scholarly journals PINC: Pickup Non-Critical Node Based k-Connectivity Restoration in Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6418
Author(s):  
Vahid Khalilpour Akram ◽  
Zuleyha Akusta Dagdeviren ◽  
Orhan Dagdeviren ◽  
Moharram Challenger
Keyword(s):  
Data Transmission ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Critical Groups ◽  
Critical Node ◽  
Connectivity Restoration ◽  
Critical Nodes ◽  
Communication Path ◽  
Complicated Task ◽  
Node Failures

A Wireless Sensor Network (WSN) is connected if a communication path exists among each pair of sensor nodes (motes). Maintaining reliable connectivity in WSNs is a complicated task, since any failure in the nodes can cause the data transmission paths to break. In a k-connected WSN, the connectivity survives after failure in any k-1 nodes; hence, preserving the k-connectivity ensures that the WSN can permit k-1 node failures without wasting the connectivity. Higher k values will increase the reliability of a WSN against node failures. We propose a simple and efficient algorithm (PINC) to accomplish movement-based k-connectivity restoration that divides the nodes into the critical, which are the nodes whose failure reduces k, and non-critical groups. The PINC algorithm pickups and moves the non-critical nodes when a critical node stops working. This algorithm moves a non-critical node with minimum movement cost to the position of the failed mote. The measurements obtained from the testbed of real IRIS motes and Kobuki robots, along with extensive simulations, revealed that the PINC restores the k-connectivity by generating optimum movements faster than its competitors.

scholarly journals Smart node relocation (SNR) and connectivity restoration mechanism for wireless sensor networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Mahmood ul Hassan ◽  
Khalid Mahmood ◽  
Muhammad Kashif Saeed ◽  
Shahzad Ali ◽  
Safdar Zaman ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Metrics ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Basic Operation ◽  
Efficient Operation ◽  
Connectivity Restoration ◽  
Node Failures

AbstractNode failures are inevitable in wireless sensor networks (WSNs) because sensor nodes in WSNs are miniature and equipped with small and often irreplaceable batteries. Due to battery drainage, sensor nodes can fail at any instance. Moreover, WSNs operate in hostile environments and environmental factors may also contribute to nodes failure. Failure of nodes leads to disruption of inter-node connectivity and might also lead to network partitioning. Failure to communicate with each other and with the base station can compromise the basic operation of the sensor network. For restoration of connectivity, a robust recovery mechanism is required. The existing connectivity restoration mechanisms suffer from shortcomings because they do not focus on energy-efficient operation and coverage-aware mechanisms while performing connectivity restoration. As a result, most of these mechanisms lead to the excessive mobility of nodes, which itself causes the utilization of excessive battery. In this work, we propose a novel technique called smart node relocation (SNR). SNR is capable of detecting and restoring the connectivity caused by either single or multiple node failures. For achieving energy efficiency, SNR relies on transmitting a lesser number of control packets. For achieving the goal of being coverage-aware, it tries to relocate only essential nodes while trying to restore connectivity. By performing extensive simulations, we prove that SNR outperforms the existing approaches concerning multiple performance metrics including but not limited to the total number of packets transmitted, total distance moved for connectivity restoration, the percentage reduction in field coverage.

scholarly journals PACR: Position-Aware Protocol for Connectivity Restoration in Mobile Sensor Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Rab Nawaz Jadoon ◽  
Adnan Anwar Awan ◽  
Muhammad Amir Khan ◽  
WuYang Zhou ◽  
Aqdas Naveed Malik
Keyword(s):  
Sensor Networks ◽  
Data Transmission ◽  
Recovery Process ◽  
Mobile Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Connectivity Restoration ◽  
Communication Links ◽  
Exact Position ◽  
Failed Node

