Design, Resource Management, and Evaluation of Fog Computing Systems: A Survey

被引:97
作者
Martinez, Ismael [1 ]
Hafid, Abdelhakim Senhaji [1 ]
Jarray, Abdallah [2 ]
机构
[1] Univ Montreal, Dept Comp Sci & Operat Res, Montreal, PQ, Canada
[2] Univ Ottawa, Sch Elect Engn & Comp Sci, Ottawa, ON K1N 6N5, Canada
关键词
Cloud computing; Edge computing; Resource management; Servers; Internet of Things; Computational modeling; Tools; Fog computing; fog design and dimensioning; fog infrastructure evaluation; fog resource management; Internet of Things (IoT); simulation; survey; MOBILE-CLOUD; BIG DATA; ARCHITECTURE; INTERNET; EDGE; INFRASTRUCTURE; SIMULATION; FRAMEWORK; SELECTION; TOOLKIT;
D O I
10.1109/JIOT.2020.3022699
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A steady increase in Internet-of-Things (IoT) applications needing large-scale computation and long-term storage has lead to an overreliance on cloud computing. The resulting network congestion in the cloud, coupled with the distance of cloud data centers from IoT, contributes to unreliable end-to-end response delay. Fog computing has been introduced as an alternative to cloud, providing low-latency service by bringing processing and storage resources to the network edge. In this survey, we sequentially present the phases required in the implementation and realization of practical fog computing systems: 1) design and dimensioning of a fog infrastructure; 2) fog resource provisioning for IoT application use and IoT resource allocation to fog; 3) installation of fog frameworks for fog resource management; and 4) evaluation of fog infrastructure through simulation and emulation. Our focus is on determining the implementation aspects required to build a practical large-scale fog computing infrastructure to support the general IoT landscape.
引用
收藏
页码:2494 / 2516
页数:23
相关论文
共 50 条
[41]   A learning-based resource provisioning approach in the fog computing environment [J].
Etemadi, Masoumeh ;
Ghobaei-Arani, Mostafa ;
Shahidinejad, Ali .
JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, 2021, 33 (06) :1033-1056
[42]   Evaluation of fog application placement algorithms: a survey [J].
Smolka, Sven ;
Mann, Zoltan Adam .
COMPUTING, 2022, 104 (06) :1397-1423
[43]   Fog Computing Algorithms: A Survey and Research Opportunities [J].
Malukani, Shaifali P. ;
Bhensdadia, C. K. .
APPLIED COMPUTER SYSTEMS, 2021, 26 (02) :139-149
[44]   Enhancement of QoS for Fog Computing Model Aspect of Robust Resource Management [J].
Jana, Gopal Chandra ;
Banerjee, Sudatta .
2017 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING, INSTRUMENTATION AND CONTROL TECHNOLOGIES (ICICICT), 2017, :1462-1466
[45]   Resource Management Approaches in Fog Computing: a Comprehensive Review [J].
Mostafa Ghobaei-Arani ;
Alireza Souri ;
Ali A. Rahmanian .
Journal of Grid Computing, 2020, 18 :1-42
[46]   A Novel Bio-Inspired Hybrid Algorithm (NBIHA) for Efficient Resource Management in Fog Computing [J].
Rafique, Hina ;
Shah, Munam Ali ;
Islam, Saif Ul ;
Maqsood, Tahir ;
Khan, Suleman ;
Maple, Carsten .
IEEE ACCESS, 2019, 7 :115760-115773
[47]   Fog Computing Resource Optimization: A Review on Current Scenarios and Resource Management [J].
Dar, Ab Rashid ;
Ravindran, D. .
BAGHDAD SCIENCE JOURNAL, 2019, 16 (02) :419-427
[48]   Joint Resource Allocation for Device-to-Device Communication Assisted Fog Computing [J].
Yi, Changyan ;
Huang, Shiwei ;
Cai, Jun .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2021, 20 (03) :1076-1091
[49]   Context Aware Resource and Service Provisioning Management in Fog Computing Systems [J].
Pesic, Sasa ;
Tosic, Milenko ;
Ikovic, Ognjen ;
Ivanovic, Mirjana ;
Radovanovic, Milos ;
Boskovic, Dragan .
INTELLIGENT DISTRIBUTED COMPUTING XI, 2018, 737 :213-223
[50]   Vehicular Fog Computing: A Survey of Architectures, Resource Management, Challenges and Emerging Trends [J].
Husain, Mohammed Hassan ;
Ahmadi, Mahmood ;
Mardukhi, Farhad .
WIRELESS PERSONAL COMMUNICATIONS, 2024, 136 (04) :2243-2273