TY - GEN
T1 - Minimum-cost linear coverage by sensors with adjustable ranges
AU - Li, Minming
AU - Sun, Xianwei
AU - Zhao, Yingchao
PY - 2011
Y1 - 2011
N2 - One of the most fundamental tasks of wireless sensor networks is to provide coverage of the deployment region. In this paper, we study the coverage of a line segment with a set of wireless sensors with adjustable coverage ranges. Each coverage range of a sensor is an interval centered at that sensor whose length is decided by the power the sensor chooses. The objective is to find a range assignment with the minimum cost. There are two variants of the optimization problem. In the discrete variant, each sensor can only choose from a finite set of powers while in the continuous variant, each sensor can choose power from a given interval. For the discrete variant of the problem, we present a polynomial-time exact algorithm. For the continuous variant of the problem, we develop constant-approximation algorithms when the cost for all sensors is proportional to r κ for some constant κ ≥ 1, where r is the covering radius corresponding to the chosen power. Specifically, if κ = 1, we give a simple 1.25-approximation algorithm and a fully polynomial-time approximation scheme (FPTAS); if κ > 1, we give a simple 2-approximation algorithm.
AB - One of the most fundamental tasks of wireless sensor networks is to provide coverage of the deployment region. In this paper, we study the coverage of a line segment with a set of wireless sensors with adjustable coverage ranges. Each coverage range of a sensor is an interval centered at that sensor whose length is decided by the power the sensor chooses. The objective is to find a range assignment with the minimum cost. There are two variants of the optimization problem. In the discrete variant, each sensor can only choose from a finite set of powers while in the continuous variant, each sensor can choose power from a given interval. For the discrete variant of the problem, we present a polynomial-time exact algorithm. For the continuous variant of the problem, we develop constant-approximation algorithms when the cost for all sensors is proportional to r κ for some constant κ ≥ 1, where r is the covering radius corresponding to the chosen power. Specifically, if κ = 1, we give a simple 1.25-approximation algorithm and a fully polynomial-time approximation scheme (FPTAS); if κ > 1, we give a simple 2-approximation algorithm.
UR - https://www.scopus.com/pages/publications/80052246207
U2 - 10.1007/978-3-642-23490-3_3
DO - 10.1007/978-3-642-23490-3_3
M3 - 会议稿件
AN - SCOPUS:80052246207
SN - 9783642234897
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 25
EP - 35
BT - Wireless Algorithms, Systems, and Applications - 6th International Conference, WASA 2011, Proceedings
T2 - 6th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2011
Y2 - 11 August 2011 through 13 August 2011
ER -