A New Spread Spectrum Based Approach for Ensuring Energy Efficiency and Security in Wireless Sensor Networks

2018 ◽  
Vol 10 (4) ◽  
pp. 45-57
Author(s):  
Nejla Rouissi ◽  
Hamza Gharsellaoui ◽  
Sadok Bouamama
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Spread Spectrum ◽  
Data Communication ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
The Internet ◽  
Rich Information

Wireless sensor networks (WSNs) play a central role in the Internet of Things (IoT). It consists of small-size sensor nodes connected to the internet through gateways providing content rich information. So, the traffic transmission between sensor nodes over radio links requires highly bandwidth and needs to ensure the reliability of the data. Therefore, providing safe communications of sensor data over wireless communication channel plays an essential role. Thus, the important issue on wireless sensor networks is to find an optimal schema that ensuring energy efficiency together with the security. In contrast, implementing traditional cryptographic algorithms is not very well suited for WSNs nodes. In this article, a novel combination of spread spectrum into watermarking scheme is presented. This watermarking schema based on direct-frequency-time spread spectrum secures data communication against jamming and falsification to ensure data integrity and increases resistance to interference at the same time ensures the energy efficiency.

A New Spread Spectrum Based Approach for Ensuring Energy Efficiency and Security in Wireless Sensor Networks

2020 ◽  
pp. 183-196
Author(s):  
Nejla Rouissi ◽  
Hamza Gharsellaoui ◽  
Sadok Bouamama
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Spread Spectrum ◽  
Data Communication ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
The Internet ◽  
Watermarking Scheme

Wireless sensor networks (WSNs) play a central role in the Internet of Things (IoT). It consists of small-size sensor nodes connected to the internet through gateways providing content rich information. So, the traffic transmission between sensor nodes over radio links requires highly bandwidth and needs to ensure the reliability of the data. Therefore, providing safe communications of sensor data over wireless communication channel plays an essential role. Thus, the important issue on wireless sensor networks is to find an optimal schema that ensuring energy efficiency together with the security. In contrast, implementing traditional cryptographic algorithms is not very well suited for WSNs nodes. In this article, a novel combination of spread spectrum into watermarking scheme is presented. This watermarking schema based on direct-frequency-time spread spectrum secures data communication against jamming and falsification to ensure data integrity and increases resistance to interference at the same time ensures the energy efficiency.

scholarly journals Evaluation of Energy Consumption using Receiver–Centric MAC Protocol in Wireless Sensor Networks

2018 ◽  
Vol 8 (1) ◽  
pp. 87
Author(s):  
Ananda Kumar K S ◽  
Balakrishna R
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Mac Protocol ◽  
Research Work ◽  
Data Communication ◽  
Reliable Data ◽  
Sensor Nodes ◽  
Wireless Sensor

At present day’s wireless sensor networks, obtain a lot consideration to researchers. Maximum number of sensor nodes are scattered that can communicate with all others. Reliable data communication and energy consumption are the mainly significant parameters that are required in wireless sensor networks. Many of MAC protocols have been planned to improve the efficiency more by enhancing the throughput and energy consumption. The majority of the presented medium access control protocols to only make available, reliable data delivery or energy efficiency does not offer together at the same time. In this research work the author proposes a novel approach based on Receiver Centric-MAC is implemented using NS2 simulator. Here, the author focuses on the following parametric measures like - energy consumption, reliability and bandwidth. RC-MAC provides high bandwidth without decreasing energy efficiency. The results show that 0.12% of less energy consumption, reliability improved by 20.86% and bandwidth increased by 27.32% of RC-MAC compared with MAC IEEE 802.11.

Sampling Sensor Nodes to Extend the Longevity of Wireless Sensor Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 53-63
Author(s):  
Mohammed Baqer ◽  
Luisella Balbis
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Smart Grids ◽  
Smart Cities ◽  
Sampling Rate ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
The Internet ◽  
Detection Accuracy

Background and Objective: Wireless Sensor Networks (WSN) are one of the most important elements in the Internet of Things (IoT) paradigm. It is envisaged that WSNs will seamlessly bridge the physical world with the Internet resulting in countless IoT applications in smart cities, wearable devices, smart grids, smart retails amongst others. It is necessary, however, to consider that sensing, processing and communicating large amounts of sensor data is an energy-demanding tasks. Recharging or replacing those battery-powered sensor nodes deployed in inaccessible locations is generally a tedious and time-consuming task. As a result, energy efficient approaches for WSN need to be devised in order to prolong the longevity of the network. Methods: In this paper, we present an approach that reduces energy consumption by controlling the sampling rate and the number of actively communicating nodes. The proposed approach applies compressive sensing to reduce the sampling rate and a statistical approach to decrease the sample size of sensor nodes. Results and Conclusion: The proposed approach is expected to significantly increase the lifetime of the network whilst maintaining the event detection accuracy.

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.

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 Time-selective data fusion for in-network processing in ad hoc wireless sensor networks

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881130 ◽  
Author(s):  
Jaanus Kaugerand ◽  
Johannes Ehala ◽  
Leo Mõtus ◽  
Jürgo-Sören Preden
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Fusion ◽  
Data Streams ◽  
Ad Hoc ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Temporal Consistency ◽  
Variable Delays

This article introduces a time-selective strategy for enhancing temporal consistency of input data for multi-sensor data fusion for in-network data processing in ad hoc wireless sensor networks. Detecting and handling complex time-variable (real-time) situations require methodical consideration of temporal aspects, especially in ad hoc wireless sensor network with distributed asynchronous and autonomous nodes. For example, assigning processing intervals of network nodes, defining validity and simultaneity requirements for data items, determining the size of memory required for buffering the data streams produced by ad hoc nodes and other relevant aspects. The data streams produced periodically and sometimes intermittently by sensor nodes arrive to the fusion nodes with variable delays, which results in sporadic temporal order of inputs. Using data from individual nodes in the order of arrival (i.e. freshest data first) does not, in all cases, yield the optimal results in terms of data temporal consistency and fusion accuracy. We propose time-selective data fusion strategy, which combines temporal alignment, temporal constraints and a method for computing delay of sensor readings, to allow fusion node to select the temporally compatible data from received streams. A real-world experiment (moving vehicles in urban environment) for validation of the strategy demonstrates significant improvement of the accuracy of fusion results.

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.

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.

Applications of Wireless Sensor Networks

2010 ◽  
pp. 1076-1090 ◽  
Author(s):  
Corinna Schmitt ◽  
Georg Carle
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Radio Communication ◽  
Power Resources ◽  
Limited Power

Today the researchers want to collect as much data as possible from different locations for monitoring reasons. In this context large-scale wireless sensor networks are becoming an active topic of research (Kahn1999). Because of the different locations and environments in which these sensor networks can be used, specific requirements for the hardware apply. The hardware of the sensor nodes must be robust, provide sufficient storage and communication capabilities, and get along with limited power resources. Sensor nodes such as the Berkeley-Mote Family (Polastre2006, Schmitt2006) are capable of meeting these requirements. These sensor nodes are small and light devices with radio communication and the capability for collecting sensor data. In this chapter the authors review the key elements for sensor networks and give an overview on possible applications in the field of monitoring.

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