In sensor networks, the sensor selection task is to activate only a subset, possibly a small subset, of the sensors while gaining as much utility as possible from the sensors. Most solutions are centralized algorithms with full knowledge of the network. We explore local algorithms for sensor selection. In these algorithms, each sensor independently decides if it should be included in the selection based on knowledge of its neighborhood alone. We design algorithms for increasing levels of knowledge in terms of the neighborhood size and demonstrate on randomly generated graphs representing sensor networks the improvement possible with more knowledge.
|Title of host publication||International Conference on Embedded Wireless Systems and Networks, EWSN 2018|
|Editors||Domenico Giustiniano, Dimitrios Koutsonikolas|
|Number of pages||2|
|State||Published - 2018|
|Event||International Conference on Embedded Wireless Systems and Networks, EWSN 2018 - Madrid, Spain|
Duration: 14 Feb 2018 → 16 Feb 2018
|Name||International Conference on Embedded Wireless Systems and Networks|
|Conference||International Conference on Embedded Wireless Systems and Networks, EWSN 2018|
|Period||14/02/18 → 16/02/18|
Bibliographical noteFunding Information:
Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-09-2-0053. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. 6 References
© 2018 is held by the authors.