Energy aware cloud-edge service placement approaches in the Internet of Things communications

被引:10
作者
Heng, Liang [1 ]
Yin, Guofu [1 ]
Zhao, Xiufen [1 ]
机构
[1] Sichuan Univ, Sch Mech Engn, Chengdu 610065, Peoples R China
关键词
cloud-edge computing; energy; IoT; quality of service; service placement; ALGORITHMS; OPTIMIZATION;
D O I
10.1002/dac.4899
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In recent years, applying Internet of Things (IoT) applications has significantly increased to facilitate and improve quality of human life activities in various fields such as healthcare, education, industry, economics, etc. The energy aware cloud-edge computing paradigm has developed as a hybrid computing solution to provide IoT applications using available cloud service providers and fog nodes for the smart devices and mobile applications. Since the IoT applications are developed in the form of several IoT services with various quality of service (QoS) metrics which can deploy on the cloud-edge providers with different resource capabilities, finding an efficient placement solution as one of challenging topics to be measured for IoT applications. The service placement issue arranges IoT applications on the cloud-edge providers with various capabilities of atomic services though sufficient different QoS factors to support service level agreement (SLA) contracts. This paper presents a technical analysis on the cloud-edge service placement approaches in IoT systems. The key point of this technical analysis is to identify substantial studies in the service placement approaches which need additional consideration to progress more efficient and effective placement strategies in IoT environments. In addition, a side-by-side taxonomy is proposed to categorize the relevant studies on cloud-edge service placement approaches and algorithms. A statistical and technical analysis of reviewed existing approaches is provided, and evaluation factors and attributes are discussed. Finally, open issues and forthcoming challenges of service placement approaches are presented.
引用
收藏
页数:23
相关论文
共 82 条
[31]  
Ouyang T, 2019, IEEE INFOCOM SER, P1468, DOI [10.1109/INFOCOM.2019.8737560, 10.1109/infocom.2019.8737560]
[32]   Follow Me at the Edge: Mobility-Aware Dynamic Service Placement for Mobile Edge Computing [J].
Ouyang, Tao ;
Zhou, Zhi ;
Chen, Xu .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2018, 36 (10) :2333-2345
[33]  
Pasteris Stephen, 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, P514, DOI 10.1109/INFOCOM.2019.8737449
[34]  
Pi L, 2018, IEEE CONF COMPUT
[35]   Design and Implementation of a Fast Sliding-Mode Speed Controller With Disturbance Compensation for SPMSM System [J].
Qu, Shaocheng ;
Xu, Wenjun ;
Zhao, Jinghong ;
Zhang, Hongrui .
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2021, 7 (04) :2611-2622
[36]  
Minh QT, 2017, 2017 4TH NAFOSTED CONFERENCE ON INFORMATION AND COMPUTER SCIENCE (NICS), P291, DOI 10.1109/NAFOSTED.2017.8108080
[37]  
Rachkidi E, 2015, 2015 17TH INTERNATIONAL CONFERENCE ON E-HEALTH NETWORKING, APPLICATION & SERVICES (HEALTHCOM), P627, DOI 10.1109/HealthCom.2015.7454580
[38]  
Rasheed A., 2010, P 8 INT C FRONT INF
[39]   A Survey on Replica Server Placement Algorithms for Content Delivery Networks [J].
Sahoo, Jagruti ;
Salahuddin, Mohammad A. ;
Glitho, Roch ;
Elbiaze, Halima ;
Ajib, Wessam .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2017, 19 (02) :1002-1026
[40]   An Overview of Service Placement Problem in Fog and Edge Computing [J].
Salaht, Farah Ait ;
Desprez, Frederic ;
Lebre, Adrien .
ACM COMPUTING SURVEYS, 2020, 53 (03)