Wireless sensor networks security coverage and localization pdf

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wireless sensor networks security coverage and localization pdf

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Overview of Wireless Sensor Network

The Journal of Applied Research and Technology JART is a bimonthly open access journal that publishes papers on innovative applications, development of new technologies and efficient solutions in engineering, computing and scientific research.

JART publishes manuscripts describing original research, with significant results based on experimental, theoretical and numerical work. The journal does not charge for submission, processing, publication of manuscripts or for color reproduction of photographs. JART classifies research into the following main fields: Material Science Biomaterials, carbon, ceramics, composite, metals, polymers, thin films, functional materials and semiconductors.

Computer Science Computer graphics and visualization, programming, human-computer interaction, neural networks, image processing and software engineering. Industrial Engineering Operations research, systems engineering, management science, complex systems and cybernetics applications and information technologies Electronic Engineering Solid-state physics, radio engineering, telecommunications, control systems, signal processing, power electronics, electronic devices and circuits and automation.

Instrumentation engineering and science Measurement devices pressure, temperature, flow, voltage, frequency etc. SRJ is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and qualitative measure of the journal's impact. SNIP measures contextual citation impact by wighting citations based on the total number of citations in a subject field.

Diseases related to poor water and sanitation conditions have over million cases reported annually, causing 5—10 million deaths world-wide. Water quality monitoring has thus become essential to the supply of clean and safe water.

Conventional monitoring processes involve manual collection of samples from various points in the distribution network, followed by laboratory testing and analysis. This process has proved to be ineffective since it is laborious, time consuming and lacks real-time results to promote proactive response to water contamination. Wireless sensor networks WSN have since been considered a promising alternative to complement conventional monitoring processes.

These networks are relatively affordable and allow measurements to be taken remotely, in real-time and with minimal human intervention. This work surveys the application of WSN in environmental monitoring, with particular emphasis on water quality. Various WSN based water quality monitoring methods suggested by other authors are studied and analyzed, taking into account their coverage, energy and security concerns.

Wireless sensor networks WSNs have gained popularity within research community because they provide a promising infrastructure for numerous control and monitoring applications.

These simple low-cost networks allow monitoring processes to be conducted remotely, in real-time and with minimal human intervention. A typical WSN network consists of two main components namely node and base-station, as shown in Figure 1. A node is a device that is normally equipped with sensing, processing and communication capabilities, and is responsible for measuring the parameters associated with a particular application.

A typical WSN Libelium, These standards include IEEE There is no single connectivity solution considered suitable for all WSNs, and the choice of standard entirely depends on communication requirements and resource constraints of a particular application. Typical considerations for selecting a wireless connectivity solution are specified in Table 1.

Considerations in the selection of a WSN connectivity standard. BLE is an ultra-low power version of the Bluetooth specification which allows data rates of up to 1 Mbps in the 30—80 m range context Gungor et al.

LoRaWAN is a technology that has been designed for applications that need to send small amounts of data over long distances a few times per day. SigFox is the world's first cellular network dedicated to low bandwidth Machine-to-Machine and Internet of Things applications. Its patented Ultra Narrow Band UNB technology utilizes unlicensed frequency bands to transmit data over a very narrow spectrum. Sigfox has a range capability of up to 40 km in open space SigFox, n.

Table 2 provides a technical comparison of the commonly employed WSN standards. WSNs have numerous applications ranging from military surveillance, industrial monitoring, medical telemetry and environmental monitoring. These applications have different operational requirements, which is why they tend to adopt different WSN architectures. For military surveillance, the most important requirements include high bandwidth, high security and good coverage. Industrial monitoring applications require secure, reliable, robust and real-time WSN solutions.

Medical applications often put more emphasis on security and network reliability, and environmental monitoring usually requires robust, energy efficient and autonomous nodes Bhende et al. The development of human society has come with major impacts on the environment, and all efforts to improve its conservation have been aggressively sought.

Environmental monitoring is one such significant effort, which has allowed various physical parameters to be monitored in order to control or limit further progression of environmental degradation. Conventional monitoring techniques required manual collection of environmental data, but were later considered inefficient since they are labor intensive and lack early warning capability to issues of environmental contamination.

Some years ago, digital data loggers were introduced to help improve the spatial and temporal resolution of environmental monitoring, but still lacked real-time data analytics. This approach has since promoted pro-active response to environmental contamination.

The proposed system employed GPS enabled sensor nodes to monitor air quality parameters and transmit them to a sink node linked to a computer network. GIS analysis was suggested to simulate spatial and temporal distribution of air pollution in a given area.

However, the proposed schema was only developed for a small area, which implies additional networking requirements will have to be taken into account when considering a relatively large area. Jadhav and Deshmukh designed and developed a WSN system for detecting forest fires by monitoring environmental parameters such as temperature, smoke and humidity.

From experimental testing, the system was able to take readings and send them for real-time sensor data logging. Nonetheless, the system was battery operated and did not integrate any energy scavenging mechanisms such as solar to extend the lifetime of the nodes.

Keshtgari designed a WSN system to monitor climatological and environmental parameters for use in precision agriculture. From simulation results, the proposed methodology achieved high transmission success rates proving great potential for employing ZigBee technology in agricultural systems. Nevertheless, the adopted topologies were not optimized for power consumption and therefore limit the WSN lifetime.

Water borne diseases have become a major challenge to human health. Therefore, ensuring water quality is undoubtedly highly significant to maintaining a sustainable civilization for all. Water quality can be defined as the suitability of water for a particular application based on its chemical, biological and physical characteristics.

