Evaluating energy cost of route diversity for security in wireless sensor networks

2015 ◽  
Vol 39 ◽  
pp. 44-57 ◽  
Author(s):  
Davut Incebacak ◽  
Kemal Bicakci ◽  
Bulent Tavli
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Cost ◽  
Wireless Sensor

scholarly journals EOTS: An Energy-consumption Optimization-oriented Task Scheduling Algorithm for Wireless Sensor Networks

2016 ◽  
Vol 12 (07) ◽  
pp. 59
Author(s):  
Zeyu Sun ◽  
Yuanbo Li ◽  
Chuanfeng Li ◽  
Yalin Nie
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Task Scheduling ◽  
Energy Cost ◽  
Iterative Refinement ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Utilization Rate ◽  
Energy Consumption Optimization

<p><span style="font-family: Times New Roman;"><strong>The mismatch of task scheduling results in rapid network energy consumption during data transmission in wireless sensor networks. To address this issue, the paper proposed an </strong><strong>E</strong><strong>nergy-consumption </strong><strong>O</strong><strong>ptimization-oriented </strong><strong>T</strong><strong>ask </strong><strong>S</strong><strong>cheduling </strong><strong>A</strong><strong>lgorithm (EOTS algorithm) which formally described the overall power dissipation in the network system. On this basis, a network model was built up such that both the idle energy consumption in sensor nodes and energy consumption during the execution of tasks were taken into account, with which the whole task was effectively decomposed into sub-task sequences. They underwent simulated annealing and iterative refinement, with the intention of improving sensor nodes’ utilization rate, reducing local idle energy cost, as well as cutting down the overall energy consumption accordingly. The experiment result shows that under the environment of multi-task operation, from the perspective of energy cost optimization, the proposed scheduling strategy recorded an increase of 21.24% compared with the FIFO algorithm, and an increase of 16.77% in comparison to the EMRSA algorithm; while in light of network lifetimes, the EOTS algorithm surpassed the ECTA algorithm by a gain of 19.21%. Therefore, the effectiveness of the proposed EOTS algorithm is verified.</strong></span></p>

PACMLA: A Localization Algorithm Based on Permutation and Combination Midnormal for Wireless Sensor Networks

2013 ◽  
Vol 475-476 ◽  
pp. 564-568
Author(s):  
Wei Yong Jiang ◽  
Pin Wan ◽  
Yong Hua Wang ◽  
Dong Liang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Cost ◽  
Wireless Sensor ◽  
Data Sets ◽  
Localization Algorithm ◽  
Anchor Nodes ◽  
Unknown Node ◽  
Number Of Iterations ◽  
Range Free

Localization of sensors is one key technique in wireless sensor networks (WSN).Because the midnormal-based localization algorithm (MBLA) has shortcomings such as low accuracy, relatively large number of iterations, a localization algorithm based on permutation and combination midnormal (PACMLA) for WSN is proposed. Nodes are divided into anchor nodes and unknown nodes. In its own communication range, unknown node can communicate with anchor nodes. In PACMLA algorithm, the unknown node communicates with the anchor nodes in turn, and collects their coordinate information and RSSI value. Then by comparing the RSSI values received by unknown node, these RSSI values are formed an array in accordance with the order from small to large. Then starting from the first value of the RSSI array, each of these values and the value behind them will be combined into data sets. Finally, according to corresponding coordinate information of the RSSI value in the data sets, we will determine the position of the unknown node by Point In Which Side (PIWS) determination. In addition, our algorithm is a kind of Range-free algorithm, and it can cuts down the node energy cost. The experiment results illustrate that the PACMLA algorithm has lower error and higher accuracy.

scholarly journals An Energy-Efficient Coverage Enhancement Strategy for Wireless Sensor Networks Based on a Dynamic Partition Algorithm for Cellular Grids and an Improved Vampire Bat Optimizer

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 619 ◽  
Author(s):  
Xiaoqiang Zhao ◽  
Yanpeng Cui ◽  
Zheng Guo ◽  
Zhanjun Hao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Assignment Problem ◽  
Energy Cost ◽  
Task Assignment ◽  
Residual Energy ◽  
Coverage Rate ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Vampire Bat

Sensor nodes perform missions based on the effectual invariable coverage of events, and it is commonly guaranteed by the determinate deployment for sensor nodes who deviate from the optimum site frequently. To reach the optimal coverage effect with the lowest costs is a primary goal of wireless sensor networks. In this paper, by splicing the sensing area optimally with cellular grids, the best deployment location for sensors and the required minimum number of them are revealed. The optimization problem of coverage rate and energy consumption is converted into a task assignment problem, and a dynamic partition algorithm for cellular grids is also proposed to improve the coverage effect when the number of sensors is variable. Furthermore, on the basis of solving the multi-objective problem of reducing and balancing the energy cost of sensors, the vampire bat optimizer is improved by introducing virtual bats and virtual preys, and finally solves the asymmetric assignment problem once the number of cellular grids is not equal to that of sensors. Simulation results indicate that the residual energy of sensors during redeployment is balanced notably by our strategy when compared to three other popular coverage-enhancement algorithms. Additionally, the total energy cost of sensor nodes and coverage rate can be optimized, and it also has a superior robustness when the number of nodes changes.

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