A novel topology optimization of coverage-oriented strategy for wireless sensor networks

Wang, Shuxin; You, Hairong; Yue, Yinggao; Cao, Li

doi:10.1177/1550147721992298

Cited by 20 publications

(14 citation statements)

References 26 publications

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“…The data collection layer uses the RS-485 bus to connect all energy consumption monitoring points into a mixed topology node communication network [12]. The communication network combines a bus topology and a star topology.…”

Section: Data Collection Layermentioning

confidence: 99%

Design and Implementation of Energy Management System Based on Spring Boot Framework

Zhang¹,

Sun²,

Zheng³

et al. 2021

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This paper designs and implements an energy management system based on the Spring Boot framework. The system mainly includes three layers, which are the data collection layer, the business logic layer, and the display interface layer from bottom to top. The data collection layer is based on the RS-485 electrical standard and the MODBUS communication protocol. The two protocols connect all energy consumption monitoring points into a mixed topology communication network in the enterprise. The programs in the data collection layer poll each energy consumption monitoring point in the network to collect the data and transmit to the business logic layer. The business logic layer is developed on the basis of the Spring Boot framework and mainly includes two parts: the MySQL database and Tomcat server. In the MySQL database, the stored data are horizontally split according to the time column and stored in different data tables. The split of data reduces the load of a single data table and improves the query performance of the database. The Tomcat server is built into the Spring Boot framework to provide a basic environment for system operation. The Spring Boot framework is the core component of the system. It is responsible for collecting, storing, and analyzing data from energy consumption monitoring points, receiving and processing data requests from the display interface layer. It also provides standard data interfaces to the external programs. The display interface layer is developed on the basis of the Vue framework and integrated into the Spring Boot framework. The display layer combines an open-source visualization chart library called ECharts to provide users with a fully functional and friendly human–computer interaction interface. Through the calculation of hardware and software costs, considering the personnel cost in different regions, the total cost of the energy management system can be estimated. The cost of construction was approximately 210,000 USD in this paper. Since the system was actually deployed in a manufacturing company in December 2019, it has been operating stably for more than 600 days.

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Section: Data Collection Layermentioning

confidence: 99%

Design and Implementation of Energy Management System Based on Spring Boot Framework

Zhang¹,

Sun²,

Zheng³

et al. 2021

Information

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“…In order to improve the efficiency and reliability of data communication, Gupta et al [10] studied the n-dimensional hypercube network on the chip topology. Wang et al [11] proposed a network topology optimization strategy based on wolf pack algorithm to solve the optimization problem of wireless sensor networks in complex industrial application environments. Li et al [12] proposed a scheduling algorithm based on energy balance, which can extend the life of the entire network while ensuring energy balance.…”

Section: Ntroductionmentioning

confidence: 99%

An Invulnerability Algorithm for Wireless Sensor Network's Topology Based on Distance and Energy

Chen

Liu

et al. 2021

Teh. vjesn.

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“…When monitoring pipelines, the main challenge is energy consumption because sensor nodes are deployed in the soil. This creates restrictions such as poor data transmission and data loss 22 , 23 . Also, this underground environment imposes major limitations on sensor nodes, especially poor radio frequency (RF) so that the RF transmission range in soil is significantly lower than in air 24 , 25 .…”

Section: Introductionmentioning

confidence: 99%

An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things

Rahmani

Ali

Malik

et al. 2022

Sci Rep

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Pipelines are the safest tools for transporting oil and gas. However, the environmental effects and sabotage of hostile people cause corrosion and decay of pipelines, which bring financial and environmental damages. Today, new technologies such as the Internet of Things (IoT) and wireless sensor networks (WSNs) can provide solutions to monitor and timely detect corrosion of oil pipelines. Coverage is a fundamental challenge in pipeline monitoring systems to timely detect and resolve oil leakage and pipeline corrosion. To ensure appropriate coverage on pipeline monitoring systems, one solution is to design a scheduling mechanism for nodes to reduce energy consumption. In this paper, we propose a reinforcement learning-based area coverage technique called CoWSN to intelligently monitor oil and gas pipelines. In CoWSN, the sensing range of each sensor node is converted to a digital matrix to estimate the overlap of this node with other neighboring nodes. Then, a Q-learning-based scheduling mechanism is designed to determine the activity time of sensor nodes based on their overlapping, energy, and distance to the base station. Finally, CoWSN can predict the death time of sensor nodes and replace them at the right time. This work does not allow to be disrupted the data transmission process between sensor nodes and BS. CoWSN is simulated using NS2. Then, our scheme is compared with three area coverage schemes, including the scheme of Rahmani et al., CCM-RL, and CCA according to several parameters, including the average number of active sensor nodes, coverage rate, energy consumption, and network lifetime. The simulation results show that CoWSN has a better performance than other methods.

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A novel topology optimization of coverage-oriented strategy for wireless sensor networks

Cited by 20 publications

References 26 publications

Design and Implementation of Energy Management System Based on Spring Boot Framework

Design and Implementation of Energy Management System Based on Spring Boot Framework

An Invulnerability Algorithm for Wireless Sensor Network's Topology Based on Distance and Energy

An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things

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