scholarly journals Energy-Efficient Broadcasting Scheme for Smart Industrial Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Zhuangbin Chen ◽  
Anfeng Liu ◽  
Zhetao Li ◽  
Young-June Choi ◽  
Hiroo Sekiya ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Packet Transmission ◽  
Link Quality ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Smart Devices ◽  
Industrial Wireless Sensor Networks ◽  
Network Upgrade

In smart Industrial Wireless Sensor Networks (IWSNs), sensor nodes usually adopt a programmable technology. These smart devices can obtain new or special functions by reprogramming: they upgrade their soft systems through receiving new version of program codes. If sensor nodes need to be upgraded, the sink node will propagate program code packets to them through “one-to-many” broadcasting, and therefore new capabilities can be obtained, forming the so-called Software Defined Network (SDN). However, due to the high volume of code packet, the constraint energy of sensor node, and the unreliable link quality of wireless network, rapidly broadcasting the code packets to all nodes in network can be a challenge issue. In this paper, a novel Energy-efficient Broadcast scheme with adjustable broadcasting radius is proposed aiming to improve the performance of network upgrade. In our scheme, the nonhotspots sensor nodes take full advantage of their residual energy caused in data collection period to improve the packet reception probability and reduce the broadcasting delay of code packet transmission by enlarging the broadcasting radius, that is, the transmitting power. The theoretical analyses and experimental results show that, compared with previous work, our approach can averagely reduce the Network Upgrade Delay (NUD) by 14.8%–45.2% and simultaneously increase the reliability without harming the lifetime of network.

Energy-Efficient and Secure Data Forwarding Mechanism for Balancing Cluster Lifetime for Huge Size Wireless Sensor Networks

2019 ◽  
Vol 16 (9) ◽  
pp. 3961-3964
Author(s):  
Charu Sharma ◽  
Rohit Vaid
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Base Station ◽  
Packet Transmission ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor

In designing Wireless Sensor Networks, energy efficiency and security should be considered very critically. Energy efficiency is achieved through data aggregation which eliminates the transmission of redundant data while security is achieved by preserving confidentiality among sensor node and the base station. In this paper, an energy efficient and secure cluster based aggregation mechanism is presented. In this model, for energy efficiency the network is divided into tracks and sectors so the cluster head’s are uniformly selected from the whole network. To achieve security the cluster head’s perform data aggregation with the help of some pattern codes and only distinctive data is transmitted from sensor nodes in encrypted form. To perform aggregation, the sensor nodes do not need to know about the actual sensor data therefore there is no need to use any encryption or decryption schemes between nodes and cluster head. Performance evaluation shows proposed model works better to enhance the network lifetime, security, average residual energy, and average packet transmission ratio than conventional data aggregation models.

scholarly journals EERS: Energy-Efficient Reference Node Selection Algorithm for Synchronization in Industrial Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4095
Author(s):  
Mahmoud Elsharief ◽  
Mohamed A. Abd El-Gawad ◽  
Haneul Ko ◽  
Sangheon Pack
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Time Synchronization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Industrial Wireless Sensor Networks ◽  
Node Selection ◽  
Reference Node

Time synchronization is an essential issue in industrial wireless sensor networks (IWSNs). It assists perfect coordinated communications among the sensor nodes to preserve battery power. Generally, time synchronization in IWSNs has two major aspects of energy consumption and accuracy. In the literature, the energy consumption has not received much attention in contrast to the accuracy. In this paper, focusing on the energy consumption aspect, we introduce an energy-efficient reference node selection (EERS) algorithm for time synchronization in IWSNs. It selects and schedules a minimal sequence of connected reference nodes that are responsible for spreading timing messages. EERS achieves energy consumption synchronization by reducing the number of transmitted messages among the sensor nodes. To evaluate the performance of EERS, we conducted extensive experiments with Arduino Nano RF sensors and revealed that EERS achieves considerably fewer messages than previous techniques, robust time synchronization (R-Sync), fast scheduling and accurate drift compensation for time synchronization (FADS), and low power scheduling for time synchronization protocols (LPSS). In addition, simulation results for a large sensor network of 450 nodes demonstrate that EERS reduces the whole number of transmitted messages by 52%, 30%, and 13% compared to R-Sync, FADS, and LPSS, respectively.

