Wireless Sensor Network Using ARM Processors

2013 ◽  
Vol 4 (4) ◽  
pp. 48-59 ◽  
Author(s):  
Manivannan Doraipandian ◽  
Periasamy Neelamegam
Keyword(s):  
Critical Role ◽  
Sensor Nodes ◽  
Base Stations ◽  
Wireless Sensor ◽  
Processing Unit ◽  
Distributed Data ◽  
Embedded Devices ◽  
Arm Processor ◽  
Distributed Data Processing ◽  
Efficient Data

The hardware design of Wireless Sensor Networks (WSN) is the crux of its effective deployment. Nowadays these networks are used in microscopic, secure and high-end embedded products. WSN's potentiality in terms of efficient data sensing and distributed data processing has led to its usage in applications for measurement and tracking. WSN comprises of small number of embedded devices known as sensor nodes, gateways and base stations. Sensor nodes consist of sensors, processors and transceivers. The property of embedded sensor devices, also called motes, is to determine the strength of WSN. Thus processor selection for the motes plays a critical role in determining a WSN's competency. In this article, the absolute and obvious hardware characteristics of available and proposed sensor nodes are discussed. The objective of this work was to increase the efficiency and provision of sensor nodes by evaluating their processing and transceiver units. During this work, a sensor node was developed with ARM processor and XBee series 2 Unit. LPC 2148, LPC 2378 ARM processors were posed as processing unit and XBee series 2 acted as communication unit. Results of this experimental setup were recorded. Also a comparative study of the various available sensor nodes and proposed sensor nodes was done extensively.

scholarly journals A Systematic Literature Review on Outlier Detection in Wireless Sensor Networks

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 328 ◽  
Author(s):  
Mahmood Safaei ◽  
Shahla Asadi ◽  
Maha Driss ◽  
Wadii Boulila ◽  
Abdullah Alsaeedi ◽  
...  
Keyword(s):  
Literature Review ◽  
Outlier Detection ◽  
Systematic Literature Review ◽  
Machine Learning Algorithms ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Distributed Data ◽  
Detection Techniques ◽  
Distributed Data Processing ◽  
Spatially Distributed

A wireless sensor network (WSN) is defined as a set of spatially distributed and interconnected sensor nodes. WSNs allow one to monitor and recognize environmental phenomena such as soil moisture, air pollution, and health data. Because of the very limited resources available in sensors, the collected data from WSNs are often characterized as unreliable or uncertain. However, applications using WSNs demand precise readings, and uncertainty in data reading can cause serious damage (e.g., health monitoring data). Therefore, an efficient local/distributed data processing algorithm is needed to ensure: (1) the extraction of precise and reliable values from noisy readings; (2) the detection of anomalies from data reported by sensors; and (3) the identification of outlier sensors in a WSN. Several works have been conducted to achieve these objectives using several techniques such as machine learning algorithms, mathematical modeling, and clustering. The purpose of this paper is to conduct a systematic literature review to report the available works on outlier and anomaly detection in WSNs. The paper highlights works conducted from January 2004 to October 2018. A total of 3520 papers are reviewed in the initial search process. Later, these papers are filtered by title, abstract, and contents, and a total of 117 papers are selected. These papers are examined to answer the defined research questions. The current paper presents an improved taxonomy of outlier detection techniques. This will help researchers and practitioners to find the most relevant and recent studies related to outlier detection in WSNs. Finally, the paper identifies existing gaps that future studies can fill.

