Machine Learning - Special issue on context sensitivity and concept drift
A survey of design techniques for system-level dynamic power management
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special section on low-power electronics and design
Dynamic power management for portable systems
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Minimizing energy for wireless web access with bounded slowdown
Proceedings of the 8th annual international conference on Mobile computing and networking
Minimizing energy for wireless web access with bounded slowdown
Wireless Networks
Energy consumption in mobile phones: a measurement study and implications for network applications
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Characterizing radio resource allocation for 3G networks
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
A first look at traffic on smartphones
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
TailTheft: leveraging the wasted time for saving energy in cellular communications
MobiArch '11 Proceedings of the sixth international workshop on MobiArch
Profiling resource usage for mobile applications: a cross-layer approach
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
TOP: Tail Optimization Protocol For Cellular Radio Resource Allocation
ICNP '10 Proceedings of the The 18th IEEE International Conference on Network Protocols
A close examination of performance and power characteristics of 4G LTE networks
Proceedings of the 10th international conference on Mobile systems, applications, and services
Optimizing background email sync on smartphones
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
Opportunistic position update protocols for mobile devices
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Practical prediction and prefetch for faster access to applications on mobile phones
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
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The 3G/LTE wireless interface is a significant contributor to battery drain on mobile devices. A large portion of the energy is consumed by unnecessarily keeping the mobile device's radio in its "Active" mode even when there is no traffic. This paper describes the design of methods to reduce this portion of energy consumption by learning the traffic patterns and predicting when a burst of traffic will start or end. We develop a technique to determine when to change the radio's state from Active to Idle, and another to change the radio's state from Idle to Active. In evaluating the methods on real usage data from 9 users over 28 total days on four different carriers, we find that the energy savings range between 51% and 66% across the carriers for 3G, and is 67% on the Verizon LTE network. When allowing for delays of a few seconds (acceptable for background applications), the energy savings increase to between 62% and 75% for 3G, and 71% for LTE. The increased delays reduce the number of state switches to be the same as in current networks with existing inactivity timers.