Editorial Advances in Mobile Video Networking · Editorial Advances in Mobile Video Networking...
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Editorial Advances in Mobile Video Networking Qi Wang, 1 Guojun Wang, 2 Christos Grecos, 3 and Ansgar Gerlicher 4 1 University of the West of Scotland, Paisley PA1 2BE, UK 2 Guangzhou University, Guangzhou 510006, China 3 Central Washington University, 400 E. University Way, Ellensburg, WA 98926, USA 4 Stuttgart Media University, Hochschule der Medien Nobelstraße 10, 70569 Stuttgart, Germany Correspondence should be addressed to Qi Wang; [email protected] Received 21 July 2016; Accepted 21 July 2016 Copyright © 2016 Qi Wang et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Video applications have been increasingly dominating world- wide mobile network traffic in the last years. e growing popularity of smart phones and other mobile devices, on- demand and surveillance video services, multimedia social networking, the latest advances in video coding and trans- mission, and the significant increase in mobile network capacity have all contributed to this global phenomenon. Both challenges and opportunities have emerged in multiple research disciplines involving video signal processing, 4G such as LTE (Long Term Evolution) and even 5G mobile networks, mobile cloud computing, Big Visual Data, mobile user experience, and so on. Research in these leading-edge areas has been gaining accelerated global momentum in both developing and developed economies. erefore, it is high time to call for contributions to further stimulate the continuing efforts to resolve the intrin- sic conflicts between resource-demanding video applications and resource-constrained mobile networks, optimise video networking performance in mobile networks and achieve improved Quality of Experience (QoE) for end users, and leverage cloud computing and other cutting-edge technolo- gies and standards in supporting adaptive, secure, energy- efficient, and reliable video delivery in various mobile sys- tems. is special issue attracted numerous submissions, out of which five papers have been accepted to be published. ese accepted papers are expected to highlight some of the important aspects outlined above. It is the pleasure for the guest editorial team to introduce these papers as follows. e first paper entitled “Energy-Efficient Transmission Strategy by Using Optimal Stopping Approach for Mobile Networks” by Y. Peng et al. contributes to greener video delivery in mobile networks. An optimised distributed opportunistic scheduling algorithm is proposed to maximise the usage of good quality slots of the time-varying wireless transmission channels to improve video data delivery ratio and thus energy efficiency, whilst taking into account the delay constraint for video applications. e second paper “Network-Aware Reference Frame Control for Error-Resilient H.264/AVC Video Streaming Service” by H.-S. Gang et al. focuses on enhancing the reliability of video streaming in error-prone networks such as mobile/wireless networks whilst making a trade-off between error resilience and coding efficiency. In particular, error propagation across video frames caused by video packet loss or corruption is effectively mitigated, through controlling the number of reference video frames based on the awareness of network channel status. In the third paper, “A Framework for QoE-Aware 3D Video Streaming Optimisation over Wireless Networks” by I. Politis et al., the challenging topic of 3D video streaming in LTE networks with good perceived quality is addressed. To model the QoE of end users, machine learning techniques are utilised and parameters from multiple layers are monitored and collected. In addition, a media-aware proxy is introduced to the proposed system, integrated with the QoE controller, to achieve QoE-aware, optimised 3D video transmission. e fourth paper, “A Low Energy Consumption Storage Method for Cloud Video Surveillance Data Based on SLA Classification” by Y. Xiong et al., also deals with the energy efficiency in a video system although the main concern is on the storage side other than the transmission side as in the first paper. e targeted application is Cloud Video Surveillance, Hindawi Publishing Corporation Mobile Information Systems Volume 2016, Article ID 9706378, 2 pages http://dx.doi.org/10.1155/2016/9706378
Transcript of Editorial Advances in Mobile Video Networking · Editorial Advances in Mobile Video Networking...
