Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

2020 ◽  
Vol 10 ◽  
Author(s):  
Chinedu Duru ◽  
Neco Ventura ◽  
Mqhele Dlodlo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Remote Monitoring ◽  
Linear Array ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Pipeline Monitoring

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research have also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed a distance apart from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs) which over the years have seen themselves being applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrate that groups containing small number of nodes with a corresponding sink node is the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it is discovered that energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink servicing each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This therefore means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of a LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.

An Opportunistic Large Array Concentric Geographic Routing Algorithm with a Relay Node in Wireless Sensor Networks

2015 ◽  
Vol 764-765 ◽  
pp. 838-842
Author(s):  
Young Long Chen ◽  
Yung Chi Chang ◽  
Yu Ling Zeng
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Algorithm ◽  
Geographic Routing ◽  
Sensor Nodes ◽  
Source Node ◽  
Wireless Sensor ◽  
Sink Node ◽  
Large Array

Wireless sensor networks (WSNs) are a group of wireless sensor nodes, those sensor nodes with sensing and monitoring of environmental information. Energy consumption is an important topic; the node's power is limited. Therefore, we proposed an Opportunistic Large Array Concentric Geographic Routing Algorithm (OLACGRA) to reduce the node’s energy consumption and analysis the characteristic of energy model. The sink position of our proposed OLACGRA is at the center of concentric topology architecture. The source node wants to transmit data that it needs to calculate the distance between source node and sink node. If this distance bigger than threshold value, we use the multi-hop manner. Otherwise, source node transmits data to sink node directly. Simulation results show that our proposed algorithm can effectively reduce the node’s energy consumption.

scholarly journals Monitoring square and circular fields with sensors using energy-efficient cluster-based routing for underwater wireless sensor networks

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771718 ◽  
Author(s):  
Arshad Sher ◽  
Nadeem Javaid ◽  
Irfan Azam ◽  
Hira Ahmad ◽  
Wadood Abdul ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Search Algorithm ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Energy Efficient Clustering

In this article, to monitor the fields with square and circular geometries, three energy-efficient routing protocols are proposed for underwater wireless sensor networks. First one is sparsity-aware energy-efficient clustering, second one is circular sparsity-aware energy-efficient clustering, and the third one is circular depth–based sparsity-aware energy-efficient clustering routing protocol. All three protocols are proposed to minimize the energy consumption of sparse regions, whereas sparsity search algorithm is proposed to find sparse regions and density search algorithm is used to find dense regions of the network field. Moreover, clustering is performed in dense regions to minimize redundant transmissions of a data packet, while sink mobility is exploited to collect data from sensor nodes with an objective of minimum energy consumption. A depth threshold [Formula: see text] value is also used to minimize number of hops between source and destination for less energy consumption. Simulation results show that our schemes perform better than their counter-part schemes (depth-based routing and energy-efficient depth-based routing) in terms of energy efficiency.

scholarly journals Reliability and Energy Efficiency of DEAR Protocol with Cooperative Caching in IEEE802.15.4 based large ubiquitous Wireless Sensor Networks

2019 ◽  
Vol 9 (2) ◽  
pp. 2140-2145
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Reliability ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cooperative Caching ◽  
Sink Node ◽  
Energy Aware ◽  
The Impact

Reliability and Energy Consumption issues in large ubiquitous Wireless Sensor Networks are a cause of concern especially because there is an inherent conflict between the two: an increase in reliability usually leads to an increase in energy consumption. Conversely, energy conservation has been a priority research concern in wireless sensor nodes. Data aggregation from various nodes and its transmission to the sink node through multiple hops which is important for network reliability increases the overall energy consumption in the network. Several schemes were proposed in the past to address the reliability needs and also to minimize the energy consumption in the network. In this context, this paper proposes a novel strategy for IEEE802.15.4/ZigBee based networks by incorporating a Distributed Energy Aware Routing (DEAR) protocol with a localized Cooperative Caching algorithm that addresses the query generated by a requester node or sink node with datum already existing in the locally available cache memory or in the memory of its one-hop neighbors or by the source node. The DEAR protocol considers battery level as a key factor to include nodes in its routing path. The proposed model is evaluated on the basis of three scenarios which were considered to illustrate the impact of energy consumption on the reliability of WSNs.

