research-article

Cross-Layer Opportunistic Scheduling for Device-to-Device Video Multicast Services

Authors:

Xiangdong Wang,

Yiqiang ChenAuthors Info & Claims

ACM Transactions on Embedded Computing Systems (TECS), Volume 15, Issue 2

Article No.: 37, Pages 1 - 18

https://doi.org/10.1145/2856034

Published: 26 February 2016 Publication History

Abstract

In this article, we address the problem of how to make the wireless device-to-device (D2D) video multicast systems have better quality provision with consideration of internet-of-things (IoT) applications. We propose an opportunistic transmission and fair resource allocation framework, including joint application-layer and physical-layer transmission and optimization. First, we use a parallel subchannels structure by concatenating the Fountain codes and diversity-embedded space-time block codes to provide reliable and flexible transmission in heterogeneous circumstances. Second, we exploit the quality of heterogeneous user experience (quality of experience) metric under D2D video multicast systems, with consideration of various channel states, device capability, video content urgency, and the number of demanding users. Third, we formulate reliable multiple video streams broadcasting to heterogeneous devices as an aggregate maximum utility achieving problem, and we use opportunistic scheduling to select suitable users in each transmission interval to improve the broadcasting utility. Fourth, we use the utility fair scheme to guide rate allocation among multicontent video multicast. Extensive performance comparison and analysis are presented to demonstrate efficiency of the proposed solution.

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Cited By

Zhong YWang GHan TWu MGe X(2019)QoE and Cost for Wireless Networks With Mobility Under Spatio-Temporal TrafficIEEE Access10.1109/ACCESS.2019.29099487(47206-47220)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2909948
Lv CHuang RZhuang WWei XBao Q(2017)QoE prediction on imbalanced IPTV data based on multi-layer neural network2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)10.1109/IWCMC.2017.7986390(818-823)Online publication date: Jun-2017
https://doi.org/10.1109/IWCMC.2017.7986390
Gao YWei XZhuang WHuang RDiao M(2017)QoE prediction for IPTV based on BP_adaboost neural networks2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)10.1109/IWCMC.2017.7986258(32-37)Online publication date: Jun-2017
https://doi.org/10.1109/IWCMC.2017.7986258
Show More Cited By

Index Terms

Cross-Layer Opportunistic Scheduling for Device-to-Device Video Multicast Services
1. Information systems
  1. Information systems applications

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Published In

cover image ACM Transactions on Embedded Computing Systems

ACM Transactions on Embedded Computing Systems Volume 15, Issue 2

Special Issue on Innovative Design, Special Issue on MEMOCODE 2014 and Special Issue on M2M/IOT

May 2016

421 pages

ISSN:1539-9087

EISSN:1558-3465

DOI:10.1145/2888407

Editor:
Sandeep K. Shukla
Indian Institute of Technology, India

Issue’s Table of Contents

Copyright © 2016 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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Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 26 February 2016

Accepted: 01 December 2015

Revised: 01 November 2015

Received: 01 March 2015

Published in TECS Volume 15, Issue 2

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Cited By

Zhong YWang GHan TWu MGe X(2019)QoE and Cost for Wireless Networks With Mobility Under Spatio-Temporal TrafficIEEE Access10.1109/ACCESS.2019.29099487(47206-47220)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2909948
Lv CHuang RZhuang WWei XBao Q(2017)QoE prediction on imbalanced IPTV data based on multi-layer neural network2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)10.1109/IWCMC.2017.7986390(818-823)Online publication date: Jun-2017
https://doi.org/10.1109/IWCMC.2017.7986390
Gao YWei XZhuang WHuang RDiao M(2017)QoE prediction for IPTV based on BP_adaboost neural networks2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)10.1109/IWCMC.2017.7986258(32-37)Online publication date: Jun-2017
https://doi.org/10.1109/IWCMC.2017.7986258
Liu FLiu YWang JDeng WXu S(2017)ADMB: Application‐driven multihop broadcast for vehicular networksInternational Journal of Communication Systems10.1002/dac.330630:15Online publication date: 6-Mar-2017
https://doi.org/10.1002/dac.3306

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