A taxonomy of load balancing algorithms and approaches in fog computing: a survey

被引:13
作者
Ebneyousef, Sepideh [1 ]
Shirmarz, Alireza [1 ]
机构
[1] Ale Taha Inst Higher Educ, Dept Comp & Elect Engn, Tehran, Iran
来源
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2023年 / 26卷 / 05期
关键词
Cloud computing; Fog computing; Edge computing; Load balancing; Performance; Quality of Service; Quality of Experience; ENERGY;
D O I
10.1007/s10586-023-03982-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
These days, cloud computing usage has been increasing with the rapid growth of Internet coverage all over the world to serve as a pay-per-use model using shared computing resources. Internet of Things (IoT) is a growing technology which is used in different applications and it needs cloud computing however the distance between cloud computing resources and the end system in IoT can cause a delay which is intolerable for delay-sensitive applications. Fog computing is a computing resource between cloud computing and end system to reduce the delay for the delay-sensitive applications in IoT. Therefore, load balancing functionality is a significant role to provide the required quality of service (QoS), quality of experience (QoE), and performance. Load balancing can be done based on response time, throughput, energy consumption, and utilization metrics. In this paper, the papers published in Elsevier, ACM, IEEE, Springer and Wiley between 2018 and 2022 have been examined to extract the load-balancing algorithms, system architecture, tools and applications, advantages and disadvantages. This review is useful for those working on load-balancing performance improvement.
引用
收藏
页码:3187 / 3208
页数:22
相关论文
共 44 条
[1]  
Abbasi SH., 2019, LECT NOTE DATA ENG, DOI [10.1007/978-3-030-02613-4, DOI 10.1007/978-3-030-02613-4]
[2]   Improving fog computing performance via Fog-2-Fog collaboration [J].
Al-khafajiy, Mohammed ;
Baker, Thar ;
Al-Libawy, Hilal ;
Maamar, Zakaria ;
Aloqaily, Moayad ;
Jararweh, Yaser .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 100 :266-280
[3]  
Alzeyadi A, 2019, 2019 9TH INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE 2019), P104, DOI [10.1109/ICCKE48569.2019.8964946, 10.1109/iccke48569.2019.8964946]
[4]  
[Anonymous], PERFORMANCE EVALUATI
[5]  
Applications W., 2021, J GRID COMPUT, DOI [10.1007/s10723-021-09584-w, DOI 10.1007/S10723-021-09584-W]
[6]   Fog Based Architecture and Load Balancing Methodology for Health Monitoring Systems [J].
Asghar, Anam ;
Abbas, Assad ;
Khattak, Hasan Ali ;
Khan, Samee U. .
IEEE ACCESS, 2021, 9 :96189-96200
[7]   Latency Minimization with Optimum Workload Distribution and Power Control for Fog Computing [J].
Atapattu, Saman ;
Weeraddana, Chathuranga ;
Ding, Minhua ;
Inaltekin, Hazer ;
Evans, Jamie .
2020 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2020,
[8]  
Baek JY, 2019, IEEE WCNC
[9]   Load balancing between fog and cloud in fog of things based platforms through software-defined networking [J].
Batista, Ernando ;
Figueiredo, Gustavo ;
Prazeres, Cassio .
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2022, 34 (09) :7111-7125
[10]   Randomized Load Balancing under Loosely Correlated State Information in Fog Computing [J].
Beraldi, Roberto ;
Canali, Claudia ;
Lancellotti, Riccardo ;
Mattia, Gabriele Proietti .
PROCEEDINGS OF THE 23RD INTERNATIONAL ACM CONFERENCE ON MODELING, ANALYSIS AND SIMULATION OF WIRELESS AND MOBILE SYSTEMS, MSWIM 2020, 2020, :123-127