Energy-Efficient Provisioning for Service Function Chains to Support Delay-Sensitive Applications in Network Function Virtualization

Sun, G; Zhou, R; Sun, J; Yu, H; Vasilakos, AV

Energy-Efficient Provisioning for Service Function Chains to Support Delay-Sensitive Applications in Network Function Virtualization

Sun, G Zhou, R Sun, J Yu, H Vasilakos, AV

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Internet of Things Journal, 2020, 7, (7), pp. 6116-6131
Issue Date:: 2020-07-01

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Field	Value	Language
dc.contributor.author	Sun, G
dc.contributor.author	Zhou, R
dc.contributor.author	Sun, J
dc.contributor.author	Yu, H
dc.contributor.author	Vasilakos, AV
dc.date.accessioned	2021-01-10T22:47:37Z
dc.date.available	2021-01-10T22:47:37Z
dc.date.issued	2020-07-01
dc.identifier.citation	IEEE Internet of Things Journal, 2020, 7, (7), pp. 6116-6131
dc.identifier.issn	2327-4662
dc.identifier.issn	2327-4662
dc.identifier.uri	http://hdl.handle.net/10453/145250
dc.description.abstract	© 2014 IEEE. The efficient deployment of virtual network functions (VNFs) for network service provisioning is key for achieving network function virtualization (NFV); however, most existing studies address only offline or one-off deployments of service function chains (SFCs) while neglecting the dynamic (i.e., online) deployment and expansion requirements. In particular, many methods of energy/resource cost reduction are achieved by merging VNFs. However, the energy waste and device wear for large-scale collections of servers (e.g., cloud networks and data centers) caused by sporadic request updating are ignored. To solve these problems, we propose an energy-aware routing and adaptive delayed shutdown (EAR-ADS) algorithm for dynamic SFC deployment, which includes the following features: 1) energy-aware routing (EAR): by considering a practical deployment environment, a flexible solution is developed based on reusing open servers and selecting paths with the aims of balancing energy and resources and minimizing the total cost and 2) adaptive delayed shutdown (ADS): the delayed shutdown time of the servers can be flexibly adjusted in accordance with the usage of each device in each time slot, thus eliminating the no-load wait time of the servers and frequent on/off switching. Therefore, the EAR-ADS can achieve dual-energy savings by both decreasing the number of open servers and reducing the idle/switching energy consumption of these servers. The simulation results show that EAR-ADS not only minimizes the cost of energy and resources but also achieves an excellent success rate and stability. Moreover, EAR-ADS is efficient compared with an improved Markov algorithm (SAMA), reducing the average deployment time by more than a factor of 40.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE Internet of Things Journal
dc.relation.isbasedon	10.1109/JIOT.2020.2970995
dc.rights	info:eu-repo/semantics/closedAccess
dc.rights	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.subject	0805 Distributed Computing, 1005 Communications Technologies
dc.title	Energy-Efficient Provisioning for Service Function Chains to Support Delay-Sensitive Applications in Network Function Virtualization
dc.type	Journal Article
utslib.citation.volume	7
utslib.for	0805 Distributed Computing
utslib.for	1005 Communications Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2021-01-10T22:47:16Z
pubs.issue	7
pubs.publication-status	Published
pubs.volume	7
utslib.citation.issue	7

Abstract:

© 2014 IEEE. The efficient deployment of virtual network functions (VNFs) for network service provisioning is key for achieving network function virtualization (NFV); however, most existing studies address only offline or one-off deployments of service function chains (SFCs) while neglecting the dynamic (i.e., online) deployment and expansion requirements. In particular, many methods of energy/resource cost reduction are achieved by merging VNFs. However, the energy waste and device wear for large-scale collections of servers (e.g., cloud networks and data centers) caused by sporadic request updating are ignored. To solve these problems, we propose an energy-aware routing and adaptive delayed shutdown (EAR-ADS) algorithm for dynamic SFC deployment, which includes the following features: 1) energy-aware routing (EAR): by considering a practical deployment environment, a flexible solution is developed based on reusing open servers and selecting paths with the aims of balancing energy and resources and minimizing the total cost and 2) adaptive delayed shutdown (ADS): the delayed shutdown time of the servers can be flexibly adjusted in accordance with the usage of each device in each time slot, thus eliminating the no-load wait time of the servers and frequent on/off switching. Therefore, the EAR-ADS can achieve dual-energy savings by both decreasing the number of open servers and reducing the idle/switching energy consumption of these servers. The simulation results show that EAR-ADS not only minimizes the cost of energy and resources but also achieves an excellent success rate and stability. Moreover, EAR-ADS is efficient compared with an improved Markov algorithm (SAMA), reducing the average deployment time by more than a factor of 40.

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http://hdl.handle.net/10453/145250