RoC prediction for Bi-objective cost-QoS optimization of cloud VoIP call allocations

J.M. Cortes-Mendoza; A. Tchernykh; G. Radchenko; A.Y. Drozdov; Suroegina Z.; Pavlyukova E.; Uzhinskaya L.

doi:10.1109/ICEnT.2017.32

RoC prediction for Bi-objective cost-QoS optimization of cloud VoIP call allocations

J.M. Cortes-Mendoza, A. Tchernykh, G. Radchenko, A.Y. Drozdov, Suroegina Z., Pavlyukova E., Uzhinskaya L.

Research output: Contribution to conference (No Proceedings) › Paper › peer-review

Abstract

In this paper, we present cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective problem is reasonable and representative for real installations and applications. We conduct comprehensive simulation on real data of sixty four strategies with dynamic prediction of the load. We show that our prediction rule that consider the number of Virtual Machines (VMs) running in the system improves the efficiency of traditional rate of change algorithm. It provides suitable quality of service and lower cost. Variations of VM startup time delays permit to evaluate the prediction rules under different scenarios and assess the robustness of all strategies. © 2017 IEEE.

Original language	English
Pages	119-123
Number of pages	5
DOIs	https://doi.org/10.1109/ICEnT.2017.32
Publication status	Published - 2017
Event	4th International Conference on Engineering and Telecommunication - Moscow, Russian Federation Duration: 25 Nov 2020 → …

Conference

Conference	4th International Conference on Engineering and Telecommunication
Abbreviated title	En and T 2017
Country/Territory	Russian Federation
City	Moscow
Period	25/11/20 → …

Keywords

bin packing
call allocation
cloud voice over IP
load prediction
quality of service
Costs
Forecasting
Internet telephony
Voice/data communication systems
Bin packing
Dynamic prediction
Load predictions
Prediction rules
QoS optimization
Scheduling strategies
Voice over IP
Quality of service

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10.1109/ICEnT.2017.32

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049257255&doi=10.1109%2fICEnT.2017.32&partnerID=40&md5=b0c792f450e31785d1b4b473a20770b2

Cite this

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title = "RoC prediction for Bi-objective cost-QoS optimization of cloud VoIP call allocations",

abstract = "In this paper, we present cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective problem is reasonable and representative for real installations and applications. We conduct comprehensive simulation on real data of sixty four strategies with dynamic prediction of the load. We show that our prediction rule that consider the number of Virtual Machines (VMs) running in the system improves the efficiency of traditional rate of change algorithm. It provides suitable quality of service and lower cost. Variations of VM startup time delays permit to evaluate the prediction rules under different scenarios and assess the robustness of all strategies. {\textcopyright} 2017 IEEE.",

keywords = "bin packing, call allocation, cloud voice over IP, load prediction, quality of service, Costs, Forecasting, Internet telephony, Voice/data communication systems, Bin packing, Dynamic prediction, Load predictions, Prediction rules, QoS optimization, Scheduling strategies, Voice over IP, Quality of service",

author = "J.M. Cortes-Mendoza and A. Tchernykh and G. Radchenko and A.Y. Drozdov and Suroegina Z. and Pavlyukova E. and Uzhinskaya L.",

note = "Conference code: 134065 Export Date: 27 August 2021 Correspondence Address: Tchernykh, A.; CICESE Research CenterMexico; email: chernykh@cicese.mx; 4th International Conference on Engineering and Telecommunication, En and T 2017 ; Conference date: 25-11-2020",

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doi = "10.1109/ICEnT.2017.32",

language = "English",

pages = "119--123",

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T1 - RoC prediction for Bi-objective cost-QoS optimization of cloud VoIP call allocations

AU - Cortes-Mendoza, J.M.

AU - Tchernykh, A.

AU - Radchenko, G.

AU - Drozdov, A.Y.

AU - Z., Suroegina

AU - E., Pavlyukova

AU - L., Uzhinskaya

N1 - Conference code: 134065 Export Date: 27 August 2021 Correspondence Address: Tchernykh, A.; CICESE Research CenterMexico; email: chernykh@cicese.mx

PY - 2017

Y1 - 2017

N2 - In this paper, we present cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective problem is reasonable and representative for real installations and applications. We conduct comprehensive simulation on real data of sixty four strategies with dynamic prediction of the load. We show that our prediction rule that consider the number of Virtual Machines (VMs) running in the system improves the efficiency of traditional rate of change algorithm. It provides suitable quality of service and lower cost. Variations of VM startup time delays permit to evaluate the prediction rules under different scenarios and assess the robustness of all strategies. © 2017 IEEE.

AB - In this paper, we present cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective problem is reasonable and representative for real installations and applications. We conduct comprehensive simulation on real data of sixty four strategies with dynamic prediction of the load. We show that our prediction rule that consider the number of Virtual Machines (VMs) running in the system improves the efficiency of traditional rate of change algorithm. It provides suitable quality of service and lower cost. Variations of VM startup time delays permit to evaluate the prediction rules under different scenarios and assess the robustness of all strategies. © 2017 IEEE.

KW - bin packing

KW - call allocation

KW - cloud voice over IP

KW - load prediction

KW - quality of service

KW - Costs

KW - Forecasting

KW - Internet telephony

KW - Voice/data communication systems

KW - Bin packing

KW - Dynamic prediction

KW - Load predictions

KW - Prediction rules

KW - QoS optimization

KW - Scheduling strategies

KW - Voice over IP

KW - Quality of service

U2 - 10.1109/ICEnT.2017.32

DO - 10.1109/ICEnT.2017.32

M3 - Paper

SP - 119

EP - 123

T2 - 4th International Conference on Engineering and Telecommunication

Y2 - 25 November 2020

ER -

RoC prediction for Bi-objective cost-QoS optimization of cloud VoIP call allocations

Abstract

Conference

Keywords

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