Interference mitigation in point to point wireless sensor networks using LSP protocol and time division multiplexing approach

2020 ◽  
Vol 39 (4) ◽  
pp. 5449-5458
Author(s):  
A. Arokiaraj Jovith ◽  
S.V. Kasmir Raja ◽  
A. Razia Sulthana
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Control Parameter ◽  
Interference Mitigation ◽  
Wireless Sensor ◽  
Point To Point ◽  
A Minor ◽  
Two Stages ◽  
Time Division ◽  
And Control

Interference in Wireless Sensor Network (WSN) predominantly affects the performance of the WSN. Energy consumption in WSN is one of the greatest concerns in the current generation. This work presents an approach for interference measurement and interference mitigation in point to point network. The nodes are distributed in the network and interference is measured by grouping the nodes in the region of a specific diameter. Hence this approach is scalable and isextended to large scale WSN. Interference is measured in two stages. In the first stage, interference is overcome by allocating time slots to the node stations in Time Division Multiple Access (TDMA) fashion. The node area is split into larger regions and smaller regions. The time slots are allocated to smaller regions in TDMA fashion. A TDMA based time slot allocation algorithm is proposed in this paper to enable reuse of timeslots with minimal interference between smaller regions. In the second stage, the network density and control parameter is introduced to reduce interference in a minor level within smaller node regions. The algorithm issimulated and the system is tested with varying control parameter. The node-level interference and the energy dissipation at nodes are captured by varying the node density of the network. The results indicate that the proposed approach measures the interference and mitigates with minimal energy consumption at nodes and with less overhead transmission.

Hybrid Combination of GIS,GPS,WSN and GPRS Technology in Modern Digital Agriculture Application

2010 ◽  
Vol 108-111 ◽  
pp. 1158-1163 ◽  
Author(s):  
Peng Cheng Nie ◽  
Di Wu ◽  
Weiong Zhang ◽  
Yan Yang ◽  
Yong He
Keyword(s):  
Large Scale ◽  
Field Application ◽  
Wireless Sensor ◽  
Information Collection ◽  
Scale Field ◽  
Large Scale Field ◽  
Field Information ◽  
Intelligent Management ◽  
Digital Agriculture ◽  
And Control

In order to improve the information management of the modern digital agriculture, combined several modern digital agriculture technologies, namely wireless sensor network (WSN), global positioning system (GPS), geographic information system (GIS) and general packet radio service (GPRS), and applied them to the information collection and intelligent control process of the modern digital agriculture. Combining the advantage of the local multi-channel information collection and the low-power wireless transmission of WSN, the stable and low cost long-distance communication and data transmission ability of GPRS, the high-precision positioning technology of the DGPS positioning and the large-scale field information layer-management technology of GIS, such a hybrid technology combination is applied to the large-scale field information and intelligent management. In this study, wireless sensor network routing nodes are disposed in the sub-area of field. These nodes have GPS receiver modules and the electric control mechanism, and are relative positioned by GPS. They can real-time monitor the field information and control the equipment for the field application. When the GPS position information and other collected field information are measured, the information can be remotely transmitted to PC by GPRS. Then PC can upload the information to the GIS management software. All the field information can be classified into different layers in GIS and shown on the GIS map based on their GPS position. Moreover, we have developed remote control software based on GIS. It can send the control commands through GPRS to the nodes which have control modules; and then we can real-time manage and control the field application. In conclusion, the unattended automatic wireless intelligent technology for the field information collection and control can effectively utilize hardware resources, improve the field information intelligent management and reduce the information and intelligent cost.

A Wireless Sensor Network Routing Algorithm Based on Zigbee

2014 ◽  
Vol 513-517 ◽  
pp. 1845-1849
Author(s):  
Hua Rui Wu ◽  
Li Zhu
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Large Scale ◽  
Routing Algorithm ◽  
Network Routing ◽  
Routing Algorithms ◽  
Wireless Sensor ◽  
Quantitative Relation ◽  
Analysis Model

Routing strategy with effective and saving energy is an important problem in the research on the application of wireless sensor network into the farmland micro climate and soil moisture monitoring,it analyzed the disadvantage of the layered tree routing algorithm and ZigBee routing algorithms in energy saving, combined with ZigBee network topology,establishing an optimal node analysis model based on fuzzy decision, bringing forward a new routing algorithm which is suitable for large-scale farmland gradient environment, this new algorithm find out the quantitative relation between energy consumption and routing node selecting strategy,which can greatly decrease the route hop number by routing discovery mechanism and create an optimum goal group. Simulation results showed that compared with the layered tree and ZigBee routing algorithms,the new routing algorithms can significantly reduce the energy consumption of routing process.

