RF Ranging Methods and Performance Limits for Sensor Localization

2009 ◽  
pp. 96-121 ◽  
Author(s):  
Steven Lanzisera ◽  
Kristofer S.J. Pister
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensors ◽  
Wireless Systems ◽  
Multipath Channels ◽  
Wireless Sensor ◽  
Performance Limits ◽  
Sensor Localization ◽  
Range Estimation ◽  
Mitigation Techniques ◽  
And Performance

Localization or geolocation of wireless sensors usually requires accurate estimates of the distance between nodes in the network. RF ranging techniques can provide these estimates through a variety of methods some of which are well suited to wireless sensor networks. Noise and multipath channels fundamentally limit the accuracy of range estimation, and a number of other implementation related phenomena further impact accuracy. This chapter explores these effects and selected mitigation techniques in the context of low power wireless systems.

scholarly journals A Model-Based Approach for Adaptable Middleware Evolution in WSN Platforms

2021 ◽  
Vol 10 (1) ◽  
pp. 20
Author(s):  
Walter Tiberti ◽  
Dajana Cassioli ◽  
Antinisca Di Marco ◽  
Luigi Pomante ◽  
Marco Santic
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Embedded System ◽  
Operating Systems ◽  
Parallel Evolution ◽  
Wireless Sensor ◽  
New Techniques ◽  
Model Based ◽  
And Performance ◽  
Hardware Platforms

Advances in technology call for a parallel evolution in the software. New techniques are needed to support this dynamism, to track and guide its evolution process. This applies especially in the field of embedded systems, and certainly in Wireless Sensor Networks (WSNs), where hardware platforms and software environments change very quickly. Commonly, operating systems play a key role in the development process of any application. The most used operating system in WSNs is TinyOS, currently at its TinyOS 2.1.2 version. The evolution from TinyOS 1.x and TinyOS 2.x made the applications developed on TinyOS 1.x obsolete. In other words, these applications are not compatible out-of-the-box with TinyOS 2.x and require a porting action. In this paper, we discuss on the porting of embedded system (i.e., Wireless Sensor Networks) applications in response to operating systems’ evolution. In particular, using a model-based approach, we report the porting we did of Agilla, a Mobile-Agent Middleware (MAMW) for WSNs, on TinyOS 2.x, which we refer to as Agilla 2. We also provide a comparative analysis about the characteristics of Agilla 2 versus Agilla. The proposed Agilla 2 is compatible with TinyOS 2.x, has full capabilities and provides new features, as shown by the maintainability and performance measurement presented in this paper. An additional valuable result is the architectural modeling of Agilla and Agilla 2, missing before, which extends its documentation and improves its maintainability.

scholarly journals Self-Organization of Activity in Wireless Sensor Networks

2005 ◽  
Vol 1 (2) ◽  
pp. 245-252 ◽  
Author(s):  
P. Davis ◽  
A. Hasegawa ◽  
N. Kadowaki ◽  
S. Obana
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Power Consumption ◽  
Wireless Sensors ◽  
Ad Hoc ◽  
Wireless Sensor ◽  
Self Organization ◽  
Sensor Systems ◽  
Low Resolution ◽  
Sensing Data

We propose a method for managing the spontaneous organization of sensor activity in ad hoc wireless sensor systems. The wireless sensors exchange messages to coordinate responses to requests for sensing data, and to control the fraction of sensors which are active. This method can be used to manage a variety of sensor activities. In particular, it can be used for reducing the power consumption by battery operated devices when only low resolution sensing is required, thus increasing their operation lifetimes.

Design and Performance Analysis of Segmented Wireless Sensor Networks

2018 ◽  
Vol 2 (4) ◽  
pp. 1-4
Author(s):  
Victor Barrera-Figueroa ◽  
Mario E. Rivero-Angeles ◽  
Rolando Menchaca-Mendez ◽  
Edgar Romo-Montiel ◽  
Ricardo Menchaca-Mendez
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Analysis ◽  
Wireless Sensor ◽  
And Performance

scholarly journals A Provably Secure Three-Factor Authentication Protocol for Wireless Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Tsu-Yang Wu ◽  
Lei Yang ◽  
Zhiyuan Lee ◽  
Shu-Chuan Chu ◽  
Saru Kumari ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Formal Analysis ◽  
Authentication Protocol ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensitive Data ◽  
Computational Overhead ◽  
And Performance ◽  
Three Factor

The wireless sensor network is a network composed of sensor nodes self-organizing through the application of wireless communication technology. The application of wireless sensor networks (WSNs) requires high security, but the transmission of sensitive data may be exposed to the adversary. Therefore, to guarantee the security of information transmission, researchers propose numerous security authentication protocols. Recently, Wu et al. proposed a new three-factor authentication protocol for WSNs. However, we find that their protocol cannot resist key compromise impersonation attacks and known session-specific temporary information attacks. Meanwhile, it also violates perfect forward secrecy and anonymity. To overcome the proposed attacks, this paper proposes an enhanced protocol in which the security is verified by the formal analysis and informal analysis, Burross-Abadii-Needham (BAN) logic, and ProVerif tools. The comparison of security and performance proves that our protocol has higher security and lower computational overhead.

scholarly journals Proposed Intelligent Pre-Processing Model of Real-Time Flood Forecasting and Warning for Data Classification and Aggregation

2017 ◽  
Vol 13 (11) ◽  
pp. 4 ◽  
Author(s):  
Marouane El Mabrouk ◽  
Salma Gaou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Real Time ◽  
Wireless Sensors ◽  
Data Classification ◽  
Flood Forecasting ◽  
Base Stations ◽  
Wireless Sensor ◽  
Time Data ◽  
Forecasting And Warning

A wireless sensor network is a network that can design a self-organizing structure and provides effective support for several protocols such as routing, locating, discovering services, etc. It is composed of several nodes called sensors grouped together into a network to communicate with each other and with the base stations. Nowadays, the use of Wireless sensor networks increased considerably. It can collect physical data and transform it into a digital values in real-time to monitor in a continuous manner different disaster like flood. However, due to various factors that can affect the wireless sensor networks namely, environmental, manufacturing errors hardware and software problems etc... It is necessary to carefully select and filter the data from the wireless sensors since we are providing a decision support system for flood forecasting and warning. In this paper, we presents an intelligent Pre-Processing model of real-time flood forecasting and warning for data classification and aggregation. The proposed model consists on several stages to monitor the wireless sensors and its proper functioning, to provide the most appropriate data received from the wireless sensor networks in order to guarantee the best accuracy in terms of real-time data and to generate a historical data to be used in the further flood forecasting.

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