Sensor scheduling for confident information coverage in wireless sensor networks

Deng, Xianjun; Wang, Bang; Wang, Nuoya; Liu, Wenyu; Mo, Yijun

doi:10.1109/wcnc.2013.6554705

Cited by 14 publications

(6 citation statements)

References 15 publications

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“…Table II lists the simulation parameters and their values. We first compare our algorithm priority-based greedy scheduling (PGS) with a mostly related algorithm. The greedy sensor scheduling (GSS) [13] is the first algorithm dealing with sensor activity scheduling for confident information coverage. In each slot, it selects the node with the greatest contribution of decreasing RMSE among all the available nodes to cover a reconstruction point.…”

Section: Simulation Resultsmentioning

confidence: 99%

Priority-Based Greedy Scheduling for Confident Information Coverage in Energy Harvesting Wireless Sensor Networks

Xiong

Wang

Wang³

2015

2015 11th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)

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An important issue in Wireless Sensor Networks (WSNs) is to maximize the network lifetime while guaranteeing the desired coverage requirement. Recent studies have demonstrated that using rechargeable sensor nodes with energy harvesting capability has a great potential to extend the network lifetime. However, due to the high cost of rechargeable nodes, equipping every node with an energy harvesting unit is not practical in a large scale WSN. In this paper, we study the problem of maximizing the network lifetime of a hybrid WSN consisting of both common nodes and rechargeable nodes. Furthermore, we consider a new confident information coverage model which is more efficient for environment monitoring applications. We propose a novel priority-based greedy scheduling (PGS) algorithm to schedule the sensor nodes into a series of set covers that are activated sequentially, each satisfying the required coverage. Also, it can effectively exploit the advantages of using collaboration among sensors for the coverage requirement. Our simulations validate that the PGS algorithm can provide substantial performance improvement as compared to other peer algorithms.

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Section: Simulation Resultsmentioning

confidence: 99%

Priority-Based Greedy Scheduling for Confident Information Coverage in Energy Harvesting Wireless Sensor Networks

Xiong

Wang

Wang³

2015

2015 11th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)

Self Cite

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“…For a randomly deployed WSN with some redundant sensors, Deng et al have proposed two heuristic algorithms to schedule single model sensors and multi-modal sensors for confident information coverage to prolong the network lifetime [22] [23]. To the best of our knowledge, we are the first one to study the optimal placement pattern to fully cover an unbounded plane based on the CIC model.…”

Section: Related Workmentioning

confidence: 99%

The Optimal Placement Pattern for Confident Information Coverage in Wireless Sensor Networks

Zhu

Wang

2016

IEEE Trans. on Mobile Comput.

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Finding the optimal placement pattern to provide complete area coverage is of great theoretical and practical significance. Most of the current studies on placement problem are based on the simplest disk coverage model. In this paper, we study the optimal placement pattern based on the confident information coverage (CIC or Φ-coverage) model [1], which is much more complicated than the disk coverage model. Based on the reconstruction theory, the CIC model takes into consideration of not only the collaboration of sensors for information processing but also the spatial correlation of physical phenomena. We first analyze Φ-coverage of one sensor and two sensors, and then Φcoverage of n sensors for n ≥ 3, where n sensors are deployed at n vertices of a regular n-sided polygon. We prove that the regular triangular lattice is the optimal placement pattern among all the placement patterns consisting of regular polygons. We also extend our analysis to acute cyclic polygons, and prove that the regular triangular lattice is still the optimal placement pattern among all the placement patterns consisting of acute cyclic polygons.

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“…But the algorithm has to be used in indoor and urban applications, with poor practicability in complex terrain outdoor. Deng X. had similar shortcomings in their proposed algorithm in [23]. Jin M. [24] introduced the general function to measure the uncertainty of the monitoring data to quantify the optimal surface coverage problem (OSCP) in terms of perceived quality, and finally proposed a series of practical algorithm.…”

Section: B Three-dementional Surface Coveragementioning

confidence: 99%

“…Based on the features of FoI, the coverage problem is divided into target coverage, barrier coverage and area coverage [10] [23]. This paper studies the problem of deterministic area coverage, more specifically, is the coverage problem of 3D surface (OSCP).…”

Section: A Problem Descriptionmentioning

confidence: 99%

Improved Chemical Reaction Optimization algorithm for 3D complex surface coverage

Fan

Zhao

Cheng

2016

2016 IEEE 13th International Conference on Networking, Sensing, and Control (ICNSC)

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Deployment of wireless sensor networks on 3D complex surface is an important and fundamental issue to be solved. The existing studies focus on the plane coverage and 3D coverage under ideal conditions. An important flaw of their algorithms is poor in flexibility and operability, and not considering the economic cost factor of nodes. To this end, this article presents an elevation map based an intelligence node deployment method in the complex surface. Firstly, we propose a practical sensing model. Secondly, we extract Field of Interest from the terrain map and make Delaunay triangulation. At last, we tackle the NP complete problem based on Improved Chemical Reaction Optimization algorithm. Experiments verify and evaluate the effectiveness of our method.

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Sensor scheduling for confident information coverage in wireless sensor networks

Cited by 14 publications

References 15 publications

Priority-Based Greedy Scheduling for Confident Information Coverage in Energy Harvesting Wireless Sensor Networks

Priority-Based Greedy Scheduling for Confident Information Coverage in Energy Harvesting Wireless Sensor Networks

The Optimal Placement Pattern for Confident Information Coverage in Wireless Sensor Networks

Improved Chemical Reaction Optimization algorithm for 3D complex surface coverage

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