Monitoring Nodes Research Articles

Optimal layout of pressure monitoring points in water supply network based on Optics

It is necessary to monitor the pressure in the networks in real time, when we face the problem of pipe burst and leakage in urban water supply network. Therefore, it is particularly important to arrange pressure monitoring points in appropriate places in the pipeline networks. The pressure monitoring point layout is often based on similar degree of the node pressure data in the current stage. A method of optimal pressure monitoring point location in the urban water distribution networks was proposed in this paper. Since the above method did not consider spatial properties of network node. The original feature matrix data is constructed by acquiring the spatial attributes of the pressure monitoring nodes and calculating the non-spatial attributes of the nodes. The original feature matrix data will be normalized. Then the Optics clustering algorithm is used to cluster the normalized node feature matrix data to determine the location and number of pressure monitoring points in monitoring area of urban water distribution networks. Experimental results show that the method effectively ensures that the pressure monitoring points can grasp the pressure information of the whole water supply network more comprehensively and rationally, improves the economy of the pressure monitoring points layout, and provides good guidance for the actual layout of pressure monitoring points in municipal water distribution networks.

Development of Modular Cable-Driven Parallel Robotic Systems

Task-oriented modular design and safety monitoring are demonstrated to be outstanding challenges for robots in practical application. In order to obtain better flexibility and better obstacles avoidance capability, design and analysis of a modular cable-driven parallel robot (MCDPR) are presented in this paper, which can be reconfigured to several configurations in engineering applications by changing the number of the mobile modules and the connection mode of the end effector. With regard to the motion control and safety monitoring system, the design and implementation of hardware and software are presented. An experimental prototype for the MCDPR is developed, followed by a brief illustration of the connection mode between the end effector and cables, and the installation of monitoring nodes. The performance of the MCDPR is discussed experimentally, including real-time pose monitoring and obstacle avoidance. The results verify the feasibility and efficiency of kinematics model and obstacle avoidance method, and the results also indicate that the designed motion control and safety monitoring system can realize trajectory tracking control, real-time safety monitoring, and obstacle avoidance for the MCDPR.

Path Optimization of Mobile Sink Node in Wireless Sensor Network Water Monitoring System

In the water area monitoring of the traditional wireless sensor networks (WSNs), the monitoring data are mostly transmitted to the base station through multihop. However, there are many problems in multihop transmission in traditional wireless sensor networks, such as energy hole, uneven energy consumption, unreliable data transmission, and so on. Based on the high maneuverability of unmanned aerial vehicles (UAVs), a mobile data collection scheme is proposed, which uses UAV as a mobile sink node in WSN water monitoring and transmits data wirelessly to collect monitoring node data efficiently and flexibly. In order to further reduce the energy consumption of UAV, the terminal nodes are grouped according to the dynamic clustering algorithm and the nodes with high residual energy in the cluster are selected as cluster head nodes. Then, according to the characteristics of sensor nodes with a certain range of wireless signal coverage, the angular bisection method is introduced on the basis of the traditional ant colony algorithm to plan the path of UAV, which further shortens the length of the mobile path. Finally, the effectiveness and correctness of the method are proved by simulation and experimental tests.

IPS: Incentive and Punishment Scheme for Omitting Selfishness in the Internet of Vehicles (Iov)

Internet of Vehicles (IoV) is a new emerging concept and is an extended notion of Vehicular Ad-hoc networks (VANETs). In IoV the vehicles (nodes) are connected to the internet and able to transmit information. However, due to resources constraint nature of vehicles, they may not want to cooperate in order to save its own resources such as memory, energy, and buffer, etc. This behavior may lead to poor system performance. IoV needs an efficient solution to motivate the nodes in terms of cooperation to avoid selfish behavior. A novel mechanism Incentive and Punishment Scheme (IPS) has been proposed in this article where vehicles with higher weight and cooperation are elected as Heads during the election process. Vickrey, Clarke, and Groves (VCG) model has been used to scrutinize the weight of these heads. Vehicle participating in the election process can increase its incentives (reputation) by active participation (forwarding data). Vehicles with repeated selfish behavior are punished. The monitoring nodes monitor the performance of their neighbor nodes after the election process. A mathematical model and algorithms has been developed for the election, monitoring and incentive processes. The proposed approach has been simulated through VDTNSim environment to analyze the performance of the proposed IPS. The performance results demonstrate that the proposed schemes outperform the existing schemes in terms of packet delivery ratio, average delivery delay, average cost, and overhead.