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 Wormhole Detection Mechanism in Wireless Sensor Networks

2020 ◽  
Vol 9 (2) ◽  
pp. 1845-1847
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Base Station ◽  
Sensor Nodes ◽  
Base Stations ◽  
Wireless Sensor ◽  
Health Care Environment ◽  
Detection Mechanism ◽  
Primary Base ◽  
Power And Energy

A Wireless Sensor Network (WSN) is a component with sensor nodes that continuously observes environmental circumstances. Sensor nodes accomplish different key operations like sensing temperature and distance. It has been used in many applications like computing, signal processing, and network selfconfiguration to expand network coverage and build up its scalability. The Unit of all these sensors that exhibit sensing and transmitting information will offer more information than those offered by autonomously operating sensors. Usually, the transmitting task is somewhat critical as there is a huge amount of data and sensors devices are restricted. Being the limited number of sensor devices the network is exposed to different types of attacks. The Traditional security mechanisms are not suitable for WSN as they are generally heavy and having limited number of nodes and also these mechanisms will not eliminate the risk of other attacks. WSN are most useful in different crucial domains such as health care, environment, industry, and security, military. For example, in a military operation, a wireless sensor network monitors various activities. If an event is detected, these sensor nodes sense that and report the data to the primary (base) station (called sink) by making communication with other nodes. To collect data from WSN base Stations are commonly used. Base stations have more resources (e.g. computation power and energy) compared to normal sensor nodes which include more or less such limitations. Aggregation points will gather the data from neighboring sensor nodes to combine the data and forward to master (base) stations, where the data will be further forwarded or processed to a processing center. In this manner, the energy can be preserved in WSN and the lifetime of network is expanded.

scholarly journals Anomaly Detection in Wireless Sensor Networks: A Proposed Framework

2020 ◽  
Vol 14 (10) ◽  
pp. 150
Author(s):  
Dina M. Ibrahim ◽  
Nada M. Alruhaily
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
Detection System ◽  
Denial Of Service ◽  
Research Problem ◽  
Sensor Nodes ◽  
Base Stations ◽  
Sensor Data ◽  
Wireless Sensor

With the rise of IOT devices and the systems connected to the internet, there was, accordingly, an ever-increasing number of network attacks (e.g. in DOS, DDOS attacks). A very significant research problem related to identifying Wireless Sensor Networks (WSN) attacks and the analysis of the sensor data is the detection of the relevant anomalies. In this paper, we propose a framework for intrusion detection system in WSN. The first two levels are located inside the WSN, one of them is between sensor nodes and the second is between the cluster heads. While the third level located on the cloud, and represented by the base stations. In the first level, which we called light mode, we simulated an intrusion traffic by generating data packets based on TCPDUMP data, which contain intrusion packets, our work, is done by using WSN technology. We used OPNET simulation for generating the traffic because it allows us to collect intrusion detection data in order to measure the network performance and efficiency of the simulated network scenarios. Finally, we report the experimental results by mimicking a Denial-of-Service (DOS) attack. <em> </em>

scholarly journals Proposing a Density-Based Clustering Approach (DBCA) to Aggregate Data Collected from the Environment in Arid Area for Desertification

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Zhihao Peng ◽  
Raziyeh Daraei ◽  
Seyed Mojtaba Ahmadpanahi ◽  
Amir Seyed Danesh ◽  
Safieh Siadat ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Arid Area ◽  
Sensor Nodes ◽  
Base Stations ◽  
Wireless Sensor ◽  
Arid Areas ◽  
Density Based Clustering ◽  
Energy Limitation ◽  
Clustering Approach

Nowadays, the expansion of desert areas has become one of the main problems in arid areas due to various reasons such as rising temperatures and vegetation fires. Establishment of wireless sensor networks in these areas can accelerate the process of environmental monitoring and integrate temperature and humidity information sending to base stations in order to make basic decisions on desertification. The main problem in this regard is the energy limitation of sensor nodes in wireless sensor networks, which is one of the main challenges in using these nodes due to the lack of a fixed power supply. Because the node consumes the most energy during data transmission, the node that transmits the most data or sends the packets over long distances runs out of energy faster than the others and the network work process is disrupted. Therefore, in this study, a density-based clustering approach is proposed to integrate data collected from the environment in arid areas for desertification. In the proposed method at each step, the node that has the most residual energy and is highly centralized will be selected to transfer information. The results of experiments for evaluating the performance of the proposed method show that the proposed method balances the energy consumption of the nodes and optimizes the lifespan of the nodes in the wireless sensor network installed in the arid area.

