TY - JOUR
T1 - Minimizing the total cost of barrier coverage in a linear domain
AU - Zhang, Xiao
AU - Fan, Haosheng
AU - Lee, Victor C.S.
AU - Li, Minming
AU - Zhao, Yingchao
AU - Liu, Chuang
N1 - Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2018/8/1
Y1 - 2018/8/1
N2 - Barrier coverage, as one of the most important applications of wireless sensor network (WSNs), is to provide coverage for the boundary of a target region. We study the barrier coverage problem by using a set of n sensors with adjustable coverage radii deployed along a line interval or circle. Our goal is to determine a range assignment R= (r1, r2, … , rn) of sensors such that the line interval or circle is fully covered and its total cost C(R)=∑i=1nriα is minimized. For the line interval case, we formulate the barrier coverage problem of line-based offsets deployment, and present two approximation algorithms to solve it. One is an approximation algorithm of ratio 4 / 3 runs in O(n2) time, while the other is a fully polynomial time approximation scheme (FPTAS) of computational complexity O(n2ϵ). For the circle case, we optimally solve it when α= 1 and present a 2(π2)α-approximation algorithm when α> 1. Besides, we propose an integer linear programming (ILP) to minimize the total cost of the barrier coverage problem such that each point of the line interval is covered by at least k sensors.
AB - Barrier coverage, as one of the most important applications of wireless sensor network (WSNs), is to provide coverage for the boundary of a target region. We study the barrier coverage problem by using a set of n sensors with adjustable coverage radii deployed along a line interval or circle. Our goal is to determine a range assignment R= (r1, r2, … , rn) of sensors such that the line interval or circle is fully covered and its total cost C(R)=∑i=1nriα is minimized. For the line interval case, we formulate the barrier coverage problem of line-based offsets deployment, and present two approximation algorithms to solve it. One is an approximation algorithm of ratio 4 / 3 runs in O(n2) time, while the other is a fully polynomial time approximation scheme (FPTAS) of computational complexity O(n2ϵ). For the circle case, we optimally solve it when α= 1 and present a 2(π2)α-approximation algorithm when α> 1. Besides, we propose an integer linear programming (ILP) to minimize the total cost of the barrier coverage problem such that each point of the line interval is covered by at least k sensors.
KW - Approximation algorithm
KW - Barrier coverage
KW - Range assignment
KW - Wireless sensor networks
UR - https://www.scopus.com/pages/publications/85047144768
U2 - 10.1007/s10878-018-0306-6
DO - 10.1007/s10878-018-0306-6
M3 - 文章
AN - SCOPUS:85047144768
SN - 1382-6905
VL - 36
SP - 434
EP - 457
JO - Journal of Combinatorial Optimization
JF - Journal of Combinatorial Optimization
IS - 2
ER -