Malicious node detection through run time self-healing algorithm in WSN

Wireless sensor network possess a large number of randomly deployed nodes. These nodes configure themselves to form a network. WSNs' major role is to monitor the environment, collect the data and communicate the data to the base node. The originality of the data communicated by the WSN nodes is an important criterion to avoid failure in the network. So, self-healing techniques are implemented to overcome the losses of data in routing due to misbehaving nodes. However, major protocols designed for self-healing are not energy constrained and not suitable for battery powered network. In this paper, we propose a new run-time self-healing algorithm which possesses individual monitoring node capable of scanning the data and evaluate the stability of the nodes to ensure proper communication in the network. The proposed method is compared with self-healing hybrid sensor network architecture (SASHA) and error correction code (ECC) algorithm to validate the proposed system efficiency. The simulation results show that the proposed algorithm improves efficiency by 86%.

Real-Time Image Transmission Algorithm in WSN with Limited Bandwidth

In this paper, a real-time image transmission algorithm in WSN with limited bandwidth networks is studied. Firstly, a simple and effective monitoring network architecture is established, which allows multiple video monitoring nodes to access the network, and the data transmission is controlled by the synchronization mechanism without collision. Then, the image data is compressed locally at the monitoring nodes (over 85%), so that the image of each node can meet the needs of real-time data transmission, and the overall power consumption of the system is greatly reduced. Finally, based on NVIDIA TX1, four test nodes are constructed to test the algorithm cumulatively, which verifies the effectiveness of the system framework and compression algorithm.

Design, modeling and experimental verification of circular Halbach electromagnetic energy harvesting from bearing motion

Recently, bearing health condition monitoring has attracted considerable attention due to its great significance to prolong the lifespan and improve the system reliability of key industrial equipments. For the purpose of improving the reliability and effectiveness of energy harvesting in the monitoring node of industrial equipments, this paper proposes circular Halbach electromagnetic energy harvesters for extracting the electrical energy from the rotational motion of bearings to supply the monitoring units. The magnetic distribution model of the circular Halbach array is derived to investigate the magnetic field enhancement using different arrangement modes and structural parameters. The effect of gap, magnetic shape and distribution radius on the magnetic field is numerically discussed to obtain the proper configuration of circular Halbach array for performance enhancement. The experimental results of the fabricated prototype demonstrate the effectiveness of the proposed model and optimization design for enhancing the energy harvesting performance. Moreover, voltage response and power output under different connection modes of multi-coil are experimentally discussed for increasing efficiency and reducing the cost and difficulty of interface circuits. Under the rotational speed from 600 rpm to 1000 rpm, the proposed harvester can generate the voltage of 2.79–4.59 V and the maximum average power of 50.8–131.1 mW.

Research on Routing Protocol of Real-time Monitoring Nodes in Transformer Substation

The safety, stability and reliability of electrical equipment are directly related to the operation of the electrical system. Discovering various electrical equipment problems and effective treatment of the problem without delay will minimize the probability of electrical equipment failure. In electrical equipment monitoring and maintenance, Application of real-time monitoring is one of the most important elements. Real-time monitoring node can detect equipment failure promptly which will avoid the expansion of accident caused by the long test period or manual inspection. Working time of online monitoring nodes is limited by power consumption of node itself. Application of routing protocol can optimize energy consumption and extend working time of nodes.

