DOI: 10.1007/978-3-540-79353-3_6
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An Analytical Approach to the Optimal Deployment of Wireless Sensor Networks

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Cited by 6 publications
(12 citation statements)
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“…A wide variety of meta-heuristic methods have been applied to the placement problem, ranging from the genetic algorithm (GA) [23], evolution algorithm with specialized operators [24], particle swarm optimization algorithm (PSO) [25], simulated annealing algorithm (SA) [12][13][14][15], virtual force algorithm (VF) [26], and the virtual force oriented particles algorithm [27]. Other algorithms are analyzed in [16] like the artificial bee colony algorithm (ABC), ant colony optimization algorithm (ACO), and PSO for the sensor deployment problem with the target coverage.…”
Section: Related Workmentioning
confidence: 99%
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“…A wide variety of meta-heuristic methods have been applied to the placement problem, ranging from the genetic algorithm (GA) [23], evolution algorithm with specialized operators [24], particle swarm optimization algorithm (PSO) [25], simulated annealing algorithm (SA) [12][13][14][15], virtual force algorithm (VF) [26], and the virtual force oriented particles algorithm [27]. Other algorithms are analyzed in [16] like the artificial bee colony algorithm (ABC), ant colony optimization algorithm (ACO), and PSO for the sensor deployment problem with the target coverage.…”
Section: Related Workmentioning
confidence: 99%
“…Several approaches were developed to improve coverage and connectivity using the SA algorithm [12][13][14][15]. In this article, we propose a hybrid algorithm based on the Gradient method and the SA algorithm to solve the WSN placement problem while defining the optimal number of nodes to deploy, to ensure the required coverage and connectivity in the case of a deterministic deployment, where all sensor nodes positions are well controlled.…”
mentioning
confidence: 99%
“…In the authentication table, the second field of each row corresponds to a hash function executed on the bits that are not included in the first field of the row. For example, considering row 0 of the authentication table of Node 1, the bits corresponding to the indexes in the mask of Node 1 (15,12,9,6, in bold) are extracted from the 16 bits of Puk 0 (0110 0110 0110 0110), and stored in the first field of the row, while the result of a hash function computed on the other bits is stored in the second field of the row. Figure 2 shows the pairwise key establishment.…”
Section: Predeployment Phasementioning
confidence: 99%
“…If the resulting hash also corresponds to the hash stored in the same row of the table, the initiator is considered authentic. In the example, after receiving the Hello, Node 1 checks if the four bits (M 0 ) in Puk 0 at the addresses written in its mask (15,12,9,6) correspond to the four bits in the first row of its table. Then, Node 1 executes the hash (h 0 ) on the other bits of Puk 0 , by excluding bits 15, 12, 9 and 6, and checks if the result is equal to the content of the second part of row 0 in its identification table.…”
Section: Predeployment Phasementioning
confidence: 99%
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