scholarly journals Novel Energy-Efficient Miner Monitoring System with Duty-Cycled Wireless Sensor Networks

2012 ◽  
Vol 8 (1) ◽  
pp. 975082 ◽  
Author(s):  
Peng Guo ◽  
Tao Jiang ◽  
Kui Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Monitoring System ◽  
Data Transmission ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Media Access Control ◽  
Mac Scheme ◽  
Range Free

Target monitoring is an important application of wireless sensor networks. In this paper, we develop an energy-efficient miner monitoring system with sensor nodes. To keep monitoring miners' activities in tunnels, periodical localization and timely data transmission are both required. Since the localization and data transmission much depend on the media access control (MAC) scheme, codesign of localization and MAC scheme is actually needed for the resource-constrained system, which is seldom discussed in existing related works. Moreover, as sensor nodes form an ultra-sparse network with linear topology in tunnels, it is a challenge for existing range-free localization methods to localize targets. In this paper, we propose a localization-MAC codesign approach for the monitoring system under the environment of coal mine. With the proposed approach, the system can achieve higher localization accuracy with low energy consumption and transmission delay, compared with existing range-free localization methods for sensor nodes.

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

scholarly journals Hybrid Swarm Intelligence Energy Efficient Clustered Routing Algorithm for Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Rajeev Kumar ◽  
Dilip Kumar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Data Transmission ◽  
Energy Efficient ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Abc Algorithm ◽  
Cluster Heads

Currently, wireless sensor networks (WSNs) are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC) algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO) is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO) and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP) hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i) selection of optimal number of subregions and further subregion parts, (ii) cluster head selection using ABC algorithm, and (iii) efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS). The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively.

scholarly journals An Enhanced Cluster based Energy Efficient Optimal Routing in WSN

2021 ◽  
pp. 84-92
Author(s):  
G. Sai Krishna ◽  
Dr. D. J. Nagendra Kumar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Power Level ◽  
Optimization Techniques ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor

In recent years, Wireless sensor networks (WSNs) have been emerged as an important research area due to its wide spread application in various domains such as military sensing and tracking, environment monitoring, patient monitoring, etc. WSN also have various advantages in gathering the data also with data transmission as well. Even though WSN has such advantages, there is certain drawback related to the energy consumption for data transmission over the network. Wireless sensor networks basically depend on the availability of nodes for transmission and if some dead nodes are available on the designated path of transmission, there will be delay in communication and also will affect the energy consumptions. Also when a particular node is transmitting any data packet with high power, it may lead to interference which will affect the proper transmission of data and wastage of power as well. For power level reduction proper methodology has to be followed starting with the clustering and designing of routing protocols. We intend to develop an enhanced clustering algorithm for initial clustering of sensor nodes for data transmission. Nodes will be clustered based on working attributes. Once nodes are clustered into different groups, transmission path will be assigned. An energy efficient optimal protocol will be designed in our approach for routing to improve the energy utilization by optimal power utilization. For optimization, we can employ multi objective optimization techniques which can enhance the optimal selection of power utilization. The proposed scheme will be then compared with some existing techniques to show the efficiency of the proposed approach.

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.

scholarly journals A Survey on Energy Efficient Optimal Routing in Wireless Sensor Networks

2019 ◽  
pp. 288-296
Author(s):  
G. Mohan Ram ◽  
T. Kesava ◽  
M.V. Subba Rao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Power Level ◽  
Optimization Techniques ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor

In recent years, Wireless sensor networks (WSNs) have been emerged as an important research area due to its wide spread application in various domains such as military sensing and tracking, environment monitoring, patient monitoring, etc. WSN also have various advantages in gathering the data also with data transmission as well. Even though WSN has such advantages, there is certain drawback related to the energy consumption for data transmission over the network. Wireless sensor networks basically depend on the availability of nodes for transmission and if some dead nodes are available on the designated path of transmission, there will be delay in communication and also will affect the energy consumptions. Also, when a particular node is transmitting any data packet with high power, it may lead to interference which will affect the proper transmission of data and wastage of power as well. For power level reduction proper methodology has to be followed starting with the clustering and designing of routing protocols in WSNs. We intend to develop an enhanced clustering algorithm for initial clustering of sensor nodes for data transmission. Nodes will be clustered based on working attributes. Once nodes are clustered into different groups, transmission path will be assigned. An energy efficient optimal protocol will be designed in our approach for routing to improve the energy utilization by optimal power utilization. For optimization, we can employ multi objective optimization techniques which can enhance the optimal selection of power utilization. The proposed scheme will be then compared with some existing techniques to show the efficiency of the proposed approach.

scholarly journals Energy-efficient hierarchical routing in wireless sensor networks based on fog computing

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Ademola Philip 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

AbstractWireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the twenty-first 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 the energy consumption of sensor nodes 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. 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 algorithm that can be used to construct an 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. We are aware that in WSNs, the certainty of the sensed data collected by a sensor node can vary due to many reasons such as environmental factors, drained energy, and hardware failures.

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.

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.

An Energy Efficient Routing Approach to Enhance Coverage for Application Specific Wireless Sensor Networks using Genetic Algorithm

2019 ◽  
Vol 13 ◽  
Author(s):  
Amandeep Kaur Sohal ◽  
Ajay Kumar Sharma ◽  
Neetu Sood
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Energy Efficient ◽  
Search Algorithm ◽  
Cluster Formation ◽  
Green Computing ◽  
Wireless Sensor ◽  
Energy Efficient Routing

Background: An information gathering is a typical and important task in agriculture monitoring and military surveillance. In these applications, minimization of energy consumption and maximization of network lifetime have prime importance for green computing. As wireless sensor networks comprise of a large number of sensors with limited battery power and deployed at remote geographical locations for monitoring physical events, therefore it is imperative to have minimum consumption of energy during network coverage. The WSNs help in accurate monitoring of remote environment by collecting data intelligently from the individual sensors. Objective: The paper is motivated from green computing aspect of wireless sensor network and an Energy-efficient Weight-based Coverage Enhancing protocol using Genetic Algorithm (WCEGA) is presented. The WCEGA is designed to achieve continuously monitoring of remote areas for a longer time with least power consumption. Method: The cluster-based algorithm consists two phases: cluster formation and data transmission. In cluster formation, selection of cluster heads and cluster members areas based on energy and coverage efficient parameters. The governing parameters are residual energy, overlapping degree, node density and neighbor’s degree. The data transmission between CHs and sink is based on well-known evolution search algorithm i.e. Genetic Algorithm. Conclusion: The results of WCEGA are compared with other established protocols and shows significant improvement of full coverage and lifetime approximately 40% and 45% respectively.

scholarly journals A Data-Based Fault-Detection Model for Wireless Sensor Networks

2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Data Transmission ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensors And Actuators ◽  
Detection Model ◽  
Management Platform

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.

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