欢迎访问中国科学院大学学报,今天是
计算机科学

移动智能终端下3G网络低功耗延迟唤醒策略

  • 陈博 ,
  • 李曦 ,
  • 周学海 ,
  • 席菁 ,
  • 朱宗卫
展开
  • 1. 中国科学技术大学软件学院, 江苏 苏州 215123;
    2. 中国科学技术大学计算机科学与技术学院, 合肥 230027

收稿日期: 2014-08-13

  修回日期: 2014-10-28

  网络出版日期: 2015-07-15

基金资助

国家自然科学基金(61272131,61379040)资助

Low-power strategy based on delayed awakening 3G network for smartphone

  • CHEN Bo ,
  • LI Xi ,
  • ZHOU Xuehai ,
  • XI Jing ,
  • ZHU Zongwei
Expand
  • 1. School of Software Engineering, University of Science and Technology of China, Suzhou 215123, Jiangsu, China;
    2. School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China

Received date: 2014-08-13

  Revised date: 2014-10-28

  Online published: 2015-07-15

摘要

突发性数据传输易导致3G网络工作模式从低功耗状态向高功耗状态迁移,状态切换加剧能耗开销.本文对移动终端网络通信行为进行分析,提出移动终端下3G网络低功耗延迟唤醒策略.该策略对网络数据进行延时敏感性划分,并据此进行不同时间的延时传输,延迟3G网络唤醒时间达到降耗目的.仿真实验表明,策略有效降低系统功耗,具有较强的可行性.

本文引用格式

陈博 , 李曦 , 周学海 , 席菁 , 朱宗卫 . 移动智能终端下3G网络低功耗延迟唤醒策略[J]. 中国科学院大学学报, 2015 , 32(4) : 562 -570 . DOI: 10.7523/j.issn.2095-6134.2015.04.020

Abstract

The burst data transfer will lead to 3G migration from the low-power state to high-power state, and frequent switching exacerbates the energy consumption. We analyze 3G network communication behavior and give a low-power strategy based on delayed awakening 3G network for smartphone. The strategy classifies packages according to the delay-sensitivity, and delays sending packet for different intervals so as to reduce the energy consumption. Simulation results show that the proposed mechanism effectively reduces the power consumption of the system and has the strong feasibility.

参考文献

[1] Kim S, Kim H K, Kim H J. Climate change and ICTs [C]//Proceeding of Telecommunications Energy Conference, 2009:1-4.
[2] Wang X F, Vasilakos A V, Chen M, et al. A survey of green mobile networks: opportunities and challenges[J] Mobile Networks and Applications, 2011,17(1):4-20
[3] Hepburn A. Infographic: 2013 mobile growth statistics [EB/OL](2013-10-01) [2014-09-25].http://www.digitalbuzzblog.com/infographic-2013-mobile-growth-statistics.
[4] Google Company. Android SDK [EB/OL]. (2008-07-09) [2014-09-25] http://www.android-doc.com/reference/packages.html.
[5] Balasubramanian A, Balasubramanian N J, Venkataramani A. Energy consumption in mobile phones: a measurement study and implications for network applications [C]//Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference. 2009: 280-293.
[6] ARM Company. ARM Technical Support Knowledge Articles [EB/OL].(2011-05-01) [2014-09-25]. http://infocenter.arm.com/.
[7] Apple Company. OS X Mavericks is more than powerful. [EB/OL].(2013-07-01) [2014-09-25]. http://www.apple.com/osx/advanced-technologies/.
[8] Perrucci G P, Fitzek F, Sasso G, et al. On the impact of 2G and 3G network usage for mobile phones'battery life [C]//Proceedings of the European Wireless Conference (EW), 2009:255-259.
[9] Armstrong T, Trescases O, Amza C, et al. Effcient and transparent dynamic content updates for mobile clients [C]//Proceedings of the 4th International Conference on Mobile Systems, Applications and Services(MobiSys'06), 2006.
[10] Qian F, Wang Z, Gerber A, et al. Profiling resource usage for mobile applications: a cross-layer approach [C]//Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services ( MobiSys'11), 2011: 321-334.
[11] Palit R, Naik K, Singh A, et al. Impact of packet aggregation on energy consumption in smartphones [C]//Proceedings of the 7th Inter-national Wireless Communications and Mobile Computing Conference (IWCMC), 2011:589-594.
[12] Hossein F, Dimitrios L, Ratul M, et al. A first look at traffic on smartphones [C]//Proceedings of the 10th ACM SIGCOMM Conference on Internet Measurement Melbourne, Australia(SIGCOMM), 2010.
[13] Pathak A, Hu Y C, Zhang M, et al. Where is the energy spent inside my app? fine grained energy accounting on smartphones with eprof [C]//Proceedings of the ACM European Conference on Computer Systems(EuroSys), 2012: 29-42.
[14] Liu H, Zhang Y, Zhou Y, et al. TailTheft: leveraging the wasted time for saving energy in cellular communications [C]//Proceedings of the 6th International Workshop on MobiArch, ser. (MobiArch), 2011: 31-36.
[15] Schwartz C, Hossfeld T, Lehrieder F, et al. Angry apps: the impact of network timer selection on power consumption,signalling load,and Web QoE[J]. Journal of Computer Networks and Communications, 2013.
[16] Vergara E J, Tehrani S N. Energy-aware cross-layer burst buffering for wireless communication [C]//Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet, 2012:1-10.
[17] Vergara E J, Sanjuan J. Kernel level energy-efficient 3G background traffic shaper for android smartphones [C]//Proceedings of Wireless Communications and Mobile Computing Conference(IWCMC), 2013.
[18] Garcia J S. 3G Energy-efficient packet handling kernel module for android [D]. Link Oping University, 2012.
[19] Zhao B, Tak B C, Cao G. Reducing the delay and power consumption of web browsing on smartphones in 3G networks [C]//Proceeding of the 31st International Conference on Distributed Computing Systems (ICDCS), 2011:413-422.
[20] Schulman A, Navda V, Ramachandran, et al. Bartendr:a practical approach to energy-aware cellular data scheduling [C]//Proceedings of the sixteenth annual international conference on Mobile computing and networking( MobiCom), 2010.
[21] Netfilter.org. Linux netfilter Hacking HOWTO [EB/OL].(2002-07-02) [2014-09-25]. http://www.netfilter.org/documentation/HOWTO/netfilter-hacking-HOWTO.html.
[22] Qian F, Wang Z G, Gerber A, et al. Top: tail optimization protocol for cellular radio resource allocation [C]//Proceeding of the 18th IEEE International Conference on Network Protocols( ICNP), 2010:285-294.
文章导航

/