research-article

Anticipatory Admission Control and Resource Allocation for Media Streaming in Mobile Networks

Authors:

Ilaria Malanchini,

Joerg WidmerAuthors Info & Claims

MSWiM '15: Proceedings of the 18th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

Pages 255 - 262

https://doi.org/10.1145/2811587.2811604

Published: 02 November 2015 Publication History

Abstract

The exponential growth of media streaming traffic will have a strong impact on the bandwidth consumption of the future wireless infrastructure. One key challenge is to deliver services taking into account the stringent requirements of mobile video streaming, e.g., the users' expected Quality-of-Service. Admission control and resource allocation can strongly benefit from the use of anticipatory information such as the prediction of future user's demand and expected channel gain. In this paper, we use this information to formulate an optimal admission control scheme that maximizes the number of accepted users into the system with the constraint that not only the current but also the expected demand of all users must be satisfied. Together with the optimal set of accepted users, the optimal resource scheduling is derived. In order to have a solution that can be computed in a reasonable time, we propose a low complexity heuristic. Numerical results show the performance of the proposed scheme with respect to the state of the art.

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Cited By

Huang XZhao SGao XShao ZQian HYang Y(2022)Online User-AP Association With Predictive Scheduling in Wireless Caching NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2020.303687621:6(2116-2129)Online publication date: 1-Jun-2022
https://doi.org/10.1109/TMC.2020.3036876
Kamboj PPal S(2021)Software-Defined Networking in Data CentersSoftware Defined Internet of Everything10.1007/978-3-030-89328-6_10(177-203)Online publication date: 8-Oct-2021
https://doi.org/10.1007/978-3-030-89328-6_10
Malanchini ISuryaprakash V(2018)Minimizing the Impact of Prediction Errors during Anticipatory Resource Allocation2018 IEEE 87th Vehicular Technology Conference (VTC Spring)10.1109/VTCSpring.2018.8417684(1-6)Online publication date: Jun-2018
https://doi.org/10.1109/VTCSpring.2018.8417684
Show More Cited By

Index Terms

Anticipatory Admission Control and Resource Allocation for Media Streaming in Mobile Networks
1. Networks
  1. Network services
    1. Network management

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Published In

cover image ACM Conferences

MSWiM '15: Proceedings of the 18th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

November 2015

358 pages

ISBN:9781450337625

DOI:10.1145/2811587

General Chairs:
J. J. Garcia-Luna-Aceves
University of California, USA
,
Graciela Romén Alonso
Universidad Autónoma Metropolitana, Mexico
,
Program Chairs:
Falko Dressler
University of Paderborn, Germany
,
Brahim Bensaou
Hong Kong University of Science and Technology, Hong Kong
,
Antonio F. Loureiro
Federal University of Minas Gerais, Brazil

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSIM: ACM Special Interest Group on Simulation and Modeling

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 November 2015

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Funding Sources

European Union H2020-ICT
Alcatel-Lucent Bell Labs
Spanish Ministry of Economy and Competitiveness
Madrid Regional Government

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MSWiM'15

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SIGSIM

MSWiM'15: 18th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

November 2 - 6, 2015

Cancun, Mexico

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MSWiM '15 Paper Acceptance Rate 34 of 142 submissions, 24%;

Overall Acceptance Rate 398 of 1,577 submissions, 25%

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Cited By

Huang XZhao SGao XShao ZQian HYang Y(2022)Online User-AP Association With Predictive Scheduling in Wireless Caching NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2020.303687621:6(2116-2129)Online publication date: 1-Jun-2022
https://doi.org/10.1109/TMC.2020.3036876
Kamboj PPal S(2021)Software-Defined Networking in Data CentersSoftware Defined Internet of Everything10.1007/978-3-030-89328-6_10(177-203)Online publication date: 8-Oct-2021
https://doi.org/10.1007/978-3-030-89328-6_10
Malanchini ISuryaprakash V(2018)Minimizing the Impact of Prediction Errors during Anticipatory Resource Allocation2018 IEEE 87th Vehicular Technology Conference (VTC Spring)10.1109/VTCSpring.2018.8417684(1-6)Online publication date: Jun-2018
https://doi.org/10.1109/VTCSpring.2018.8417684
Bui NWidmer J(2018)Data-Driven Evaluation of Anticipatory Networking in LTE NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2018.280975017:10(2252-2265)Online publication date: 1-Oct-2018
https://doi.org/10.1109/TMC.2018.2809750
Bhaumik SChakraborty S(2018)Hierarchical Two Dimensional Queuing: A Scalable Approach for Traffic Shaping using Software Defined Networking2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft)10.1109/NETSOFT.2018.8460072(150-158)Online publication date: Jun-2018
https://doi.org/10.1109/NETSOFT.2018.8460072
Bui NWidmer J(2017)Data-Driven Evaluation of Anticipatory Networking in LTE Networks2017 29th International Teletraffic Congress (ITC 29)10.23919/ITC.2017.8064338(46-54)Online publication date: Sep-2017
https://doi.org/10.23919/ITC.2017.8064338
Bui NMichelinakis FWidmer J(2017)Fine-grained LTE radio link estimation for mobile phones2017 IEEE 18th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM)10.1109/WoWMoM.2017.7974286(1-9)Online publication date: Jun-2017
https://doi.org/10.1109/WoWMoM.2017.7974286
Bui NCesana MHosseini SLiao QMalanchini IWidmer J(2017)A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization TechniquesIEEE Communications Surveys & Tutorials10.1109/COMST.2017.269414019:3(1790-1821)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1109/COMST.2017.2694140
Fazio PDe Rango FTropea M(2017)Prediction and QoS Enhancement in New Generation Cellular Networks With Mobile Hosts: A Survey on Different Protocols and Conventional/Unconventional ApproachesIEEE Communications Surveys & Tutorials10.1109/COMST.2017.268477819:3(1822-1841)Online publication date: Nov-2018
https://doi.org/10.1109/COMST.2017.2684778
Abbes YNajeh SBesbes H(2016)QoS-aware admission control formalism for OFDMA-based network2016 Wireless Days (WD)10.1109/WD.2016.7461511(1-3)Online publication date: Mar-2016
https://doi.org/10.1109/WD.2016.7461511
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