EditorialAdvances in Mobile Video Networking
Qi Wang,1 Guojun Wang,2 Christos Grecos,3 and Ansgar Gerlicher4
1University of the West of Scotland, Paisley PA1 2BE, UK2Guangzhou University, Guangzhou 510006, China3Central Washington University, 400 E. University Way, Ellensburg, WA 98926, USA4Stuttgart Media University, Hochschule der Medien Nobelstraße 10, 70569 Stuttgart, Germany
Correspondence should be addressed to Qi Wang; [email protected]
Received 21 July 2016; Accepted 21 July 2016
Copyright © 2016 Qi Wang et al.This is an open access article distributed under the Creative Commons Attribution License, whichpermits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Video applications have been increasingly dominatingworld-wide mobile network traffic in the last years. The growingpopularity of smart phones and other mobile devices, on-demand and surveillance video services, multimedia socialnetworking, the latest advances in video coding and trans-mission, and the significant increase in mobile networkcapacity have all contributed to this global phenomenon.Both challenges and opportunities have emerged in multipleresearch disciplines involving video signal processing, 4Gsuch as LTE (Long Term Evolution) and even 5G mobilenetworks, mobile cloud computing, Big Visual Data, mobileuser experience, and so on. Research in these leading-edgeareas has been gaining accelerated global momentum in bothdeveloping and developed economies.
Therefore, it is high time to call for contributions tofurther stimulate the continuing efforts to resolve the intrin-sic conflicts between resource-demanding video applicationsand resource-constrained mobile networks, optimise videonetworking performance in mobile networks and achieveimproved Quality of Experience (QoE) for end users, andleverage cloud computing and other cutting-edge technolo-gies and standards in supporting adaptive, secure, energy-efficient, and reliable video delivery in various mobile sys-tems. This special issue attracted numerous submissions, outof which five papers have been accepted to be published.These accepted papers are expected to highlight some of theimportant aspects outlined above. It is the pleasure for theguest editorial team to introduce these papers as follows.
The first paper entitled “Energy-Efficient TransmissionStrategy by Using Optimal Stopping Approach for MobileNetworks” by Y. Peng et al. contributes to greener video
delivery in mobile networks. An optimised distributedopportunistic scheduling algorithm is proposed to maximisethe usage of good quality slots of the time-varying wirelesstransmission channels to improve video data delivery ratioand thus energy efficiency, whilst taking into account thedelay constraint for video applications.
The second paper “Network-Aware Reference FrameControl for Error-Resilient H.264/AVC Video StreamingService” by H.-S. Gang et al. focuses on enhancing thereliability of video streaming in error-prone networks such asmobile/wireless networks whilst making a trade-off betweenerror resilience and coding efficiency. In particular, errorpropagation across video frames caused by video packet lossor corruption is effectively mitigated, through controlling thenumber of reference video frames based on the awareness ofnetwork channel status.
In the third paper, “A Framework for QoE-Aware 3DVideo Streaming Optimisation over Wireless Networks” byI. Politis et al., the challenging topic of 3D video streaming inLTE networks with good perceived quality is addressed. Tomodel the QoE of end users, machine learning techniques areutilised and parameters from multiple layers are monitoredand collected. In addition, amedia-aware proxy is introducedto the proposed system, integratedwith theQoE controller, toachieve QoE-aware, optimised 3D video transmission.
The fourth paper, “A Low Energy Consumption StorageMethod for Cloud Video Surveillance Data Based on SLAClassification” by Y. Xiong et al., also deals with the energyefficiency in a video system although the main concern is onthe storage side other than the transmission side as in the firstpaper. The targeted application is Cloud Video Surveillance,
Hindawi Publishing CorporationMobile Information SystemsVolume 2016, Article ID 9706378, 2 pageshttp://dx.doi.org/10.1155/2016/9706378
2 Mobile Information Systems
and the design objective is to reduce the power consumptionwithout compromising the Service Level Agreement (SLA)for users to access the stored surveillance video data in thecloud on demand in a timely fashion. Based on classifyingthe access time periods and thus virtual machines andstorage nodes, the proposed system reduces overall powerconsumption in the data centre by placing selected nodes intoan energy-saving mode.
In the final paper “A Novel Adaptation Method forHTTP Streaming of VBR Videos over Mobile Networks,”H. T. Le et al. investigate adaptive on-demand transmissionof variable bitrate (VBR) videos through HTTP streaming.Their adaptation scheme is designed to be tolerant to largevariations of video bitrate, featured with a buffer-basedalgorithm that considers smoothed throughput estimate,representative bitrate, and instant bitrate.
Acknowledgments
Theguest editorial teamwould like to thank all the authors forsubmitting their manuscripts to this special issue and all theinvited reviewers for their time and constructive feedback.Moreover, the teamappreciate the staff of this journal for theircontinuous support and patience in creating this special issue.
Qi WangGuojun Wang
Christos GrecosAnsgar Gerlicher
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