k-coverage m-connected node placement using shuffled frog leaping: Nelder–Mead algorithm in WSN

Balancing the trade-off between cost and reliability for wireless sensor networks: a multi-objective optimized deployment method

“…[30] 2-D Heuristic Algorithm [31] Network uniformity, deployment time 2-D Heuristic Algorithm [32] Energy consumption 2-D Mathematical optimization [33] Time to calculate the fitness function 2-D Heuristic Algorithm [34] Power consumption of SNs 2-D Heuristic Algorithm [35] 2-D Graph theory, Heuristic Algorithm [36] Coverage duration 2-D Heuristic Algorithm [37] Target detection 2-D Mathematical optimization [38] Target detection 2-D Mathematical optimization [39] 2-D Heuristic Algorithm [40] The scheme of broadcast,unicast 3-D Mathematical optimization [41] Indicator of availability,time,reliability 2-D Mathematical optimization [42] 2-D Path coloring, Mathematical optimization [43] 2-D Graph theory [44] Fixed budget 2-D Heuristic Algorithm [45] Residual energy of the SNs 2-D Heuristic Algorithm [46] Sent Bytes, movement cost of SNs 2-D Mathematical optimization [47] Power assignment 2-D Heuristic Algorithm [48] The number of relay nodes 2-D Graph theory [49] The number of sensors to activate 2-D Mathematical optimization [50] 2-D Heuristic Algorithm [51] 2-D Heuristic Algorithm [52] The number of SNs 2-D Heuristic Algorithm [53] 2-D Mathematical optimization [54] 2-D Heuristic Algorithm [55] 2-D Mathematical optimization [56] 2-D Heuristic Algorithm [57] 2-D Mathematical optimization [58] The number of SNs 2-D Graph theory, Heuristic Algorithm [59] 2-D Heuristic Algorithm [60] The wakeup scheduling scheme of SNs 3-D Heuristic Algorithm [61] 3-D Heuristic Algorithm Ours…”

“…However, the proposed method can only ensure effective coverage and connectivity within a given sub-area. In [50], the Kcoverage and C-connectivity problem was handled by a mathematical model which integrated the Nelder-Mead method and the shuffled frog leading algorithm. In [51,52], the authors had proposed solutions based on a single objective heuristic algorithm, considering the minimum number of nodes, K-coverage, and C-connectivity.…”

A Novel Privacy-Preserving Mobile-Coverage Scheme Based on Trustworthiness in HWSNs

“…In communication trust, Equation (5) shows that communication trust needs to be calculated n 2 − n + 1 times on a finite filed F q , and so the computation overhead is O c = n 2 − n + 1.…”

“…A large number of network coverage optimization schemes for HWSNs had been proposed in [1][2][3][4][5][6]. Unlike the previously proposed mobile coverage schemes, our mobile coverage scheme based on privacy-preserving signature and trustworthiness can mitigate the eavesdropping and pollution attacks effectively and ensures that the network coverage will not be significantly reduced at the same time.…”

Cluster-based Coverage Scheme for Wireless Sensor Networks using Learning Automata

“…In WSNs, sensor nodes are usually distributed randomly in the environment which causes the density of nodes become high in some areas and low in some other [9,10]. The redundancy of sensor nodes in an area, firstly leads to waste the energy of some sensor nodes which causes to reduce the network lifetime and secondly, leads to overlap that area with a high probability while some areas may remain out of coverage [11][12][13][14]. Hence, in these networks in order to reduce the amount of overlap of sensor nodes and optimal coverage of the network and also reducing the energy consumption and prolonging the network lifetime, identifying the redundant nodes seems to be an essential problem [15][16][17][18].…”