A Wireless Sensor Monitoring Node Based for Paddy Field Environment Using IoT

A Wireless Sensor Monitoring Node Based for Paddy Field Environment Using IoT

Resource and Virtual Function Status Monitoring in Network Function Virtualization Environment

In Network Function Virtualization, in order to improve the utilization of the underlying resources and effectively deploy the service chain dynamically, we will use the management and orchestration to monitor the network resources and virtual function status in real time, but real-time monitoring will result in a certain communication overhead. In this paper, a resource state agent monitoring strategy is designed. The improved label propagation algorithm divides network to subnet and selects the agent monitoring node, which realizes the real-time monitoring of resource status and minimizes the monitoring information communication overhead. Simulation results show that the monitoring strategy proposed in this paper reduces the overhead of monitoring information communication about 15%.

Game-theoretic network bandwidth distribution for self-adaptive cameras

Devices sharing a network compete for bandwidth, being able to transmit only a limited amount of data. This is for example the case with a network of cameras, that should record and transmit video streams to a monitor node for video surveillance. Adaptive cameras can reduce the quality of their video, thereby increasing the frame compression, to limit network congestion. In this paper, we exploit our experience with computing capacity allocation to design and implement a network bandwidth allocation strategy based on game theory, that accommodates multiple adaptive streams with convergence guarantees. We conduct some experiments with our implementation and discuss the results, together with some conclusions and future challenges.

Averting Cascading Failures in Networked Infrastructures: Poset-Constrained Graph Algorithms

Cascading failures in critical networked infrastructures that result even from a single source of failure often lead to rapidly widespread outages as witnessed in the 2013 Northeast blackout in Northern America. The ensuing problem of containing future cascading failures by placement of protection or monitoring nodes in the network is complicated by the uncertainty of the failure source and the missing observation of how the cascading might unravel, be it the past cascading failures or the future ones. This paper examines the problem of minimizing the outage when a cascading failure from a single source occurs. A stochastic optimization problem is formulated where a limited number of protection nodes, when placed strategically in the network to mitigate systemic risk, can minimize the expected spread of cascading failure. We propose the vaccine centrality, which is a network centrality based on the partially ordered sets (poset) characteristics of the stochastic program and distributed message-passing, to design efficient approximation algorithms with provable approximation ratio guarantees. In particular, we illustrate how the vaccine centrality and the poset-constrained graph algorithms can be designed to tradeoff between complexity and optimality, as illustrated through a series of numerical experiments. This paper points toward a general framework of network centrality as statistical inference to design rigorous graph analytics for statistical problems in networks.

Method of Locating the Disturbance Source of Forced Power Oscillation Based on Equivalent Electrical Distance

This paper proposes a novel method of locating the disturbance source of forced power oscillation based on equivalent electrical distance. Firstly, actual grid nodes are mapped onto complex plane on the basis of equivalent electrical distance theory. Secondly, PMU monitoring nodes are selected according to the defined index of coupling degree of generator and load. Lastly, the disturbance source is effectively located by resolving optimization problem based on Geiger theory on seismology and the half-plane method. This proposed method can be implemented by acquiring and analyzing waveforms of frequency variance of several monitoring nodes, and is of great practical value for actual grid. A simulation for IEEE 30-buses system verified the validity and accuracy of this locating method.

Mechanical Vibration Monitoring System Based on Wireless Sensor Network

In order to solve the problem of mechanical vibration monitoring, a mechanical vibration monitoring system based on wireless sensor network was designed.First, the requirements of the hardware of the wireless rotating mechanical vibration monitoring system were analyzed. The monitoring node and base station node were designed.Then, based on the VisualBasic6.0 development tool, a software for monitoring the vibration of rotating machinery was designed. It had the functions of command control, data waveform display, and network topology display.In the mode of wireless mechanical vibration monitoring, the organization mode of the network, the transmission mode of data and the corresponding packet transmission format were improved.Finally, the reliable transmission of the data was verified. Compared with the traditional cable vibration sensor, the performance of the monitoring system was verified.The results showed that the wireless vibration monitoring system designed in this paper met the requirements for the monitoring of the vibration state of the rotating machinery.

