Minkowski's convex body theorem and integer programming
Mathematics of Operations Research
Journal of the ACM (JACM)
Introduction to algorithms
Extended Dominating-Set-Based Routing in Ad Hoc Wireless Networks with Unidirectional Links
IEEE Transactions on Parallel and Distributed Systems
Complexity of domination-type problems in graphs
Nordic Journal of Computing
Set k-cover algorithms for energy efficient monitoring in wireless sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Complexity of the Exact Domatic Number Problem and of the Exact Conveyor Flow Shop Problem
Theory of Computing Systems
An improved exact algorithm for the domatic number problem
Information Processing Letters
Coverage breach problems in bandwidth-constrained sensor networks
ACM Transactions on Sensor Networks (TOSN)
Improved algorithms for path, matching, and packing problems
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Coverage problems in wireless sensor networks: designs and analysis
International Journal of Sensor Networks
Energy Efficient Monitoring in Sensor Networks
Algorithmica - Special Issue: Latin American Theoretical Informatics
Maximum lifetime coverage preserving scheduling algorithms in sensor networks
Journal of Global Optimization
Parameterized Complexity
Hi-index | 5.23 |
Max-lifetime Target Coverage can be viewed as a family of problems where the task is to partition the sensors into groups and assign their time-slots such that the coverage lifetime is maximized while satisfying some coverage requirement. Unfortunately, these problems are NP-hard. To gain insight into the source of the complexity, we initiate a systematic parameterized complexity study of two types of Max-lifetime Target Coverage: Max-min Target Coverage and Max-individual Target Coverage. We first prove that both problems remain NP-hard even in the special cases where each target is covered by at most two sensors or each sensor can cover at most two targets. By contrast, restricting the number of targets reduces the complexity of the considered problems. In other words, they are both fixed parameter tractable (FPT) with respect to the parameter ''number of targets''. Moreover, we extend our studies to the structural parameter ''number k of sensors covering at least two targets''. Positively, both problems are in FPT with respect to k. Finally, we show that Max-min Target Coverage is in FPT with respect to the combined parameters ''number of groups'' and ''number of targets covered by each group''.