Wireless Sensor Networks (WSNs) have gained global attention in recent times due to their vast applications in various fields. These networks can face the disruption of data transmission due to sensor node failures when placed in harsh, inaccessible, and adverse environments such as battlefields or monitoring in enemy territory. The specific tasks performed by the collaboration among the sensor nodes in WSNs by internode connectivity may be terminated. Besides this, due to the failure of sensor nodes, the area covered by the network may be limited, which can cause damage to the objectives for such a network, as there might be an unaware danger in the lost area. Connectivity is a big problem in mobile WSNs due to the mobility of nodes. Researchers have developed a lot of algorithms that are capable enough for connectivity problems, but they do not emphasize the loss of coverage. We try to fill these gaps by proposing the new hybrid algorithm PACR (Position-Aware protocol for Connectivity Restoration). The concept behind PACR is the same as a person who writes his will before death on a deathbed. In the same way, when the sensor energy is below the threshold, it is converted into a recovery coordinator and generates a recovery plan. This accelerates the recovery by decreasing the time needed for failure identification. For the recovery process, the neighbor’s nodes do not travel to the exact position of the failed node. Instead, they just move to the distance where they can build communication links with other nodes. This greatly prolongs the network lifetime. The simulation results show that PACR outperforms other techniques present in the literature.

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.

scholarly journals Intelligent On-Demand Connectivity Restoration for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Khalid Mahmood ◽  
Muhammad Amir Khan ◽  
Mahmood ul Hassan ◽  
Ansar Munir Shah ◽  
Shahzad Ali ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Connectivity ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
On Demand ◽  
Connectivity Restoration ◽  
Restoration Technique ◽  
Near Future

Wireless sensor networks are envisioned to play a very important role in the Internet of Things in near future and therefore the challenges associated with wireless sensor networks have attracted researchers from all around the globe. A common issue which is well studied is how to restore network connectivity in case of failure of single or multiple nodes. Energy being a scarce resource in sensor networks drives all the proposed solutions to connectivity restoration to be energy efficient. In this paper we introduce an intelligent on-demand connectivity restoration technique for wireless sensor networks to address the connectivity restoration problem, where nodes utilize their transmission range to ensure the connectivity and the replacement of failed nodes with their redundant nodes. The proposed technique helps us to keep track of system topology and can respond to node failures effectively. Thus our system can better handle the issue of node failure by introducing less overhead on sensor node, more efficient energy utilization, better coverage, and connectivity without moving the 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 Performance Analysis of Q-Leach Algorithm in WSN

2020 ◽  
Vol 5 (10) ◽  
pp. 1-4
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Short Range ◽  
Sensor Node ◽  
Life Time ◽  
Time Span ◽  
Sensor Nodes ◽  
Wireless Sensor

Sensor nodes are exceedingly energy compelled instrument, since it is battery operated instruments. In wsn network, every node is liable to the data transmission through the wireless mode [1]. Wireless sensor networks (WSN) is made of a huge no. of small nodes with confined functionality. The essential theme of the wireless sensor network is energy helpless and the WSN is collection of sensor. Every sensor terminal is liable to sensing, store and information clan and send it forwards into sink. The communication within the node is done via wireless network [3].Energy efficiency is the main concentration of a desining the better routing protocol. LEACH is a protocol. This is appropriate for short range network, since imagine that whole sensor node is capable of communication with inter alia and efficient to access sink node, which is not always correct for a big network. Hence, coverage is a problem which we attempt to resolve [6]. The main focus within wireless sensor networks is to increase the network life-time span as much as possible, so that resources can be utilizes efficiently and optimally. Various approaches which are based on the clustering are very much optimal in functionality. Life-time of the network is always connected with sensor node’s energy implemented at distant regions for stable and defect bearable observation [10].

Arrangement of Sensor Nodes for Wireless Sensor Network in Aquatic Products Breeding

2014 ◽  
Vol 989-994 ◽  
pp. 3433-3436
Author(s):  
Bing Shi ◽  
Shou Kun Xu ◽  
Jian Ming Jiang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Transmission ◽  
Pond Water ◽  
Sensor Nodes ◽  
Space Distribution ◽  
Wireless Sensor ◽  
Key Factors ◽  
Distribution Law ◽  
Water Testing

In order to overcome the disadvantages of ccomplexity of monitoring systems, inconvenience of installation for equipment and wiring, high error rate of data transmission, the technology of wireless sensor network is adopted. Through analysis of pond water testing results on the space distribution of water environmental factors, and the number and location of the sensor nodes is determined based on the distribution law of key factors. Experiments show that the system has higher accuracy and stability.

