scholarly journals Optimization-Based Approaches for Minimizing Deployment Costs for Wireless Sensor Networks with Bounded Estimation Errors

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7121
Author(s):  
Chiu-Han Hsiao ◽  
Frank Yeong-Sung Lin ◽  
Hao-Jyun Yang ◽  
Yennun Huang ◽  
Yu-Fang Chen ◽  
...  

As wireless sensor networks have become more prevalent, data from sensors in daily life are constantly being recorded. Due to cost or energy consumption considerations, optimization-based approaches are proposed to reduce deployed sensors and yield results within the error tolerance. The correlation-aware method is also designed in a mathematical model that combines theoretical and practical perspectives. The sensor deployment strategies, including XGBoost, Pearson correlation, and Lagrangian Relaxation (LR), are determined to minimize deployment costs while maintaining estimation errors below a given threshold. Moreover, the results significantly ensure the accuracy of the gathered information while minimizing the cost of deployment and maximizing the lifetime of the WSN. Furthermore, the proposed solution can be readily applied to sensor distribution problems in various fields.

Trust is critical in remote sensor systems to exchange the information from source to goal. The Dynamic Source Protocol computes the substitute way, if any hub neglects to exchange the information. The Dynamic Source Protocol does not have any worked in usefulness to figure a substitute way if the way has a vindictive hub. With the cost of an interloper recognition framework we can identify the vindictive hub and modify the information/parcel exchange way. Notwithstanding, gatecrasher location framework is extremely costly for remote sensor systems and there is no certification in identifying a malevolent hub. In the ebb and flow look into a trust-based approach is prescribed to limit the overheads of gatecrasher location framework and it likewise recognizes the anomalous conduct hubs. The proposed demonstrate utilizes the rehashed recreations to distinguish flawed hubs through the agreeable exertion in the sensor organize and additionally judges the trust of progressive hubs. Reenactments were exhibited for standardized result of parcel dropping, normal rebate result, and trust connection.


Author(s):  
Shirin Khezri ◽  
Karim Faez ◽  
Amjad Osmani

Adequate coverage is one of the main problems for Sensor Networks. The effectiveness of distributed wireless sensor networks highly depends on the sensor deployment scheme. Optimizing the sensor deployment provides sufficient sensor coverage and saves cost of sensors for locating in grid points. This article applies the modified binary particle swarm optimization algorithm for solving the sensor placement in distributed sensor networks. PSO is an inherent continuous algorithm, and the discrete PSO is proposed to be adapted to discrete binary space. In the distributed sensor networks, the sensor placement is an NP-complete problem for arbitrary sensor fields. One of the most important issues in the research fields, the proposed algorithms will solve this problem by considering two factors: the complete coverage and the minimum costs. The proposed method on sensors surrounding is examined in different area. The results not only confirm the successes of using the new method in sensor placement, also they show that the new method is more efficiently compared to other methods like Simulated Annealing(SA), PBIL and LAEDA.


Author(s):  
Lina M. Pestana Leão de Brito ◽  
Laura M. Rodríguez Peralta

As with many technologies, defense applications have been a driver for research in sensor networks, which started around 1980 due to two important programs of the Defense Advanced Research Projects Agency (DARPA): the distributed sensor networks (DSN) and the sensor information technology (SensIT) (Chong & Kumar, 2003). However, the development of sensor networks requires advances in several areas: sensing, communication, and computing. The explosive growth of the personal communications market has driven the cost of radio devices down and has increased the quality. At the same time, technological advances in wireless communications and electronic devices (such as low-cost, low-power, small, simple yet efficient wireless communication equipment) have enabled the manufacturing of sensor nodes and, consequently, the development of wireless sensor networks (WSNs).


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