Introduction to Algorithms
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Data Gathering Algorithms in Sensor Networks Using Energy Metrics
IEEE Transactions on Parallel and Distributed Systems
Dynamic Clustering for Acoustic Target Tracking in Wireless Sensor Networks
ICNP '03 Proceedings of the 11th IEEE International Conference on Network Protocols
Integrated coverage and connectivity configuration in wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
FTDCS '04 Proceedings of the 10th IEEE International Workshop on Future Trends of Distributed Computing Systems
Maximum lifetime routing in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Networking issues in wireless sensor networks
Journal of Parallel and Distributed Computing
Energy-efficient deployment of Intelligent Mobile sensor networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Coverage in wireless ad hoc sensor networks
IEEE Transactions on Computers
IEEE Transactions on Consumer Electronics
On demand radio frequency identification based vehicle tracking system
International Journal of Business Information Systems
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Wireless sensor networks have recently become new techniques and popular research issues. A wireless sensor network consists of a large number of sensor nodes that have the capabilities of sensing, computing and wireless transmission. Wireless sensor networks (namely WSNs) assist people in working under dangerous environments, provide long-term target observations and track on moving objects. Consequently, WSNs decrease risk and increase efficiency. Although WSNs have been studied extensively, several problems should be addressed, such as sensor-deployment policy, data aggregation/fusion issue, and data transmission issue. An efficient sensor-deployment approach could decrease cost, minimize transmission delay and reduce time complexity. Most studies have proposed the probability-based sensor-deployment policies to monitor an overall area. However, not the entire network is interested to be sensed/monitored. Monitoring of an entire area brings several disadvantages: (1) high cost of placing large number of sensors, (2) long delay of data transmission, (3) slow response and (4) unnecessary data aggregation. Furthermore, previous works were lack of considering the difference between the sensing and the transmission radii, and then yield inaccurate analysis. This work thus proposes an efficient sensor placement approach (namely ESP) for a sparse interested area with considering of obstructers that block the data transmission and sensing signal. Additionally, the issue of different radii of sensing and transmission is analyzed in detail. Numerical results demonstrate that the proposed ESP approach requires the least number of sensor nodes under various network sizes and different number of obstacles. Simulation results indicate that the number of sensor nodes decreases when the sensing or transmission radius increases. The running time of ESP, O(K^2), is also analyzed, which is better than that of the probability-based approaches, O(N^2), where K is the number of interested grids and N is the number of grids.