Leveraging the Tail Time for Saving Energy in Cellular Networks

In cellular networks, inactivity timers are used to control the release of radio resources. However, during the timeout period of inactivity timers, known as the tail time, a large proportion of energy in user devices and a considerable amount of radio resources are wasted. In this paper, we propose TailTheft, a scheme that leverages the tail time for batching and prefetching to reduce energy consumption. For network requests from a number of applications that can be deferred or prefetched, TailTheft provides a customized application programming interface to distinguish requests and then schedules delay-tolerant and prefetchable requests in the tail time to save energy. TailTheft employs a virtual tail time mechanism to determine the amount of tail time that can be used and a dual queue scheduling algorithm to schedule transmissions. We implement TailTheft in the Network Simulator with a model for calculating energy consumption that is based on parameters measured from mobile phones. We evaluate TailTheft using real application traces, and the experimental results show that TailTheft can achieve significant savings on battery energy (up to 65%) and dedicated radio resources (up to 56%), compared to the default policy.

[1]  Gernot Heiser,et al.  An Analysis of Power Consumption in a Smartphone , 2010, USENIX Annual Technical Conference.

[2]  Jui-Hung Yeh,et al.  Comparative Analysis of Energy-Saving Techniques in 3GPP and 3GPP2 Systems , 2009, IEEE Transactions on Vehicular Technology.

[3]  Hari Balakrishnan,et al.  Traffic-aware techniques to reduce 3G/LTE wireless energy consumption , 2012, CoNEXT '12.

[4]  Jason Flinn,et al.  Informed mobile prefetching , 2012, MobiSys '12.

[5]  Ramachandran Ramjee,et al.  Bartendr: a practical approach to energy-aware cellular data scheduling , 2010, MobiCom.

[6]  George Varghese,et al.  RadioJockey: mining program execution to optimize cellular radio usage , 2012, Mobicom '12.

[7]  Hossam S. Hassanein,et al.  Downlink Scheduling With Economic Considerations for Future Wireless Networks , 2009, IEEE Transactions on Vehicular Technology.

[8]  Antti Toskala,et al.  HSDPA/HSUPA for UMTS: High Speed Radio Access for Mobile Communications , 2006 .

[9]  Jul-Hung Yeh,et al.  Impact of inactivity timer on energy consumption in WCDMA and cdma2000 , 2004, 2004 Symposium on Wireless Telecommunications.

[10]  Deborah Estrin,et al.  A first look at traffic on smartphones , 2010, IMC '10.

[11]  Justin Manweiler,et al.  Avoiding the Rush Hours: WiFi Energy Management via Traffic Isolation , 2011, IEEE Transactions on Mobile Computing.

[12]  Kang G. Shin,et al.  E-MiLi: Energy-Minimizing Idle Listening in Wireless Networks , 2011, IEEE Transactions on Mobile Computing.

[13]  Wei Luo,et al.  Impacts of inactivity timer values on UMTS system capacity , 2002, 2002 IEEE Wireless Communications and Networking Conference Record. WCNC 2002 (Cat. No.02TH8609).

[14]  Deborah Estrin,et al.  Diversity in smartphone usage , 2010, MobiSys '10.

[15]  Sajal K. Das,et al.  Optimal MAC state switching for cdma2000 networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[16]  Arun Venkataramani,et al.  Augmenting mobile 3G using WiFi , 2010, MobiSys '10.

[17]  Feng Qian,et al.  Characterizing radio resource allocation for 3G networks , 2010, IMC '10.

[18]  Shlomo Moran,et al.  Optimizing Result Prefetching in Web Search Engines with Segmented Indices , 2002, VLDB.

[19]  Shlomo Moran,et al.  Optimizing result prefetching in web search engines with segmented indices , 2002, TOIT.

[20]  Ramesh Govindan,et al.  Energy-efficient positioning for smartphones using Cell-ID sequence matching , 2011, MobiSys '11.

[21]  Feng Qian,et al.  Profiling resource usage for mobile applications: a cross-layer approach , 2011, MobiSys '11.

[22]  Gokhan Memik,et al.  Into the wild: Studying real user activity patterns to guide power optimizations for mobile architectures , 2009, 2009 42nd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[23]  Feng Qian,et al.  TOP: Tail Optimization Protocol For Cellular Radio Resource Allocation , 2010, The 18th IEEE International Conference on Network Protocols.

[24]  Chuang Lin,et al.  Modeling and Improving TCP Performance over Cellular Link with Variable Bandwidth , 2011, IEEE Transactions on Mobile Computing.

[25]  Elizabeth M. Belding-Royer,et al.  Cool-Tether: energy efficient on-the-fly wifi hot-spots using mobile phones , 2009, CoNEXT '09.

[26]  Yaoxue Zhang,et al.  TailTheft: leveraging the wasted time for saving energy in cellular communications , 2011, MobiArch '11.

[27]  Stefania Sesia,et al.  LTE - The UMTS Long Term Evolution, Second Edition , 2011 .

[28]  Gennaro Boggia,et al.  Theory and Practice of RRC State Transitions in UMTS Networks , 2009, 2009 IEEE Globecom Workshops.

[29]  Arun Venkataramani,et al.  Energy consumption in mobile phones: a measurement study and implications for network applications , 2009, IMC '09.

[30]  Ramesh Govindan,et al.  Energy-delay tradeoffs in smartphone applications , 2010, MobiSys '10.