scholarly journals Power Grid-Oriented Cascading Failure Vulnerability Identifying Method Based on Wireless Sensors

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shudong Li ◽  
Yanshan Chen ◽  
Xiaobo Wu ◽  
Xiaochun Cheng ◽  
Zhihong Tian
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Bearing Capacity ◽  
Real World ◽  
Wireless Sensors ◽  
Power Grid ◽  
Wireless Sensor ◽  
Cascading Failure ◽  
Cascade Effect ◽  
Network Power

In our paper, we study the vulnerability in cascading failures of the real-world network (power grid) under intentional attacks. Here, we use three indexes ( B , K , k -shell) to measure the importance of nodes; that is, we define three attacks, respectively. Under these attacks, we measure the process of cascade effect in network by the number of avalanche nodes, the time steps, and the speed of the cascade propagation. Also, we define the node’s bearing capacity as a tolerant parameter to study the robustness of the network under three attacks. Taking the power grid as an example, we have obtained a good regularity of the collapse of the network when the node’s affordability is low. In terms of time and speed, under the betweenness-based attacks, the network collapses faster, but for the number of avalanche nodes, under the degree-based attack, the number of the failed nodes is highest. When the nodes’ bearing capacity becomes large, the regularity of the network’s performances is not obvious. The findings can be applied to identify the vulnerable nodes in real networks such as wireless sensor networks and improve their robustness against different attacks.

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.

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.

scholarly journals Practical Data Prediction for Real-World Wireless Sensor Networks

2015 ◽  
Vol 27 (8) ◽  
pp. 2231-2244 ◽  
Author(s):  
Usman Raza ◽  
Alessandro Camerra ◽  
Amy L. Murphy ◽  
Themis Palpanas ◽  
Gian Pietro Picco
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Real World ◽  
Wireless Sensor ◽  
Data Prediction

scholarly journals Performance Analysis of Distributed Estimation for Data Fusion Using a Statistical Approach in Smart Grid Noisy Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 567 ◽  
Author(s):  
Chatura Seneviratne ◽  
Patikiri Arachchige Don Shehan Nilmantha Wijesekara ◽  
Henry Leung
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Smart Grid ◽  
Communication Networks ◽  
Smart Grids ◽  
Measurement Errors ◽  
Power Grid ◽  
Distributed Estimation ◽  
Wireless Sensor ◽  
Grid Infrastructures

Internet of Things (IoT) can significantly enhance various aspects of today’s electric power grid infrastructures for making reliable, efficient, and safe next-generation Smart Grids (SGs). However, harsh and complex power grid infrastructures and environments reduce the accuracy of the information propagating through IoT platforms. In particularly, information is corrupted due to the measurement errors, quantization errors, and transmission errors. This leads to major system failures and instabilities in power grids. Redundant information measurements and retransmissions are traditionally used to eliminate the errors in noisy communication networks. However, these techniques consume excessive resources such as energy and channel capacity and increase network latency. Therefore, we propose a novel statistical information fusion method not only for structural chain and tree-based sensor networks, but also for unstructured bidirectional graph noisy wireless sensor networks in SG environments. We evaluate the accuracy, energy savings, fusion complexity, and latency of the proposed method by comparing the said parameters with several distributed estimation algorithms using extensive simulations proposing it for several SG applications. Results prove that the overall performance of the proposed method outperforms other fusion techniques for all considered networks. Under Smart Grid communication environments, the proposed method guarantees for best performance in all fusion accuracy, complexity and energy consumption. Analytical upper bounds for the variance of the final aggregated value at the sink node for structured networks are also derived by considering all major errors.

Level Crossing Sampling for Energy Conservation in Wireless Sensor Networks

2011 ◽  
pp. 207-228 ◽  
Author(s):  
Hadi Alasti
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Conservation ◽  
Network Lifetime ◽  
Wireless Sensors ◽  
Large Scale ◽  
Real Life ◽  
Wireless Sensor ◽  
Level Crossing ◽  
Bandlimited Signals

In periodic sampling of the bandlimited signals, many of the consecutive samples are very similar and sometimes the signal remains unchanged over periods of time. These samples can be interpreted as redundant. For this, transmission of all of the periodic samples from all of the sensors in wireless sensor networks is wasteful. The problem becomes more challenging in large scale wireless sensor networks. Level crossing sampling in time is proposed for energy conservation in real-life application of wireless sensor networks to increase the network lifetime by avoiding the transmission of redundant samples. In this chapter, a design framework is discussed for application of level crossing sampling in wireless sensor networks. The performance of level crossing sampling for various level definition schemes are evaluated using computer simulations and experiments with real-life wireless sensors.

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