomy. Furthermore, we identify and discuss key requirements, and enumerate recently reported synergies of edge computing-enabled smart cities. Finally, several indispensable open challenges along with their causes and guidelines are discussed, serving as future research directions.
AB - Recent years have disclosed a remarkable proliferation of compute-intensive applications in smart cities. Such applications continuously generate enormous amounts of data which demand strict latency-aware computational processing capabilities. Although edge computing is an appealing technology to compensate for stringent latency-related issues, its deployment engenders new challenges. In this article, we highlight the role of edge computing in realizing the vision of smart cities. First, we analyze the evolution of edge computing paradigms. Subsequently, we critically review the state-of-the-art literature focusing on edge computing applications in smart cities. Later, we categorize and classify the literature by devising a comprehensive and meticulous taxonomy. Furthermore, we identify and discuss key requirements, and enumerate recently reported synergies of edge computing-enabled smart cities. Finally, several indispensable open challenges along with their causes and guidelines are discussed, serving as future research directions.
KW - Cloudlet
KW - fog computing
KW - Internet of Things (IoT)
KW - micro data centers
KW - mobile cloud computing (MCC)
KW - mobile-edge computing
KW - smart cities
UR - http://www.scopus.com/inward/record.url?scp=85087819719&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2020.2987070
DO - 10.1109/JIOT.2020.2987070
M3 - Article
AN - SCOPUS:85087819719
SN - 2327-4662
VL - 7
SP - 10200
EP - 10232
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 10
M1 - 9063670
ER -
