An Improved Control for Large-Scale Wireless Sensor Networks

2011 ◽  
Vol 474-476 ◽  
pp. 2315-2319
Author(s):  
Shuang Xia Han ◽  
Lu Zhang ◽  
Jian Wen Fang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Control Strategy ◽  
Topology Control ◽  
Control Algorithm ◽  
Large Scale ◽  
Data Communication ◽  
Communication Strategy ◽  
Wireless Sensor ◽  
Reliability Control

A 3-layer topology is proposed to solve the problem of the incompatibility of the traditional topology structure in large-scale WSN. The data communication strategy for each level have been analysed, and an topology control algorithm for top-level is brought up based on the bottleneck-nodes, which will provide higher reliability control for the key-level. The experimental results indicated that, the new topology control strategy will contribute to balance the communication load of the nodes, and the energy consumption in the key-level reduce remarkably.

An Energy-Balance Based Distributed Topology Control Algorithm for Wireless Sensor Networks

2012 ◽  
Vol 490-495 ◽  
pp. 1392-1396 ◽  
Author(s):  
Chu Hang Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Topology Control ◽  
Control Algorithm ◽  
Path Loss ◽  
Network Connectivity ◽  
Premature Death ◽  
Residual Energy ◽  
Wireless Sensor

Topology control is an efficient approach which can reduce energy consumption for wireless sensor networks, and the current algorithms mostly focus on reducing the nodes’ energy consumption by power adjusting, but pay little attention to balance energy consumption of the whole network, which results in premature death of many nodes. Thus, a distributed topology control algorithm based on path-loss and residual energy (PRTC) is designed in this paper. This algorithm not only maintains the least loss links between nodes but also balances the energy consumption of the network. The simulation results show that the topology constructed by PRTC can preserve network connectivity as well as extend the lifetime of the network and provide good performance of energy consumption.

scholarly journals An Enhanced Heterogeneous Gateway-Based Energy-Aware Multi-hop Routing Protocol for Wireless Sensor Networks

2022 ◽  
Author(s):  
Fuseini Jibreel ◽  
Emmanuel Tuyishimire ◽  
I M Daabo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Base Station ◽  
Communication Strategy ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Routing Scheme

Wireless Sensor Networks (WSNs) continue to provide essential services for various applications such as surveillance, data gathering, and data transmission from the hazardous environments to safer destinations. This has been enhanced by the energy-efficient routing protocols that are mostly designed for such purposes. Gateway-based Energy-Aware Multi-hop Routing protocol (MGEAR) is one of the homogenous routing schemes that was recently designed to more efficiently reduce the energy consumption of distant nodes. However, it has been found that the protocol has a high energy consumption rate, lower stability period, less data transmission to the Base station (BS). In this paper, an enhanced Heterogeneous Gateway-based Energy-Aware multi-hop routing protocol ( HMGEAR) is proposed. The proposed routing scheme is based on the introduction of heterogeneous nodes in the existing scheme, selection of the head based on the residual energy, introduction of multi-hop communication strategy in all the regions of the network, and implementation of energy hole elimination technique. Results show that the proposed routing scheme outperforms two existing ones.

Efficient Energy Conservation and Faulty Node Detection on Machine Learning-Based Wireless Sensor Networks

2021 ◽  
Vol 13 (2) ◽  
pp. 1-20
Author(s):  
Amarasimha T. ◽  
V. Srinivasa Rao
Keyword(s):  
Machine Learning ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Communication ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Support Vector ◽  
Faulty Node

Wireless sensor networks are used in machine learning for data communication and classification. Sensor nodes in network suffer from low battery power, so it is necessary to reduce energy consumption. One way of decreasing energy utilization is reducing the information transmitted by an advanced machine learning process called support vector machine. Further, nodes in WSN malfunction upon the occurrence of malicious activities. To overcome these issues, energy conserving and faulty node detection WSN is proposed. SVM optimizes data to be transmitted via one-hop transmission. It sends only the extreme points of data instead of transmitting whole information. This will reduce transmitting energy and accumulate excess energy for future purpose. Moreover, malfunction nodes are identified to overcome difficulties on data processing. Since each node transmits data to nearby nodes, the misbehaving nodes are detected based on transmission speed. The experimental results show that proposed algorithm provides better results in terms of reduced energy consumption and faulty node detection.

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