Node-Level Energy Management for Sensor Networks in the Presence of Multiple Applications

Energy related research in wireless ad hoc sensor networks (WASNs) is focusing on energy saving techniques in the application-, protocol-, service-, or hardware-level. Little has been done to manage the finite amount of energy for a given (possibly optimally-designed) set of applications, protocols and hardware. Given multiple candidate applications (i.e., distributed algorithms in a WASN) of different energy costs and different user rewards, how does one manage a finite energy amount? Where does one provide energy, so as to maximize the useful work done (i.e., maximize user rewards)? We formulate the problem at the node-level, by having system-level “hints” from the applications. In order to tackle the central problem we first identify the energy consumption patterns of applications in WASNs, we propose ways for real-time measurements of the energy consumption by individual applications, and we solve the problem of estimating the extra energy consumption that a new application brings to a set of executing applications. Having these tools at our disposal, and by properly abstracting the problem we present an optimal admission control policy and a post-admission policing mechanism at the node-level. The admission policy can achieve up to 48% increase in user rewards compared to the absence of energy management, for a variety of application mixes.

[1]  Rajeevan Amirtharajah,et al.  Self-powered signal processing using vibration-based power generation , 1998, IEEE J. Solid State Circuits.

[2]  Carlo Vercellis,et al.  Stochastic on-line knapsack problems , 1995, Math. Program..

[3]  Mani B. Srivastava,et al.  Design and implementation of a framework for efficient and programmable sensor networks , 2003, MobiSys '03.

[4]  Anton J. Kleywegt,et al.  The Dynamic and Stochastic Knapsack Problem , 1998, Oper. Res..

[5]  W. Rabiner,et al.  Design considerations for distributed microsensor systems , 1999, Proceedings of the IEEE 1999 Custom Integrated Circuits Conference (Cat. No.99CH36327).

[6]  Mitali Singh,et al.  Proceedings of the First IEEE International Conference on Pervasive Computing and Communications (PerCom'03), March 23-26, 2003, Fort Worth, Texas, USA , 2003, PerCom.

[7]  Philip Levis,et al.  Maté: a tiny virtual machine for sensor networks , 2002, ASPLOS X.

[8]  Chien-Chung Shen,et al.  Querying and tasking in sensor networks , 2000, Defense, Security, and Sensing.

[9]  Joseph A. Paradiso,et al.  Parasitic power harvesting in shoes , 1998, Digest of Papers. Second International Symposium on Wearable Computers (Cat. No.98EX215).