Energy-Saving Technologies of WSN

2012 ◽  
Vol 605-607 ◽  
pp. 566-569
Author(s):  
Rong Mao Zheng
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Power Supply ◽  
Sensor Node ◽  
Large Scale ◽  
Working Life ◽  
Environmental Data ◽  
Wireless Sensor ◽  
Wireless Sensor Node ◽  
Node Energy

In order to layout convenient the wireless sensor node generally used battery for power supply, the node require working up to several months or even years but battery replacement was difficult or impossible. In this paper, research does not affect the function of WSN how to save the node energy consumption, which can work more time in large-scale collection, processing and communication of complex environmental data. Results show that the energy-saving technologies can be to reduce the energy consumption of 55.6%, which can greatly extend the working life of the wireless sensor node battery.

scholarly journals Designing Constrained Trajectory Based on Maximizing Energy Reduction in Large-Scale Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jia Xu ◽  
Chuan Ping Wang ◽  
Hua Dai ◽  
Da Qiang Zhang ◽  
Jing Jie Yu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Large Scale ◽  
Mobile Sink ◽  
Energy Reduction ◽  
Wireless Sensor ◽  
Movement Trajectory ◽  
Computation Efficiency

TheMobile Sinkbased data collection in wireless sensor network can reduce energy consumption efficiently and has been a new data collection paradigm. In this paper, we focus on exploring polynomial algorithm to compute the constrained trajectory of theMobile Sinkfor data collection. We first present a universal system model for designing constrained trajectory in large-scale wireless sensor networks and formulate the problem as theMaximizing Energy Reduction for Constrained Trajectory(MERC) problem. We show that the MERC problem is NP-hard and design an approximation algorithm (CTMER), which follows the greedy approach to design the movement trajectory of theMobile Sinkby maximizing theeffective average energy reduction. Through both rigid theoretical analysis and extensive simulations, we demonstrate that our algorithm achieves high computation efficiency and is superior to otherMobile Sinkbased data collection methods in aspects of energy consumption and network lifetime.

An Energy-Efficient Data Dissemination Scheme in Large-Scale Wireless Sensor Networks

2013 ◽  
Vol 5 (3) ◽  
pp. 34-54
Author(s):  
Shiow-Fen Hwang ◽  
Han-Huei Lin ◽  
Chyi-Ren Dow
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Storage ◽  
Energy Efficient ◽  
Large Scale ◽  
Data Dissemination ◽  
Wireless Sensor ◽  
Event Data ◽  
Efficient Data

In wireless sensor networks, due to limited energy, how to disseminate the event data in an energy-efficient way to allow sinks quickly querying and receiving the needed event data is a practical and important issue. Many studies about data dissemination have been proposed. However, most of them are not energy-efficient, especially in large-scale networks. Hence, in this paper the authors proposed an energy-efficient data dissemination scheme in large-scale wireless sensor networks. First, the authors design a data storage method which disseminates only a few amount event data by dividing the network into regions and levels, and thus reducing the energy consumption. Then, the authors develop an efficient sink query forwarding strategy by probability analysis so that a sink can query events easily according to its location to reduce the delay time of querying event data, as well as energy consumption. In addition, a simple and efficient maintenance mechanism is also provided. The simulation results show that the proposed scheme outperforms TTDD and LBDD in terms of the energy consumption and control overhead.

A survey on the characterization parameters and lifetime improvement techniques of wireless sensor network

Frequenz ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Manish Kumar Singh ◽  
Syed Intekhab Amin ◽  
Amit Choudhary
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Large Scale ◽  
Distributed Source Coding ◽  
Wireless Sensor ◽  
Operational Environment ◽  
Lifetime Maximization ◽  
Resource Allocation Algorithm ◽  
Wide Range

Abstract Emerging technologies, such as the Internet of things (IoT), machine learning (ML) and machine-to-machine networks encourage deployment of large-scale wireless sensor networks (WSNs). The major problem in WSN is the limited energy of node batteries. Therefore, the efficient use of node energy for data sensing, processing and communication operations is important to maintain a fully operational network for longest period of time. Literature presents a wide range of lifetime maximization techniques for WSN such as resource allocation algorithm, clustering and routing, sleep–wake scheduling, energy harvesting, MIMO technique, Distributed source coding, genetic algorithm and sink mobility. These techniques effectively lessen the energy consumption and enhance the lifetime of the entire wireless sensor network in various applications. Besides energy consumption, the characterization parameters such as coverage and connectivity, communication and modulation schemes, operational environment, network parameters, node parameters and service parameters also have great impact on WSN performance. This paper presents a comprehensive survey of state-of-the-art research works that improves the performance of WSN by optimizing various network characterization parameters and lifetime maximization techniques. These results highlight the key issues which affects WSN performance and provide a roadmap for WSN designers for effective implementation of novel WSN strategies.

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