scholarly journals Optimal Energy Resources Allocation Method of Wireless Sensor Networks for Intelligent Railway Systems

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 482 ◽  
Author(s):  
Sheng Bin ◽  
Gengxin Sun
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Resources ◽  
Wireless Sensor ◽  
Resources Allocation ◽  
Railway Systems ◽  
Status Monitoring ◽  
Optimal Energy ◽  
Allocation Method ◽  
Coverage Model

The rapid increase of train speed has brought greater challenges to the safety and reliability of railway systems. Therefore, it is necessary to monitor the operation status of trains, infrastructure, and their operating environment in real time. Because the operation environment of railway systems is complex, the construction cost of wired monitoring systems is high, and it is difficult to achieve full coverage in the operation area of harsh environments, so wireless sensor networks are suitable for the status monitoring of railway systems. Energy resources of nodes are the basis of ensuring the lifecycle of wireless sensor networks, but severely restrict the sustainability of wireless sensor networks. A construction method of special wireless sensor networks for railway status monitoring, and an optimal energy resources allocation method of wireless sensor networks for intelligent railway systems are proposed in this paper. Through cluster head selection and rotating probability model, clustering generation and optimization model, and partial coverage model, the energy consumption of nodes can be minimized and balanced. The result of simulation experiment proved that the lifetime of wireless sensor networks can be maximized by the optimal energy resources allocation method based on clustering optimization and partial coverage model, based on polynomial time algorithm.

Path coverage enhancement in wireless sensor networks based on CVT model

2021 ◽  
pp. 1-13
Author(s):  
Guangxu Yu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Detection Probability ◽  
Coverage Rate ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Current Path ◽  
Coverage Model ◽  
Path Coverage ◽  
Low Coverage

In order to overcome the problems of low detection probability, low coverage uniformity and low coverage of current path coverage enhancement methods in wireless sensor networks, a new path coverage enhancement method based on CVT model is proposed in this paper. Firstly, the node perception model and network coverage model are constructed. On the basis of the node awareness model and network coverage model, CVT model is used to adjust the connection mode, density and location of nodes in wireless sensor networks, so as to improve the coverage performance of nodes in the detection area in wireless sensor networks, and realize the effective enhancement of path coverage in wireless sensor networks. Experimental results show that, compared with the traditional methods, the proposed method has high detection probability, high coverage uniformity and coverage rate, and the highest coverage rate reaches 97%, which has higher practical application performance.

scholarly journals Optimal Coverage Model in Clifford 3-Connected Wireless Sensor Networks

2011 ◽  
Vol 1 ◽  
pp. 66-70
Author(s):  
Wen Ming Cao ◽  
Tian Cheng He
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Full Coverage ◽  
Coverage Model ◽  
Optimal Deployment ◽  
Sensing Radius ◽  
Communication Radius

While moderate loss of coverage can be tolerated by WSN applications, loss of connectivity can be fatal. Moreover, since sensors are subject to unanticipated failures after deployment, it is not sufficient for a wireless sensor network to just be connected, it should be Clifford 3-connected . In this dissertation, we propose optimal deployment patterns to achieve both full coverage and Cliford 3-connectivity, and analyses their optimality for all values of , where is the communication radius and is the sensing radius.

scholarly journals An Energy-Aware Method for Selecting Cluster Heads in Wireless Sensor Networks

2020 ◽  
Vol 10 (21) ◽  
pp. 7886
Author(s):  
Atefeh Rahiminasab ◽  
Peyman Tirandazi ◽  
M. J. Ebadi ◽  
Ali Ahmadian ◽  
Mehdi Salimi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Cluster Head ◽  
Base Station ◽  
Energy Resources ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dynamic Clustering ◽  
Clustering Protocol

Wireless sensor networks (WSNs) include several sensor nodes that have limited capabilities. The most critical restriction in WSNs is energy resources. Moreover, since each sensor node’s energy resources cannot be recharged or replaced, it is inevitable to propose various methods for managing the energy resources. Furthermore, this procedure increases the network lifetime. In wireless sensor networks, the cluster head has a significant impact on system global scalability, energy efficiency, and lifetime. Furthermore, the cluster head is most important in combining, aggregating, and transferring data that are received from other cluster nodes. One of the substantial challenges in a cluster-based network is to choose a suitable cluster head. In this paper, to select an appropriate cluster head, we first model this problem by using multi-factor decision-making according to the four factors, including energy, mobility, distance to centre, and the length of data queues. Then, we use the Cluster Splitting Process (CSP) algorithm and the Analytical Hierarchy Process (AHP) method in order to provide a new method to solve this problem. These four factors are examined in our proposed approach, and our method is compared with the Base station Controlled Dynamic Clustering Protocol (BCDCP) algorithm. The simulation results show the proposed method in improving the network lifetime has better performance than the base station controlled dynamic clustering protocol algorithm. In our proposed method, the energy reduction is almost 5% more than the BCDCP method, and the packet loss rate in our proposed method is almost 25% lower than in the BCDCP method.

Sign in / Sign up

Export Citation Format

Share Document