Localization Algorithms and Strategies for Wireless Sensor Networks

2009 ◽  
pp. 54-95 ◽  
Author(s):  
Ferit Ozan Akgul ◽  
Mohammad Heidari ◽  
Nayef Alsindi ◽  
Kaveh Pahlavan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Channel ◽  
Wireless Sensor ◽  
Location Awareness ◽  
Positioning Systems ◽  
Localization Algorithms ◽  
Physical Limitations ◽  
And Performance ◽  
Performance Results

This chapter discusses localization in WSNs specifically focusing on the physical limitations imposed by the wireless channel. Location awareness and different methods for localization are discussed. Particular attention is given to indoor TOA based ranging and positioning systems. Various aspects of WSN localization are addressed and performance results for cooperative schemes are presented.

scholarly journals Research on Secure Localization Model Based on Trust Valuation in Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Li ◽  
Xiaotian Yu ◽  
He Xu ◽  
Jiewei Qian ◽  
Lu Dong ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Malicious Nodes ◽  
Position Information ◽  
Secure Localization ◽  
Localization Algorithms ◽  
Localization Model ◽  
Proposed Model ◽  
And Performance

Secure localization has become very important in wireless sensor networks. However, the conventional secure localization algorithms used in wireless sensor networks cannot deal with internal attacks and cannot identify malicious nodes. In this paper, a localization based on trust valuation, which can overcome a various attack types, such as spoofing attacks and Sybil attacks, is presented. The trust valuation is obtained via selection of the property set, which includes estimated distance, localization performance, position information of beacon nodes, and transmission time, and discussion of the threshold in the property set. In addition, the robustness of the proposed model is verified by analysis of attack intensity, localization error, and trust relationship for three typical scenes. The experimental results have shown that the proposed model is superior to the traditional secure localization models in terms of malicious nodes identification and performance improvement.

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.

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 IMPROVING LOCALIZATION ACCURACY IN WIRELESS SENSOR NETWORKS

2013 ◽  
pp. 152-156
Author(s):  
VINOD KUMAR ◽  
SATYENDRA YADAV ◽  
ASHUTOSH KUMAR SINGH
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Sequential Monte Carlo ◽  
Fundamental Problem ◽  
Geographical Location ◽  
Wireless Sensor ◽  
Localization Accuracy ◽  
Localization Algorithms ◽  
Direction Of Movement

The most fundamental problem of wireless sensor networks is localization (finding the geographical location of the sensors). Most of the localization algorithms proposed for sensor networks are based on Sequential Monte Carlo (SMC) method. To achieve high accuracy in localization it requires high seed node density and it also suffers from low sampling efficiency. There are some papers which solves this problems but they are not energy efficient. Another approach The Bounding Box method was used to reduce the scope of searching the candidate samples and thus reduces the time for finding the set of valid samples. In this paper we propose an energy efficient approach which will further reduce the scope of searching the candidate samples, so now we can remove the invalid samples from the sample space and we can introduce more valid samples to improve the localization accuracy. We will consider the direction of movement of the valid samples, so that we can predict the next position of the samples more accurately, hence we can achieve high localization accuracy.

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