TY - GEN
T1 - Maximum gaps in path coverage
AU - Shamoun, Simon
AU - Abdelzaher, Tarek
AU - Bar-Noy, Amotz
N1 - Funding 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.
Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/11/25
Y1 - 2019/11/25
N2 - We study the maximum size of coverage gaps by sensors selected to cover a path. Gap sizes, and not just total coverage, are important because significant events can be missed during uncovered periods. The amount of knowledge about a path affects the ability to select sensors to cover it. We first study how coverage gaps are affected by increases in knowledge and improvements in selection strategies when sensors are selected to maximize path coverage. The gap size does not necessarily decrease in the same way that coverage increases with a better selection. We then show that even simple modifications to the algorithm can reduce the coverage gap, and show how this is affected about the level of knowledge.
AB - We study the maximum size of coverage gaps by sensors selected to cover a path. Gap sizes, and not just total coverage, are important because significant events can be missed during uncovered periods. The amount of knowledge about a path affects the ability to select sensors to cover it. We first study how coverage gaps are affected by increases in knowledge and improvements in selection strategies when sensors are selected to maximize path coverage. The gap size does not necessarily decrease in the same way that coverage increases with a better selection. We then show that even simple modifications to the algorithm can reduce the coverage gap, and show how this is affected about the level of knowledge.
KW - Coverage gaps
KW - Path coverage
KW - Sensor selection
UR - http://www.scopus.com/inward/record.url?scp=85077344427&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85077344427&partnerID=8YFLogxK
U2 - 10.1145/3345768.3355940
DO - 10.1145/3345768.3355940
M3 - Conference contribution
AN - SCOPUS:85077344427
T3 - MSWiM 2019 - Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems
SP - 109
EP - 112
BT - MSWiM 2019 - Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems
PB - Association for Computing Machinery, Inc
T2 - 22nd ACM International Conference on Modelling, Analysis, and Simulation of Wireless and Mobile Systems, MSWiM 2019
Y2 - 25 November 2019 through 29 November 2019
ER -