Abstract
Visual sensor networks (VSNs) are becoming increasingly popular in a number of application domains. A distinguishing characteristic of VSNs is to self-configure to minimize the need for operator control and to improve scalability. One of the areas of self-configuration is camera coverage control that is, how should cameras adjust their field-of-views to cover maximum targets? This is an NP-hard problem. We show that the existing heuristics have a number of weaknesses that influence both coverage and overhead. Therefore, we first propose a computationally efficient centralized heuristic that provides near-optimal coverage for small-scale networks. However, it requires significant communication and computation overhead, making it unsuitable for large-scale networks. Thus, we develop a distributed algorithm that outperforms the existing distributed algorithm with lower communication overhead, at the cost of coverage accuracy. We show that the proposed heuristics guarantee to cover at least half of the targets covered by the optimal solution. Finally, to gain benefits of both centralized and distributed algorithms, we propose a hierarchical algorithm where cameras are decomposed into neighborhoods that coordinate their coverage using an elected local coordinator. We observe that the hierarchical algorithm provides scalable near-optimal coverage with networking cost significantly less than that of centralized and distributed solutions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.