scholarly journals Qualification of Cluster Header and Cluster Member in Wireless Sensor Networks

2019 ◽  
Vol 8 (2S6) ◽  
pp. 101-105
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Sensor Node ◽  
Data Transfer ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node

Many researches have been proposed for efficiency of data transmission from sensor nodes to sink node for energy efficiency in wireless sensor networks. Among them, cluster-based methods have been preferred In this study, we used the angle formed with the sink node and the distance of the cluster members to calculate the probability of cluster head. Each sensor node sends measurement values to header candidates, and the header candidate node measures the probability value of the header with the value received from its candidate member nodes. To construct the cluster members, the data transfer direction is considered. We consider angle, distance, and direction as cluster header possibility value. Experimental results show that data transmission is proceeding in the direction of going to the sink node. We calculated and displayed the header possibility value of the neighbor nodes of the sensor node and confirmed the candidates of the cluster header for data transfer as the value. In this study, residual energy amount of each sensor node is not considered. In the next study, we calculate the value considering the residual energy amount of the node when measuring the header possibility value of the cluster.

scholarly journals Secured Data Transmission and Malicious Node Detection in Wireless Sensor Network

2019 ◽  
Vol 8 (6) ◽  
pp. 1062-1069
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Transmission ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Malicious Nodes ◽  
Secure Data Transmission ◽  
Fuzzy C Means Clustering

Wireless Sensor Network (WSN) is developed extremely because of their low installation cost and various applications. WSN has compact and inexpensive sensor nodes for monitoring the physical environment. WSNs are susceptible to many attacks (e.g. malicious nodes) because of its distinct characteristics. The performance of node and network is affected by the malicious nodes. Moreover, the communication among the sensor nodes also required to be secured for preventing the data from the hackers. In this paper, the architecture of the WSN is generated by using the Fuzzy-C-Means clustering (FCM). Then the detection of the malicious nodes is performed by using the Acknowledgement Scheme (AS). This AS is integrated in the Ant Colony Optimization (ACO) based routing for avoiding the malicious nodes while generating the route from the source to the Base Station (BS). Then the Hybrid Encryption Algorithm (HEA) is used for performing the secure data transmission through the network and this proposed method is named as HEA-AS. The performance of the HEA-AS method is evaluated in terms of End to End Delay (EED), network lifetime, throughput, Packet Delivery Ratio (PDR) and Packet Loss Ratio (PLR). The proposed HEA-AS method is compared with the existing method called as CTCM to evaluate the effectiveness of the HEA-AS method.

scholarly journals A wireless sensor network for high-tech agriculture

2020 ◽  
Vol 3 (4) ◽  
pp. 259-270
Author(s):  
Nhan Chi Nguyen ◽  
Hoang Huy Nguyen ◽  
Tuan Ngoc Pham
Keyword(s):  
Wireless Sensor Network ◽  
Power Consumption ◽  
Low Power ◽  
Sensor Network ◽  
Data Transmission ◽  
Urban Environments ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
High Tech ◽  
Area Network

This paper presents the design of wireless sensor network (WSN) based on low-power wide area network technology for high-tech agriculture. This WSN allows the farmer to collect data such as air temperature, air humidity, soil moisture. The WSN system consists of components: 02 wireless sensor nodes, 01 gateway, 01 cloud server and smartphone app. This WSN tested for data transmission in two zones: zone 1 (dense urban environments) at a distance of 500m and zone 2 (urban environments - less obstacles) at a distance of 1,500m and 1,700m. The data collected at different times of the day and updated every 15 minutes. The results show that the wireless sensor network system operates stably, data constantly updated to LoRa Server and there was not data packet loss. The power consumption of sensor node and gateway determined in three operating modes: transmitting, receiving, turn-off. This shows the advantages of LoRa technology in the development of wireless sensor network which is the distance of data transmission distance and low power consumption. Besides this WSN also tested in the net house of aquaponics of the Research Center for High-tech Application in Agriculture (RCHAA), University of Science, Vietnam National University-HCM. The results show that the WSN system is working reliably and promising which brings significantly benefits to smart agriculture as aquaponics, clean vegetable farms, aquaculture farms…

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