Minimum Set Cover of Sparsely Distributed Sensor Nodes by a Collection of Unit Disks

Author(s):  
Satoshi Fujita
2005 ◽  
Vol 1 (3-4) ◽  
pp. 345-354 ◽  
Author(s):  
Dibyendu Chakrabarti ◽  
Subhamoy Maitra ◽  
Bimal Roy

Key pre-distribution is an important area of research in Distributed Sensor Networks (DSN). Two sensor nodes are considered connected for secure communication if they share one or more common secret key(s). It is important to analyse the largest subset of nodes in a DSN where each node is connected to every other node in that subset (i.e., the largest clique). This parameter (largest clique size) is important in terms of resiliency and capability towards efficient distributed computing in a DSN. In this paper, we concentrate on the schemes where the key pre-distribution strategies are based on transversal design and study the largest clique sizes. We show that merging of blocks to construct a node provides larger clique sizes than considering a block itself as a node in a transversal design.


Author(s):  
Lina M. Pestana Leão de Brito ◽  
Laura M. Rodríguez Peralta

As with many technologies, defense applications have been a driver for research in sensor networks, which started around 1980 due to two important programs of the Defense Advanced Research Projects Agency (DARPA): the distributed sensor networks (DSN) and the sensor information technology (SensIT) (Chong & Kumar, 2003). However, the development of sensor networks requires advances in several areas: sensing, communication, and computing. The explosive growth of the personal communications market has driven the cost of radio devices down and has increased the quality. At the same time, technological advances in wireless communications and electronic devices (such as low-cost, low-power, small, simple yet efficient wireless communication equipment) have enabled the manufacturing of sensor nodes and, consequently, the development of wireless sensor networks (WSNs).


2013 ◽  
Vol 373-375 ◽  
pp. 1931-1934 ◽  
Author(s):  
Yi Min Zhou ◽  
La Yuan Li

The Wireless Sensor Network applications has widely been used over the last few years. WSN is a novel self-organization wireless network which is made up of randomly distributed sensor Nodes. Due to some resource constraints, the design of security in WSN encounters a great many of new challenges. It is vulnerable to attack, which is harmful for availability of WSN. In this paper we propose a trust-aware and location-based secure routing protocol which protects WSN against routing attacks, and also supports large-scale WSN deployments. The proposed protocol is extended from GPSR protocol, which imports security mechanism that depends on a distributed trust management system. The solution has been shown to efficiently detect and avoid malicious nodes.


2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Tran Khanh Dang ◽  
Khanh T. K. Tran

Wireless sensor networks consist of a large number of distributed sensor nodes so that potential risks are becoming more and more unpredictable. The new entrants pose the potential risks when they move into the secure zone. To build a door wall that provides safety and security for the system, many recent research works applied the initial authentication process. However, the majority of the previous articles only focused on the Central Authority (CA) since this leads to an increase in the computation cost and energy consumption for the specific cases on the Internet of Things (IoT). Hence, in this article, we will lessen the importance of these third parties through proposing an enhanced authentication mechanism that includes key management and evaluation based on the past interactions to assist the objects joining a secured area without any nearby CA. We refer to a mobility dataset from CRAWDAD collected at the University Politehnica of Bucharest and rebuilt into a new random dataset larger than the old one. The new one is an input for a simulated authenticating algorithm to observe the communication cost and resource usage of devices. Our proposal helps the authenticating to be flexible, being strict with unknown devices into the secured zone. The threshold of maximum friends can modify based on the optimization of the symmetric-key algorithm to diminish communication costs (our experimental results compared to previous schemes less than 2000 bits) and raise flexibility in resource-constrained environments.


Author(s):  
Usha Manasi Mohapatra ◽  
Babita Majhi

Recently the distributed sensor network has achieved more attention than its centralized counterpart. There are a number of literature that used different evolutionary computing techniques in a distributed way for the task of optimization in several problems of wireless sensor network. Particularly, parameter estimation of FIR filter is carried out using numerous sensor nodes through distributed particle swarm optimization. Differential Evolution (DE) is an evolutionary technique and has been applied in various fields due to its simplicity and faster convergence property in comparison to other algorithms. In this chapter differential evolution is used in two different approaches, namely Incremental DE (IDE) and Diffusion DE (DDE) to estimate the parameters of FIR filter in a distributed manner. The performance is compared with other population based algorithms.


Author(s):  
Yupeng Hu ◽  
Rui Li

As an enabling network technology, energy efficient Medium Access Control (MAC) protocol plays a vital role in a battery-powered distributed sensor network. MAC protocols control how sensor nodes access a shared radio channel to communicate with each other. This chapter discusses the key elements of MAC design with an emphasis on energy efficiency. Furthermore, it reviews several typical MAC protocols proposed in the literature, comparing their energy conservation mechanism. Particularly, it presents a Collaborative Compression Based MAC (CCP-MAC) protocol, which takes advantage of the overheard data to achieve energy savings. Finally, it compares the performance of CCP-MAC with related MAC protocols, illustrating their advantages and disadvantages.


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