Monitoring water quality involves detecting its characteristic parameters and comparing them with set standards and guidelines. One of the biggest challenges in monitoring water quality is the requirement to collect a large number of samples in order to ensure accurate and reliable analysis.

In this regard, manual methods introduce considerable complexity and are considered ineffective. Real-time monitoring enables early warning capability to ensure timely response to water contamination. This is why WSNs have been thoroughly investigated for this application. Additionally, these networks require relatively low startup and maintenance costs, and therefore show great potential for numerous monitoring applications.

Monitoring water quality with WSN employs nodes that can detect physico-chemical parameters such as pH, conductivity, turbidity and chlorine. This is a measure of the degree of acidity or alkalinity of a solution.

A pH of 7 is neutral, while that below and above neutral is considered acidic and alkaline, respectively. For distribution systems, a pH that is between 6. This is a measure of a solution's capability to pass electrical current. Conductivity is used as an indication of the concentration conductive ions that normally come from dissolved salts and other inorganic material. The more the dissolved salts present, the higher the conductivity.

ORP measures how strongly electrons are transferred between component species in a solution. This indicates the ability of water to rid itself of contaminants.

Healthy water normally has very high ORP readings. This indicates the concentration of suspended and colloidal material in water and it is measured in nephelometric turbidity units NTU. Drinking water should have turbidity that is less than 1 NTU.

Monitoring water quality is critical to human health, hence employing WSN for such a task requires a system that is robust, secure and has a reliable communication. Authors achieved a communication range of up to 1. Nonetheless, using the ARM-7 microprocessor is costly since it runs an operating system in addition to executing the application code. This introduces additional computational complexity which leads to high power consumption. Khetre and Hate designed a WSN system for monitoring the quality of lake waters consisting of ARM 7 slave nodes for measuring water quality parameters.

A two-slave prototype was developed and employed ZigBee to transmit data to a master terminal. The system was tested on turbid water and a reading of All other parameters were captured on a live graph. Vijayakumar and Ramya designed and developed a low cost, real time water quality monitoring system using Internet of Things IoT technologies. From experimental results, the proposed system was able to present water quality parameters on the Internet. With the Raspberry Pi solution, energy resources will be depleted rapidly since the microprocessor has to run a LINUX operating system in addition to executing the application code.

Furthermore, cloud computing requires implementation of security mechanisms since it exposes sensor data to potential cyber-attacks, and in turn results in additional computational, bandwidth, memory and energy costs. Chung and Yoo designed a WSN system to detect water pollution in rivers, streams and coastal areas. The system employed TesloB series ATmega microcontroller powered sensor nodes. A data averaging algorithm was designed to reduce the size of the communication traffic, and a TinyOS query-based flooding routing protocol was used to transfer data through the network.

Even so, the communication reliability offered by a flooding scheme introduces additional processing, information overheads which lead to huge costs in terms of energy, memory and bandwidth. This is inefficient for WSNs since they have limited resources. Table 3 compares nodes architectures of reviewed WSN water quality monitoring solutions with energy concerns. A comparison of proposed node architectures for water quality monitoring systems with energy concerns.

Yue and Ying presented a novel water quality monitoring system made up of several solar powered sensor nodes, which employ IEEE The prototype was tested on 6 water samples by measuring their pH and turbidity values and was able to provide real time feedback. He and Zhang designed a two component WSN based water quality monitoring system for the environmental protection department.

However, the proposed system does not provide any local data storage, which implies that water quality information will not be accessible where there is no Internet connection. Nasser, Ali, Karim, and Belhaouari designed and implemented an energy efficient, self-configurable and reusable WSN-based water quality monitoring system. The proposed framework consists of open hardware ZigBee sensor motes Squidbee , a data center that is connected to the Internet, and a fixed client-server component that includes an information portal and a web server.

Table 4 compares nodes architectures of reviewed WSN water quality monitoring solutions with data security concerns.

Wireless Sensor Network Dynamic Mathematics Modeling and Node Localization

The Journal of Applied Research and Technology JART is a bimonthly open access journal that publishes papers on innovative applications, development of new technologies and efficient solutions in engineering, computing and scientific research. JART publishes manuscripts describing original research, with significant results based on experimental, theoretical and numerical work. The journal does not charge for submission, processing, publication of manuscripts or for color reproduction of photographs. JART classifies research into the following main fields: Material Science Biomaterials, carbon, ceramics, composite, metals, polymers, thin films, functional materials and semiconductors. Computer Science Computer graphics and visualization, programming, human-computer interaction, neural networks, image processing and software engineering. Industrial Engineering Operations research, systems engineering, management science, complex systems and cybernetics applications and information technologies Electronic Engineering Solid-state physics, radio engineering, telecommunications, control systems, signal processing, power electronics, electronic devices and circuits and automation. Instrumentation engineering and science Measurement devices pressure, temperature, flow, voltage, frequency etc.

Wireless Sensor Network Dynamic Mathematics Modeling and Node Localization

Wireless Sensor Networks - Technology and Protocols. Wireless Sensor Networks WSNs can be defined as a self-configured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a main location or sink where the data can be observed and analysed. A sink or base station acts like an interface between users and the network. One can retrieve required information from the network by injecting queries and gathering results from the sink. Typically a wireless sensor network contains hundreds of thousands of sensor nodes.

Wireless Sensor Networks : Security, Coverage, and Localization pdf free download

With the rapid development of wireless sensor network WSN technology and its localization method, localization is one of the basic services for data collection in WSN.

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