scholarly journals Performance Comparison of Homogeneous and Heterogeneous 3D Wireless Sensor Networks

2017 ◽  
pp. 32-37 ◽  
Author(s):  
Ranjana Thalore ◽  
Partha Pratim Bhattacharya ◽  
Manish Kumar Jha
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Comparison ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Medical Monitoring ◽  
3 Dimensional ◽  
Recent Developments ◽  
Efficient Data ◽  
Battery Energy

Recent developments in wireless sensor networks include their applications in safety, medical monitoring, environment monitoring and many more. Limited battery energy and efficient data delivery are most considered constraints for sensor nodes. Depletion of node battery ceases functioning of the node. The network lifetime can be enhanced with the help of Multi-Layer protocol (ML-MAC). This paper presents a practical approach including 3-dimensional deployment of sensor nodes and analyzes two different types of networks – homogeneous and heterogeneous WSNs. To analyze various QoS parameters, two types of nodes are considered in a heterogeneous network. The performance of both the networks is compared through simulations. The results show that ML-MAC performs better for a 3D heterogeneous WSNs.

scholarly journals Transmission Power Control with the Guaranteed Communication Reliability in WSN

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Dae-Young Kim ◽  
Zilong Jin ◽  
Jungwook Choi ◽  
Ben Lee ◽  
Jinsung Cho
Keyword(s):  
Wireless Sensor Network ◽  
Power Control ◽  
Sensor Network ◽  
Data Transmission ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Transmission Power ◽  
Efficient Data ◽  
Communication Reliability

In a wireless sensor network, sensor nodes are deployed in an ad hoc fashion and they deliver data packets using multihop transmission. However, transmission failures occur frequently in the multihop transmission over wireless media. Thus, a loss recovery mechanism is required to provide end-to-end reliability. In addition, because the sensor nodes are very small devices and have insufficient resources, energy-efficient data transmission is crucial for prolonging the lifetime of a wireless sensor network. This paper proposes a transmission power control mechanism for reliable data transmission, which satisfies communication reliability through recovery of lost packets. The proposed method calculates packet reception rate (PRR) of each hop to maintain end-to-end packet delivery rate (PDR), which is determined based on the desired communication reliability. Then, the transmission power is adjusted based on the PRR to reduce energy consumption. The proposed method was evaluated through extensive simulations, and the results show that it leads to more energy-efficient data transmission compared to existing methods.

scholarly journals User Integrity Protection Security Model for Enhanced Telemedicine For Healthcare Networks

2020 ◽  
Author(s):  
Nishu Gupta
Keyword(s):  
Key Management ◽  
Energy Efficient ◽  
Key Exchange ◽  
Sensor Nodes ◽  
Base Stations ◽  
Wireless Sensor ◽  
Sensitive Information ◽  
Security Model ◽  
Wireless Sensor Nodes ◽  
Cryptographic Keys

The wireless sensor nodes utilizes the wireless channels in the frequency bands of the 802.11, 802.16, 802.15.4, 802.15.1 and other similar wireless standards. The wireless sensor networks are built of the small sensor nodes built upon the microcontroller platforms such as PIC, 8051, ARM, AVR, etc. During the periods when the WSN nodes are in working condition, they need secure cryptographic keys for secure propagation of the sensitive information. Efficient key management and distribution scheme play an important role for the data security in WSNs. Existing cryptographic key management and distribution technique usually consume higher amount of energy and put larger computational overheads on Wireless sensor nodes. The cryptographic keys are used on different communication levels of WSN communications i.e. neighbour nodes, cluster heads and base stations. A successful corporate key administration and distribution policy is required to keep up the security of the remote sensor systems. The problems described in the base papers are related to the requirement of energy efficient key exchange policies for WSNs. So to overcome the above problem there is a need to design the model to solve the key-problem of energy efficient and secure key exchange scheme. The proposed model has been found improved after the in-depth result analysis over the given scenario.

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