An SMDP-Based service function allocation scheme for mobile edge clouds

Li, G; Feng, B; Zhou, H; Yu, S

An SMDP-Based service function allocation scheme for mobile edge clouds

Li, G Feng, B Zhou, H Yu, S

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Communications, 2018, 2018-May
Issue Date:: 2018-07-27

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Field	Value	Language
dc.contributor.author	Li, G	en_US
dc.contributor.author	Feng, B	en_US
dc.contributor.author	Zhou, H	en_US
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743	en_US
dc.date.issued	2018-07-27	en_US
dc.identifier.citation	IEEE International Conference on Communications, 2018, 2018-May	en_US
dc.identifier.isbn	9781538631805	en_US
dc.identifier.issn	1550-3607	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133165
dc.description.abstract	© 2018 IEEE. With the increasing global mobile traffic, there is a trend to deploy network services at mobile edge clouds. Benefiting from the techniques of Network Function Virtualization and Software-Defined Networking, service function chains are enabled to compose a series of required network functions dynamically. As a consequence, most of common-used and IT-based mobile network services can be deployed at MEC cloud networks under the 5G context, remarkably reducing user latency and network traffic. However, as resources in cloud networks are limited, it is challenging to promote the system utilization with guaranteed user experience. Thus, in this paper, we formulate the allocation problem of service functions in MECs as an Semi-Markov Decision Process model and present a value iteration algorithm to find the optimized solution, aiming to increase request acceptance rate. Additionally, we discuss the parameter settings of the proposed scheme under different cases to find higher rewards.	en_US
dc.relation.ispartof	IEEE International Conference on Communications	en_US
dc.relation.isbasedon	10.1109/ICC.2018.8422332	en_US
dc.title	An SMDP-Based service function allocation scheme for mobile edge clouds	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2018-May	en_US
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2018-May	en_US

Abstract:

© 2018 IEEE. With the increasing global mobile traffic, there is a trend to deploy network services at mobile edge clouds. Benefiting from the techniques of Network Function Virtualization and Software-Defined Networking, service function chains are enabled to compose a series of required network functions dynamically. As a consequence, most of common-used and IT-based mobile network services can be deployed at MEC cloud networks under the 5G context, remarkably reducing user latency and network traffic. However, as resources in cloud networks are limited, it is challenging to promote the system utilization with guaranteed user experience. Thus, in this paper, we formulate the allocation problem of service functions in MECs as an Semi-Markov Decision Process model and present a value iteration algorithm to find the optimized solution, aiming to increase request acceptance rate. Additionally, we discuss the parameter settings of the proposed scheme under different cases to find higher rewards.

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http://hdl.handle.net/10453/133165