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ZTE Communications ›› 2013, Vol. 11 ›› Issue (1): 44-50.

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Battery Voltage Discharge Rate Prediction and Video Content Adaptation in Mobile Devices on 3G Access Networks

Is-Haka Mkwawa and Lingfen Sun   

  1. School of Computing and Mathematics, University of Plymouth, Plymouth, PL4 8AA, UK
  • 收稿日期:2013-01-31 出版日期:2013-03-25 发布日期:2013-03-25
  • 作者简介:Is-Haka Mkwawa (Is-Haka.Mkwawa@plymouth.ac.uk) received his PhD in computing from the University of Bradford. He is currently working as a research fellow on the EU FP7 GERYON project at Plymouth University. Since 2002, he has also worked in various capacities on the EU FP6 and FP7 projects at Plymouth University, the University of Bradford, and University College Dublin. He has previously worked on other projects, including ADAMANTIUM, VITAL, NoE Euro FGi, SFI, NoE Euro NGi, and IASON. He is the author of several published works on parallel computing and communication, distributed systems, next-generation networks, grid computing, VoIP quality adaptations, energy conservation techniques and mobility management in mobile and wireless networks, and performance analysis and evaluation of computer networks. He is the co-author of the textbook Guide to Voice and Video over IP: For Fixed and Mobile Networks.

    Lingfen Sun (L.Sun@plymouth.ac.uk) received her PhD degree in computing and communications from the University of Plymouth in 2004. She received her MSc in communications and electronics systems and BEng in telecommunications engineering from the Institute of Communications Engineering, China, in 1988 and 1985. She is currently a reader in multimedia communications and networks in the School of Computing and Mathematics, University of Plymouth. She has been involved in several funded projects, including FP7 GERYON (as scientific manager and principal investigator), COST Action QUALINET, FP7 ADAMANTIUM, and FP6 BIOPATTERN. She also led an industry funded project on multimedia over 3G networks. She has published one textbook, four book chapters, and more than 60 peer-refereed technical papers. She was the chair of QoE Interest Group of IEEE MMTC during from 2010 to 2012. Her current research interests include multimedia quality assessment, QoE control and management, VoIP/IPTV, and multimedia services for emergency communications and eHealthcare.
  • 基金资助:
    The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No. 284863 (FP7 SEC GERYON).

Battery Voltage Discharge Rate Prediction and Video Content Adaptation in Mobile Devices on 3G Access Networks

Is-Haka Mkwawa and Lingfen Sun   

  1. School of Computing and Mathematics, University of Plymouth, Plymouth, PL4 8AA, UK
  • Received:2013-01-31 Online:2013-03-25 Published:2013-03-25
  • About author:Is-Haka Mkwawa (Is-Haka.Mkwawa@plymouth.ac.uk) received his PhD in computing from the University of Bradford. He is currently working as a research fellow on the EU FP7 GERYON project at Plymouth University. Since 2002, he has also worked in various capacities on the EU FP6 and FP7 projects at Plymouth University, the University of Bradford, and University College Dublin. He has previously worked on other projects, including ADAMANTIUM, VITAL, NoE Euro FGi, SFI, NoE Euro NGi, and IASON. He is the author of several published works on parallel computing and communication, distributed systems, next-generation networks, grid computing, VoIP quality adaptations, energy conservation techniques and mobility management in mobile and wireless networks, and performance analysis and evaluation of computer networks. He is the co-author of the textbook Guide to Voice and Video over IP: For Fixed and Mobile Networks.

    Lingfen Sun (L.Sun@plymouth.ac.uk) received her PhD degree in computing and communications from the University of Plymouth in 2004. She received her MSc in communications and electronics systems and BEng in telecommunications engineering from the Institute of Communications Engineering, China, in 1988 and 1985. She is currently a reader in multimedia communications and networks in the School of Computing and Mathematics, University of Plymouth. She has been involved in several funded projects, including FP7 GERYON (as scientific manager and principal investigator), COST Action QUALINET, FP7 ADAMANTIUM, and FP6 BIOPATTERN. She also led an industry funded project on multimedia over 3G networks. She has published one textbook, four book chapters, and more than 60 peer-refereed technical papers. She was the chair of QoE Interest Group of IEEE MMTC during from 2010 to 2012. Her current research interests include multimedia quality assessment, QoE control and management, VoIP/IPTV, and multimedia services for emergency communications and eHealthcare.
  • Supported by:
    The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No. 284863 (FP7 SEC GERYON).

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摘要： According to Cisco, mobile multimedia services now account for more than half the total amount of Internet traffic. This trend is burdening mobile devices in terms of power consumption, and as a result, more effort is needed to devise a range of power-saving techniques. While most power-saving techniques are based on sleep scheduling of network interfaces, little has been done to devise multimedia content adaptation techniques. In this paper, we propose a multiple linear regression model that predicts the battery voltage discharge rate for several video send bit rates in a VoIP application. The battery voltage discharge rate needs to be accurately estimated in order to estimate battery life in critical VoIP contexts, such as emergency communication. In our proposed model, the range of video send bitrates is carefully chosen in order to maintain an acceptable VoIP quality of experience. From extensive profiling, the empirical results show that the model effectively saves power and prolongs real-time VoIP sessions when deployed in power-driven adaptation schemes.

关键词: QoE, power, mobile devices, quality adaptation, discharge rate

Abstract: According to Cisco, mobile multimedia services now account for more than half the total amount of Internet traffic. This trend is burdening mobile devices in terms of power consumption, and as a result, more effort is needed to devise a range of power-saving techniques. While most power-saving techniques are based on sleep scheduling of network interfaces, little has been done to devise multimedia content adaptation techniques. In this paper, we propose a multiple linear regression model that predicts the battery voltage discharge rate for several video send bit rates in a VoIP application. The battery voltage discharge rate needs to be accurately estimated in order to estimate battery life in critical VoIP contexts, such as emergency communication. In our proposed model, the range of video send bitrates is carefully chosen in order to maintain an acceptable VoIP quality of experience. From extensive profiling, the empirical results show that the model effectively saves power and prolongs real-time VoIP sessions when deployed in power-driven adaptation schemes.

Key words: QoE, power, mobile devices, quality adaptation, discharge rate