An optimal coverage-preserving scheme for wireless sensor networks based on local information exchange

2007 ◽  
Vol 30 (14-15) ◽  
pp. 2708-2720 ◽  
Author(s):  
Azzedine Boukerche ◽  
Xin Fei ◽  
Regina B. Araujo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Information Exchange ◽  
Local Information ◽  
Wireless Sensor

A Distributed Least-Squares Algorithm in Wireless Sensor Networks With Unknown and Limited Communications

2017 ◽  
Vol 8 (3) ◽  
pp. 15-36 ◽  
Author(s):  
Jing Wang ◽  
In Soo Ahn ◽  
Yufeng Lu ◽  
Tianyu Yang ◽  
Gennady Staskevich
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Least Squares ◽  
Multiagent Systems ◽  
Information Exchange ◽  
Large Scale ◽  
Wireless Sensor ◽  
Left Eigenvector ◽  
Mild Assumption ◽  
Least Squares Algorithm

In this article, the authors propose a new distributed least-squares algorithm to address the sensor fusion problem in using wireless sensor networks (WSN) to monitor the behaviors of large-scale multiagent systems. Under a mild assumption on network observability, that is, each sensor can take the measurements of a limited number of agents but the complete multiagent systems are covered under the union of all sensors in the network, the proposed algorithm achieves the estimation consensus if local information exchange can be performed among sensors. The proposed distributed least-squares algorithm can handle the directed communication network by explicitly estimating the left eigenvector corresponding to the largest eigenvalue of the sensing/communication matrix. The convergence of the proposed algorithm is analyzed, and simulation results are provided to further illustrate its effectiveness.

scholarly journals Clock Synchronization in Wireless Sensor Networks: Analysis and Design of Error Precision Based on Lossy Networked Control Perspective

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Wang Ting ◽  
Guo Di ◽  
Cai Chun-yang ◽  
Tang Xiao-ming ◽  
Wang Heng
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Packet Loss ◽  
Information Exchange ◽  
Clock Synchronization ◽  
Error Variance ◽  
Synchronization Error ◽  
Wireless Sensor ◽  
Analysis And Design ◽  
Packet Arrival

Motivated by the importance of the clock synchronization in wireless sensor networks (WSNs), due to the packet loss, the synchronization error variance is a random variable and may exceed the designed boundary of the synchronization variance. Based on the clock synchronization state space model, this paper establishes the model of synchronization error variance analysis and design issues. In the analysis issue, assuming sensor nodes exchange clock information in the network with packet loss, we find a minimum clock information packet arrival rate in order to guarantee the synchronization precision at synchronization node. In the design issue, assuming sensor node freely schedules whether to send the clock information, we look for an optimal clock information exchange rate between synchronization node and reference node which offers the optimal tradeoff between energy consumption and synchronization precision at synchronization node. Finally, simulations further verify the validity of clock synchronization analysis and design from the perspective of synchronization error variance.

scholarly journals Distributed Key Management to Secure IoT Wireless Sensor Networks in Smart-Agro

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2242 ◽  
Author(s):  
Safwan Mawlood Hussein ◽  
Juan Antonio López Ramos ◽  
José Antonio Álvarez Bermejo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Key Management ◽  
Information Exchange ◽  
Public Information ◽  
Sensor Nodes ◽  
Security And Privacy ◽  
Wireless Sensor ◽  
Embedded Devices ◽  
New Variety

With the deepening of the research and development in the field of embedded devices, the paradigm of the Internet of things (IoT) is gaining momentum. Its technology’s widespread applications increasing the number of connected devices constantly. IoT is built on sensor networks, which are enabling a new variety of solutions for applications in several fields (health, industry, defense, agrifood and agro sectors, etc.). Wireless communications are indispensable for taking full advantage of sensor networks but implies new requirements in the security and privacy of communications. Security in wireless sensor networks (WSNs) is a major challenge for extending IoT applications, in particular those related to the smart-agro. Moreover, limitations on processing capabilities of sensor nodes, and power consumption have made the encryption techniques devised for conventional networks not feasible. In such scenario, symmetric-key ciphers are preferred for key management in WSN; key distribution is therefore an issue. In this work, we provide a concrete implementation of a novel scalable group distributed key management method and a protocol for securing communications in IoT systems used in the smart agro sector, based on elliptic curve cryptography, to ensure that information exchange between layers of the IoT framework is not affected by sensor faults or intentional attacks. In this sense, each sensor node executes an initial key agreement, which is done through every member’s public information in just two rounds and uses some authenticating information that avoids external intrusions. Further rekeying operations require just a single message and provide backward and forward security.

Genetic Algorithms for Wireless Sensor Networks

2011 ◽  
pp. 755-758 ◽  
Author(s):  
João H. Kleinschmidt
Keyword(s):  
Wireless Sensor Networks ◽  
Genetic Algorithms ◽  
Sensor Networks ◽  
Evolutionary Algorithms ◽  
Energy Conservation ◽  
Resource Constraints ◽  
Low Cost ◽  
Local Information ◽  
Sensor Nodes ◽  
Wireless Sensor

Wireless sensor networks (WSNs) consist of a large number of low-cost and low-power sensor nodes. Some of the applications of sensor networks are environmental observation, monitoring disaster areas and so on. Distributed evolutionary computing is a poweful tool that can be applied to WSNs, because these networks require algorithms that are capable of learning independent of the operation of other nodes and also capable of using local information (Johnson, Teredesai & Saltarelli, 2005). Evolutionary algorithms must be designed for the resource constraints present in WSNs. This article describes how genetic algorithms can be used in WSNs design in order to satisfy energy conservation and connectivity constraints.

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