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.

scholarly journals Anomaly Detection in Medical Wireless Sensor Networks using SVM and Linear Regression Models

2014 ◽  
Vol 5 (1) ◽  
pp. 20-45 ◽  
Author(s):  
Osman Salem ◽  
Alexey Guerassimov ◽  
Ahmed Mehaoua ◽  
Anthony Marcus ◽  
Borko Furht
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Anomaly Detection ◽  
Patient Data ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Smart Devices ◽  
Support Vector ◽  
Processing Unit

This paper details the architecture and describes the preliminary experimentation with the proposed framework for anomaly detection in medical wireless body area networks for ubiquitous patient and healthcare monitoring. The architecture integrates novel data mining and machine learning algorithms with modern sensor fusion techniques. Knowing wireless sensor networks are prone to failures resulting from their limitations (i.e. limited energy resources and computational power), using this framework, the authors can distinguish between irregular variations in the physiological parameters of the monitored patient and faulty sensor data, to ensure reliable operations and real time global monitoring from smart devices. Sensor nodes are used to measure characteristics of the patient and the sensed data is stored on the local processing unit. Authorized users may access this patient data remotely as long as they maintain connectivity with their application enabled smart device. Anomalous or faulty measurement data resulting from damaged sensor nodes or caused by malicious external parties may lead to misdiagnosis or even death for patients. The authors' application uses a Support Vector Machine to classify abnormal instances in the incoming sensor data. If found, the authors apply a periodically rebuilt, regressive prediction model to the abnormal instance and determine if the patient is entering a critical state or if a sensor is reporting faulty readings. Using real patient data in our experiments, the results validate the robustness of our proposed framework. The authors further discuss the experimental analysis with the proposed approach which shows that it is quickly able to identify sensor anomalies and compared with several other algorithms, it maintains a higher true positive and lower false negative rate.

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 Optimized Energy Efficient Trust Aware System in Wireless Sensor Networks

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Palak Aggarwal ◽  
Santosh Kumar ◽  
Neha Garg ◽  
Sumeshwar Singh
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
False Alarm ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Packet Transmission ◽  
Secure Routing ◽  
Wireless Sensor ◽  
Packet Drop

Energy and security are very important issues in Wireless Sensor Networks (WSN) which need to be handled. These issues are interrelated because of limited energy there are some restrictions on implementation of security. Insider packet drop attack is one of the dangerous attacks for wireless sensor network that causes a heavy damage to WSN functionalities by dropping packets. It becomes necessary to identify such attack for secure routing of data in WSN. To detect this attack, trust mechanism has been proven as a successful technique. In this mechanism, each node verifies the trustworthiness of its neighbor node before packet transmission so that packets can only be transmitted to trustworthy nodes. But there is a problem of False Alarm with such trust-aware scheme. False alarm occurs when a good node’s trust value goes down due to natural packet dropping and being eliminated from the routing paths. This wastes network’s resources that further shortens network lifetime. In this paper, we have proposed a system for identification and recovery of false alarms (IRFA) which is the optimization of existing trust based system. But security solution needs to be energy efficient due to scarcity of energy resources in WSN. To provide energy efficiency, we have implemented proposed IRFA system in cluster based environment which detects insider packet drop attackers in an energy efficient manner. We have conducted OMNET++ simulation and results demonstrate that the proposed system performance is better than existing trust-based system in terms of packet delivery rate and energy efficiency which improves network lifetime.

EE-Hybrid MAC Protocol for Wireless Sensor Networks

2014 ◽  
Vol 573 ◽  
pp. 407-411
Author(s):  
Chelliah Pandeeswaran ◽  
Natrajan Papa ◽  
Sundar G. Jayesh
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Mac Protocol ◽  
Mac Protocols ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Industrial Automation ◽  
Time Critical

MAC protocol design in Wireless sensor networks becomes vibrant research field for the past several years. In this paper an EE-Hybrid MAC protocol (Energy efficient hybrid Medium Access Control) has been proposed, which is energy efficient and low latency MAC protocol, which uses interrupt method to assign priority for certain wireless sensor nodes assumed to be present in critical loops of industrial process control domain. EE-Hybrid MAC overcomes some of the limitations in the existing approaches. Industrial wireless sensor network require a suitable MAC protocol which offers energy efficiency and capable of handling emergency situations in industrial automation domain. Time critical and mission critical applications demands not only energy efficiency but strict timeliness and reliability. Harsh environmental condition and dynamic network topologies may cause industrial sensor to malfunction, so the developed protocol must adapt to changing topology and harsh environment. Most of the existing MAC protocols have number of limitations for industrial application domain In industrial automation scenario, certain sensor loops are found to be time critical, where data’s have to be transferred without any further delay. The proposed EE-Hybrid MAC protocol is simulated in NS2 environment, from the result it is observed that proposed protocol provides better performance compared to the conventional MAC protocols.

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.

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