A Lightweight Intrusion Detection Method Based on Fuzzy Clustering Algorithm for Wireless Sensor Networks

For resource-constrained wireless sensor networks (WSNs), designing a lightweight intrusion detection technology has been a hot and difficult issue. In this paper, we proposed a lightweight intrusion detection method that was able to directly map the network status into sensor monitoring data received by base station, so that base station can sense the abnormal changes in the network. Our method is highlighted by the fusion of fuzzy c-means algorithm, one-class SVM, and sliding window procedure to effectively differentiate network attacks from abnormal data. Finally, the proposed method was tested on the wireless sensor network simulation software EXata and in real applications. The results showed that the intrusion detection method in this paper could effectively identify whether the abnormal data came from a network attack or just a noise. In addition, extra energy consumption can be avoided in all sensor monitoring nodes of the sensor network where our method has been deployed.

Dynamic cluster heads selection and data aggregation for efficient target monitoring and tracking in wireless sensor networks

Due to energy limitation in wireless sensor networks, clustering is an efficient scheme which has been widely used in building practical wireless sensor networks, and various cluster head selection methods have been proposed nowadays. However, less emphasis was placed on the application constraints cluster head selection. In traditional clustering wireless sensor networks, cluster head is always located at the cluster centre and cannot detect an intruding target since the target first transits the border. Moreover, the data sensed from a target are sent by each cluster head through different routings to the sink so that it cannot be aggregated efficiently near the data source. In order to address these problems, this article proposes an efficient target tracking approach, in which the nodes on the edge of a cluster instead of the centred nodes are chosen as cluster heads so that cluster heads can serve as manager and monitoring node. Furthermore, we choose a collecting cluster head to collect the sensed data from the cluster heads around the target to facilitate data aggregation. Hence, the sensed data can be aggregated near to the data source, which avoids the data long-distance transmission and reduces data gathering costs. Moreover, each cluster head has different lifetime in the efficient target tracking approach according to its location and residual energy to balance the energy cost. Experimental results show that efficient target tracking approach outperformed the state-of-the-art approaches by improving the energy consumption as well as prolonging the network lifetime by about 20% as the 20% nodes die.

An Energy-Efficient Multiobjective Scheduling Model for Monitoring in Internet of Things

To ensure robustness in wireless networks, monitoring the network state, performance and functioning of the nodes and links is crucial, especially for critical applications. This paper targets Internet of Things (IoT) networks. In the IoT, devices (things) are vulnerable due to security risks from the Internet. Moreover, they are resource-constrained and connected via lossy links. This paper addresses the optimized scheduling of the monitoring role between the embedded devices in IoT networks. The objective is to minimize energy consumption and communication overhead of monitoring, for each node. Several subsets of the potential monitoring nodes are generated by solving a minimal vertex cover (VC) problem with constraint generation. Assuming periodical functioning, VCs are optimally assigned to time periods in order to distribute the monitoring role throughout the entire network. The assignment of VCs to periods is modeled as a multiobjective generalized assignment problem. To further optimize the energy consumption of the monitors, they are sequenced across time periods to minimize the state transitions of nodes. This part of the problem is modeled as a traveling salesman path problem. The proposed model is tested on randomly generated instances and the experimental results illustrate its effectiveness to optimize the scheduled monitoring for fault tolerance in IoT networks.