Improved DV-Hop Localization Scheme for Randomly Deployed WSNs

2020 ◽  
Vol 10 (1) ◽  
pp. 94-109 ◽  
Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Research Area ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Anchor Nodes ◽  
Least Energy ◽  
Range Free

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.

scholarly journals Calculating the Number of Cluster Heads Based on the Rate-Distortion Function in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Mingxin Yang ◽  
Jingsha He ◽  
Yuqiang Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Rate Distortion ◽  
Distortion Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Cluster Heads

Due to limited resources in wireless sensor nodes, energy efficiency is considered as one of the primary constraints in the design of the topology of wireless sensor networks (WSNs). Since data that are collected by wireless sensor nodes exhibit the characteristics of temporal association, data fusion has also become a very important means of reducing network traffic as well as eliminating data redundancy as far as data transmission is concerned. Another reason for data fusion is that, in many applications, only some of the data that are collected can meet the requirements of the sink node. In this paper, we propose a method to calculate the number of cluster heads or data aggregators during data fusion based on the rate-distortion function. In our discussion, we will first establish an energy consumption model and then describe a method for calculating the number of cluster heads from the point of view of reducing energy consumption. We will also show through theoretical analysis and experimentation that the network topology design based on the rate-distortion function is indeed more energy-efficient.

scholarly journals Energy Consumption Based Low Energy Aware Gateway (LEAG) Protocol in Wireless Sensor Networks

2019 ◽  
Vol 8 (5S3) ◽  
pp. 128-132 ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Cluster Head ◽  
Base Station ◽  
Low Energy ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware

Wireless Sensor Networks (WSN) consists of a large amount of nodes connected in a self-directed manner. The most important problems in WSN are Energy, Routing, Security, etc., price of the sensor nodes and renovation of these networks is reasonable. The sensor node tools included a radio transceiver with an antenna and an energy source, usually a battery. WSN compute the environmental conditions such as temperature, sound, pollution levels, etc., WSN built the network with the help of nodes. A sensor community consists of many detection stations known as sensor nodes, every of which is small, light-weight and portable. Nodes are linked separately. Each node is linked into the sensors. In recent years WSN has grow to be an essential function in real world. The data’s are sent from end to end multiple nodes and gateways, the data’s are connected to other networks such as wireless Ethernet. MGEAR is the existing mechanism. It works with the routing and energy consumption. The principal problem of this work is choosing cluster head, and the selection is based on base station, so the manner is consumes energy. In this paper, develop the novel based hybrid protocol Low Energy Aware Gateway (LEAG). We used Zigbee techniques to reduce energy consumption and routing. Gateway is used to minimize the energy consumption and data is send to the base station. Nodes are used to transmit the data into the cluster head, it transmit the data into gateway and gateway compress and aggregate the data then sent to the base station. Simulation result shows our proposed mechanism consumes less energy, increased throughput, packet delivery ration and secure routing when compared to existing mechanism (MGEAR).

scholarly journals Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Energy Efficient ◽  
Fog Computing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hierarchical Routing

Abstract Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime

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.

Nature-Inspired Algorithms in Wireless Sensor Networks

2019 ◽  
pp. 246-275
Author(s):  
Ajay Kaushik ◽  
S. Indu ◽  
Daya Gupta
Keyword(s):  
Wireless Sensor Networks ◽  
Big Data ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Sensor Node ◽  
Optimization Problem ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Nature Inspired Algorithms

Wireless sensor networks (WSNs) are becoming increasingly popular due to their applications in a wide variety of areas. Sensor nodes in a WSN are battery operated which outlines the need of some novel protocols that allows the limited sensor node battery to be used in an efficient way. The authors propose the use of nature-inspired algorithms to achieve energy efficient and long-lasting WSN. Multiple nature-inspired techniques like BBO, EBBO, and PSO are proposed in this chapter to minimize the energy consumption in a WSN. A large amount of data is generated from WSNs in the form of sensed information which encourage the use of big data tools in WSN domain. WSN and big data are closely connected since the large amount of data emerging from sensors can only be handled using big data tools. The authors describe how the big data can be framed as an optimization problem and the optimization problem can be effectively solved using nature-inspired algorithms.

Energy Efficient Image Compression and Transmission in WSN

2016 ◽  
pp. 67-78
Author(s):  
Wajeeha Aslam ◽  
Muazzam A. Khan ◽  
M. Usman Akram ◽  
Nazar Abbas Saqib ◽  
Seungmin Rho
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Image Compression ◽  
Sensor Network ◽  
Image Data ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life

Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.

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