Stochastic on-line knapsack problems
Mathematical Programming: Series A and B
Maté: a tiny virtual machine for sensor networks
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
The Dynamic and Stochastic Knapsack Problem
Operations Research
Parasitic Power Harvesting in Shoes
ISWC '98 Proceedings of the 2nd IEEE International Symposium on Wearable Computers
Design and implementation of a framework for efficient and programmable sensor networks
Proceedings of the 1st international conference on Mobile systems, applications and services
Design and implementation of a framework for efficient and programmable sensor networks
Proceedings of the 1st international conference on Mobile systems, applications and services
eSENSE: energy efficient stochastic sensing framework scheme for wireless sensor platforms
Proceedings of the 5th international conference on Information processing in sensor networks
ANSWER: AutoNomouS netWorked sEnsoR system
Journal of Parallel and Distributed Computing
A survey on wireless multimedia sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
SensorWare: Programming sensor networks beyond code update and querying
Pervasive and Mobile Computing
| Hi-index | 0.00 |
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 ofapplications, 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 theuseful 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 forreal-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.