Cover Set Problem in Directional Sensor Networks
FGCN '07 Proceedings of the Future Generation Communication and Networking - Volume 01
Self-orienting wireless multimedia sensor networks for occlusion-free viewpoints
Computer Networks: The International Journal of Computer and Telecommunications Networking
An Adjustable Target Coverage Method in Directional Sensor Networks
APSCC '08 Proceedings of the 2008 IEEE Asia-Pacific Services Computing Conference
Energy Efficient Target-Oriented Scheduling in Directional Sensor Networks
IEEE Transactions on Computers
Voronoi Based Area Coverage Optimization for Directional Sensor Networks
ISECS '09 Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01
Selection and orientation of directional sensors for coverage maximization
SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
Movement Assisted Sensor Deployment in Directional Sensor Networks
MSN '10 Proceedings of the 2010 Sixth International Conference on Mobile Ad-hoc and Sensor Networks
On coverage issues in directional sensor networks: A survey
Ad Hoc Networks
A new coverage improvement algorithm based on motility capability of directional sensor nodes
ADHOC-NOW'11 Proceedings of the 10th international conference on Ad-hoc, mobile, and wireless networks
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Coverage optimization is a fundamental problem in Directional Sensor Networks (DSNs). Apart from solutions for omni-directional sensor nodes, more intelligent algorithms are required for this unique and non-trivial problem. In recent years, several centralized and decentralized methods were introduced to improve the coverage in randomly deployed DSNs. A thorough review reveals that the performance of random deployment is the most preferred way to measure the performance of a newly introduced algorithm. However, the relative performance gains of two separate algorithms do not necessarily reflect the mutual performance comparison of these algorithms. Therefore, to make this comparison more quantitative, we have designed a comprehensive simulation platform, called simDSN, for both occluded and non-occluded 2D-regions. The main goal of simDSN is to make the researchers to test their algorithms for different cases against other solutions under exactly the same conditions. Thus, researchers would save time due to not implementing their simulation environment, since they could exploit the ready-to-use components, such as, node, field, obstacle and etc., of simDSN. Also, the comprehensive infrastructure of simDSN allow developers to save/load/analyze each movement of directional sensor nodes during each iteration of the simulation process, which would help to debug their algorithms.