IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Dynamic Power Management in Wireless Sensor Networks
IEEE Design & Test
Node-Level Energy Management for Sensor Networks in the Presence of Multiple Applications
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Mode Selection and Mode-Dependency Modeling for Power-Aware Embedded Systems
ASP-DAC '02 Proceedings of the 2002 Asia and South Pacific Design Automation Conference
Set k-cover algorithms for energy efficient monitoring in wireless sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
A time series-based approach for power management in mobile processors and disks
NOSSDAV '04 Proceedings of the 14th international workshop on Network and operating systems support for digital audio and video
Compressing historical information in sensor networks
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Simulating the power consumption of large-scale sensor network applications
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Telos: enabling ultra-low power wireless research
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Operating System Modifications for Task-Based Speed and Voltage
Proceedings of the 1st international conference on Mobile systems, applications and services
Load shedding in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Predictive algorithms in the management of computer systems
IBM Systems Journal
Proceedings of the 5th international conference on Embedded networked sensor systems
A framework for the automated generation of power-efficient classifiers for embedded sensor nodes
Proceedings of the 5th international conference on Embedded networked sensor systems
Optimal sensing using query arrival distributions
Proceedings of the second ACM international symposium on Design and analysis of intelligent vehicular networks and applications
Hi-index | 0.01 |
Energy is a precious resource in wireless sensor networks as sensor nodes are typically powered by batteries with high replacement cost. This paper presents eSENSE: an energy-efficient stochastic sensing framework for wireless sensor platforms. eSENSE is a node-level framework that utilizes knowledge of the underlying data streams as well as application data quality requirements to conserve energy on a sensor node. eSENSE employs a stochastic scheduling algorithm to dynamically control the operating modes of the sensor node components. This scheduling algorithm enables an adaptive sampling strategy that aggressively conserves power by adjusting sensing activity to the application requirements. Using experimental results obtained on Power-TOSSIM with a real-world data trace, we demonstrate that our approach reduces energy consumption by 29-36% while providing strong statistical guarantees on data quality.