Affinity-Based Resource and Task Allocation in Edge Computing Systems

Wenbing Zou; Xiulei Liu; Shoulu Hou; Ye Zhang; Lin Miao; Yi Gong; Ning Li

doi:10.1109/TrustCom60117.2023.00162

Affinity-Based Resource and Task Allocation in Edge Computing Systems

Wenbing Zou, Xiulei Liu, Shoulu Hou, Ye Zhang, Lin Miao, Yi Gong, Ning Li

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Edge computing has become a promising technology to mitigate the latency of various cloud services. Task scheduling in edge computing is challenging due to the heterogeneous devices and multiple tasks. This paper proposes an affinity-based scheduling algorithm to solve the multi-task scheduling problem with heterogeneous computing resources under edge computing. The algorithm uses a centralized scheduling strategy that takes into account the overall matching between intelligent computing tasks and heterogeneous resources from two aspects: resource affinity and system load balancing. It can adjust the weights among these aspects to meet different application requirements. The results show that the proposed algorithm can reduce the average response time by at least 10% and has a significant advantage regarding the system running time compared to the other comparative methods.

Original language	English
Title of host publication	Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023
Editors	Jia Hu, Geyong Min, Guojun Wang
Publisher	Institute of Electrical and Electronics Engineers
Pages	1187-1195
Number of pages	9
ISBN (Electronic)	9798350381993
DOIs	https://doi.org/10.1109/TrustCom60117.2023.00162
State	Published - 1 Jan 2023
Externally published	Yes
Event	22nd IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2023 - Exeter, United Kingdom Duration: 1 Nov 2023 → 3 Nov 2023

Publication series

Name	Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023

Conference

Conference	22nd IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2023
Country/Territory	United Kingdom
City	Exeter
Period	1/11/23 → 3/11/23

Keywords

affinity
computing tasks
edge computing
heterogeneous resources
matching

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Hardware and Architecture
Information Systems and Management
Safety, Risk, Reliability and Quality

Access to Document

10.1109/TrustCom60117.2023.00162

Cite this

Zou, W., Liu, X., Hou, S., Zhang, Y., Miao, L., Gong, Y., & Li, N. (2023). Affinity-Based Resource and Task Allocation in Edge Computing Systems. In J. Hu, G. Min, & G. Wang (Eds.), Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023 (pp. 1187-1195). (Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/TrustCom60117.2023.00162

Zou, Wenbing ; Liu, Xiulei ; Hou, Shoulu et al. / Affinity-Based Resource and Task Allocation in Edge Computing Systems. Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023. editor / Jia Hu ; Geyong Min ; Guojun Wang. Institute of Electrical and Electronics Engineers, 2023. pp. 1187-1195 (Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023).

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title = "Affinity-Based Resource and Task Allocation in Edge Computing Systems",

abstract = "Edge computing has become a promising technology to mitigate the latency of various cloud services. Task scheduling in edge computing is challenging due to the heterogeneous devices and multiple tasks. This paper proposes an affinity-based scheduling algorithm to solve the multi-task scheduling problem with heterogeneous computing resources under edge computing. The algorithm uses a centralized scheduling strategy that takes into account the overall matching between intelligent computing tasks and heterogeneous resources from two aspects: resource affinity and system load balancing. It can adjust the weights among these aspects to meet different application requirements. The results show that the proposed algorithm can reduce the average response time by at least 10% and has a significant advantage regarding the system running time compared to the other comparative methods.",

keywords = "affinity, computing tasks, edge computing, heterogeneous resources, matching",

author = "Wenbing Zou and Xiulei Liu and Shoulu Hou and Ye Zhang and Lin Miao and Yi Gong and Ning Li",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 22nd IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2023 ; Conference date: 01-11-2023 Through 03-11-2023",

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doi = "10.1109/TrustCom60117.2023.00162",

language = "English",

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editor = "Jia Hu and Geyong Min and Guojun Wang",

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Zou, W, Liu, X, Hou, S, Zhang, Y, Miao, L, Gong, Y & Li, N 2023, Affinity-Based Resource and Task Allocation in Edge Computing Systems. in J Hu, G Min & G Wang (eds), Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023. Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023, Institute of Electrical and Electronics Engineers, pp. 1187-1195, 22nd IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2023, Exeter, United Kingdom, 1/11/23. https://doi.org/10.1109/TrustCom60117.2023.00162

Affinity-Based Resource and Task Allocation in Edge Computing Systems. / Zou, Wenbing; Liu, Xiulei; Hou, Shoulu et al.
Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023. ed. / Jia Hu; Geyong Min; Guojun Wang. Institute of Electrical and Electronics Engineers, 2023. p. 1187-1195 (Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Affinity-Based Resource and Task Allocation in Edge Computing Systems

AU - Zou, Wenbing

AU - Liu, Xiulei

AU - Hou, Shoulu

AU - Zhang, Ye

AU - Miao, Lin

AU - Gong, Yi

AU - Li, Ning

PY - 2023/1/1

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N2 - Edge computing has become a promising technology to mitigate the latency of various cloud services. Task scheduling in edge computing is challenging due to the heterogeneous devices and multiple tasks. This paper proposes an affinity-based scheduling algorithm to solve the multi-task scheduling problem with heterogeneous computing resources under edge computing. The algorithm uses a centralized scheduling strategy that takes into account the overall matching between intelligent computing tasks and heterogeneous resources from two aspects: resource affinity and system load balancing. It can adjust the weights among these aspects to meet different application requirements. The results show that the proposed algorithm can reduce the average response time by at least 10% and has a significant advantage regarding the system running time compared to the other comparative methods.

AB - Edge computing has become a promising technology to mitigate the latency of various cloud services. Task scheduling in edge computing is challenging due to the heterogeneous devices and multiple tasks. This paper proposes an affinity-based scheduling algorithm to solve the multi-task scheduling problem with heterogeneous computing resources under edge computing. The algorithm uses a centralized scheduling strategy that takes into account the overall matching between intelligent computing tasks and heterogeneous resources from two aspects: resource affinity and system load balancing. It can adjust the weights among these aspects to meet different application requirements. The results show that the proposed algorithm can reduce the average response time by at least 10% and has a significant advantage regarding the system running time compared to the other comparative methods.

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ER -

Zou W, Liu X, Hou S, Zhang Y, Miao L, Gong Y et al. Affinity-Based Resource and Task Allocation in Edge Computing Systems. In Hu J, Min G, Wang G, editors, Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023. Institute of Electrical and Electronics Engineers. 2023. p. 1187-1195. (Proceedings - 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom/BigDataSE/CSE/EUC/iSCI 2023). doi: 10.1109/TrustCom60117.2023.00162

Affinity-Based Resource and Task Allocation in Edge Computing Systems

Abstract

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Keywords

ASJC Scopus subject areas

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