SECA on MIA-DTN: Tackling the Energy Issue in Monitor Incorporated Adaptive Delay Tolerant Network Using a Simplistic Energy Conscious Approach

It has been more than a decade since the inception of the Delay Tolerant Network (DTN)—a medium of communication between heterogeneous, fickle and energy hungry nodes. Since then quite a many variations of the original model have been proposed. One such variation is the Monitor Incorporated Adaptive DTN (MIA-DTN), which has special monitor nodes to keep an eye on the performance of the other nodes in the network. Like any other variant of DTN, it is crippled by the “energy drainage” issue. As such we propose to apply the Simplistic Energy Conscious Approach (SECA) on this network. SECA administers routing of messages to nodes with sufficient remaining energy levels such that the bulk of messages forwarded are in proportion to the receiver’s energy level. To achieve this it employs two threshold values. MIA-DTN has two pre-existing routing protocols tailor made for it, which are energy unconscious. This paper studies the effect of applying SECA on MIA-DTN and presents a comprehensive analysis with simulation results to justify the proposal.

A Game Theory Based Multi Layered Intrusion Detection Framework for Wireless Sensor Networks

Most of the existing intrusion detection frameworks proposed for wireless sensor networks (WSNs) are computation and energy intensive, which adversely affect the overall lifetime of the WSNs. In addition, some of these frameworks generate a significant volume of IDS traffic, which can cause congestion in bandwidth constrained WSNs. In this paper, we aim to address these issues by proposing a game theory based multi layered intrusion detection framework for WSNs. The proposed framework uses a combination of specification rules and a lightweight neural network based anomaly detection module to identify the malicious sensor nodes. Additionally, the framework models the interaction between the IDS and the sensor node being monitored as a two player non-cooperative Bayesian game. This allows the IDS to adopt probabilistic monitoring strategies based on the Bayesian Nash Equilibrium of the game and thereby, reduce the volume of IDS traffic introduced into the sensor network. The framework also proposes two different reputation update and expulsion mechanisms to enforce cooperation and discourage malicious behavior among monitoring nodes. These mechanisms are based on two different methodologies namely, Shapley Value and Vickery–Clark–Grooves (VCG) mechanism. The complexity analysis of the proposed reputation update and expulsion mechanisms have been carried out and are shown to be linear in terms of the input sizes of the mechanisms. Simulation results show that the proposed framework achieves higher accuracy and detection rate across wide range of attacks, while at the same time minimizes the overall energy consumption and volume of IDS traffic in the WSN.

Performance Analysis of Location Based Smart Catastrophe Monitoring System Using WSN

Sudden accident in factories causes huge damage to human life and property which is a serious problem. The fire incident of Baldia Town factory Karachi, Pakistan on September 11, 2012, took precious lives of approximately 259 workers. In order to overcome such catastrophe, a reliable system based on Wireless Sensor Network (WSN) is proposed. The WSNs are considered as emerging, reliable and advantageous technologies due to their self-configuring and self-organizing capabilities. Sensors are integrated to collect the required data. The system not only monitors catastrophe inside the factory but also generate alerts at the same instant to the nearby places (i.e. Residential Areas, Schools etc.). The sole purpose is to inform the workers (working inside the factory) and people (residing within factory premises) about the worst situation and hence save their lives. The proposed work revolves around two scenarios of system deployment. First is using fixed monitoring nodes and other is using mobile monitoring nodes. The prototype is firstly tested within the normal environment, secondly, with high intensity of the fire, and thirdly when the intensity of fire is kept low. It is evident from the graphs that the readings are continuously being updated not only on the display (receiver node) placed at the emergency center within the factory but on the web page as well and it then generates various emergency notifications via android application, web page and SMS. Graphs taken under different environments also show that the alarms are generated as soon as the readings cross threshold levels indicates catastrophe. To the best of our knowledge, no such system is available in the market which is generating alerts using multiple ways, hence makes the proposed system more authenticated. For mobile node scenario, this work deals with the fundamental challenge of wireless sensor networks i.e. node localization which describes that the readings obtained from a node must define the position where it is deployed. Therefore, localization technique is also introduced for catastrophe monitoring system. Location of nodes can make rapid responses to encounter the catastrophe before it reaches the intensity. RSSI Based Trilateration and Centroid Algorithm is introduced to find the location of nodes.