Configurable Cost-Quality Optimization of Cloud-based VoIP

Tchernykh, Andrei; Cortes-Mendoza, Jorge M.; Bychkov, Igor; Feoktistov, Alexander; Didelot, Loic; Bouvry, Pascal; Radchenko, Gleb; Borodulin, Kirill

doi:10.1016/j.jpdc.2018.07.001

Reference : Configurable Cost-Quality Optimization of Cloud-based VoIP


	Document type :	Scientific journals : Article
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/42079

Title :	Configurable Cost-Quality Optimization of Cloud-based VoIP
Language :	English
Author, co-author :	Tchernykh, Andrei []
	Cortes-Mendoza, Jorge M. []
	Bychkov, Igor []
	Feoktistov, Alexander []
	Didelot, Loic []
	Bouvry, Pascal [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Radchenko, Gleb []
	Borodulin, Kirill []
Publication date :	2019
Journal title :	Journal of Parallel and Distributed Computing
Publisher :	Elsevier
Volume :	133
Pages :	319-336
Peer reviewed :	Yes (verified by ORBi^lu)
Audience :	International
ISSN :	0743-7315
e-ISSN :	1096-0848
City :	Atlanta
Country :	GE
Keywords :	[en] call allocation ; scheduling ; voip
Abstract :	[en] In this paper, we formulate configurable cloud-based VoIP call allocation problem as a special case of dynamic multi-objective bin-packing. We consider voice quality influenced by CPU stress, cost contributed by the number of billing hours for Virtual Machines (VMs) provisioning, and calls placed on hold due to under-provisioning resources. We distinguish call allocation strategies by the type and amount of information used for allocation: knowledge-free, utilization-aware, rental-aware, and loadaware. We propose and study a variety of strategies with static and dynamic policies of VM provisioning. To study realistic scenarios, we consider startup delays for VM provisioning, and three configurable parameters: utilization threshold, rental threshold, and prediction interval. They can be configured and dynamically adapted to cope with different objective preferences, workloads, and cloud properties. We conduct comprehensive simulation on the real workload of the MIXvoip company and show that the proposed strategies outperform ones currently in-use.
Permalink :	http://hdl.handle.net/10993/42079
DOI :	10.1016/j.jpdc.2018.07.001

File(s) associated to this reference

Fulltext file(s):

	File	Commentary	Version	Size	Access
Limited access	JPDCPDCO_SI_2018-draft.pdf		Author preprint	1.5 MB	Request a copy

All documents in ORBi^lu are protected by a user license.

University of Luxembourg Library | Feedback | Legal notices