scholarly journals Error-Aware Data Clustering for In-Network Data Reduction in Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1011 ◽  
Author(s):  
M. K. Alam ◽  
Azrina Abd Aziz ◽  
S. A. Latif ◽  
Azlan Awang
Keyword(s):  
Data Reduction ◽  
Data Clustering ◽  
Large Scale ◽  
Temporal Correlation ◽  
Correlated Data ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Data ◽  
Spatial Correlations ◽  
Redundant Data

A wireless sensor network (WSN) deploys hundreds or thousands of nodes that may introduce large-scale data over time. Dealing with such an amount of collected data is a real challenge for energy-constraint sensor nodes. Therefore, numerous research works have been carried out to design efficient data clustering techniques in WSNs to eliminate the amount of redundant data before transmitting them to the sink while preserving their fundamental properties. This paper develops a new error-aware data clustering (EDC) technique at the cluster-heads (CHs) for in-network data reduction. The proposed EDC consists of three adaptive modules that allow users to choose the module that suits their requirements and the quality of the data. The histogram-based data clustering (HDC) module groups temporal correlated data into clusters and eliminates correlated data from each cluster. Recursive outlier detection and smoothing (RODS) with HDC module provides error-aware data clustering, which detects random outliers using temporal correlation of data to maintain data reduction errors within a predefined threshold. Verification of RODS (V-RODS) with HDC module detects not only random outliers but also frequent outliers simultaneously based on both the temporal and spatial correlations of the data. The simulation results show that the proposed EDC is computationally cheap, able to reduce a significant amount of redundant data with minimum error, and provides efficient error-aware data clustering solutions for remote monitoring environmental applications.

scholarly journals HEAP: Hybrid Energy-efficient Aggregation Protocol for Large Scale Wireless Sensor Networks

2005 ◽  
Vol 4 (2) ◽  
pp. 713-721 ◽  
Author(s):  
Santhosh Simon ◽  
K Paulose Jacob
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Fire Detection ◽  
Temporal Correlation ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Time Data ◽  
Cooperative Effort

Wireless sensor networks (WSNs) can be meritoriously used in several application areas like agriculture, military surveillance, environmental monitoring, forest fire detection etc. Since they are used to monitor large geographic areas numerous sensor nodes are to be deployed and their radio range is also very short. Hence they depend on the cooperative effort of these densely deployed sensor nodes for reporting the sensed data. Any changes in environment or an event of interest may be initially observed in a particular area. In other words, they are correlated in space domain. Many nodes in that area may detect the event and report the same event. This redundant information is of no use to system and also depletes the precious energy of the intermediate sensor nodes. Sensor nodes are having very limited energy and needs to be conserved for attaining maximum network life time. Data aggregation is an effective technique for conserving energy by reducing the packet transmissions. Many aggregation systems are available, but when employed for large scale wireless sensor networks they are less effective. In this paper we propose a scheme for large scale WSNs which effectively uses the spatial correlation and temporal correlation of the data for effective aggregation and thereby preserving precious energy.

scholarly journals Wireless Sensor Networks for Smart Cities: Network Design, Implementation and Performance Evaluation

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 218
Author(s):  
Ala’ Khalifeh ◽  
Khalid A. Darabkh ◽  
Ahmad M. Khasawneh ◽  
Issa Alqaisieh ◽  
Mohammad Salameh ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Experimental Evaluation ◽  
Large Scale ◽  
Performance Metrics ◽  
Smart Cities ◽  
Field Tests ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Real Field

The advent of various wireless technologies has paved the way for the realization of new infrastructures and applications for smart cities. Wireless Sensor Networks (WSNs) are one of the most important among these technologies. WSNs are widely used in various applications in our daily lives. Due to their cost effectiveness and rapid deployment, WSNs can be used for securing smart cities by providing remote monitoring and sensing for many critical scenarios including hostile environments, battlefields, or areas subject to natural disasters such as earthquakes, volcano eruptions, and floods or to large-scale accidents such as nuclear plants explosions or chemical plumes. The purpose of this paper is to propose a new framework where WSNs are adopted for remote sensing and monitoring in smart city applications. We propose using Unmanned Aerial Vehicles to act as a data mule to offload the sensor nodes and transfer the monitoring data securely to the remote control center for further analysis and decision making. Furthermore, the paper provides insight about implementation challenges in the realization of the proposed framework. In addition, the paper provides an experimental evaluation of the proposed design in outdoor environments, in the presence of different types of obstacles, common to typical outdoor fields. The experimental evaluation revealed several inconsistencies between the performance metrics advertised in the hardware-specific data-sheets. In particular, we found mismatches between the advertised coverage distance and signal strength with our experimental measurements. Therefore, it is crucial that network designers and developers conduct field tests and device performance assessment before designing and implementing the WSN for application in a real field setting.

scholarly journals Sensor System: A Survey of Sensor Type, Ad Hoc Network Topology and Energy Harvesting Techniques

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 219
Author(s):  
Phuoc Duc Nguyen ◽  
Lok-won Kim
Keyword(s):  
Energy Harvesting ◽  
Large Scale ◽  
Ad Hoc ◽  
Sensor Nodes ◽  
Sensor System ◽  
Wireless Sensor ◽  
The Internet ◽  
Original Research ◽  
Energy Scavenging ◽  
Term Operation

People nowadays are entering an era of rapid evolution due to the generation of massive amounts of data. Such information is produced with an enormous contribution from the use of billions of sensing devices equipped with in situ signal processing and communication capabilities which form wireless sensor networks (WSNs). As the number of small devices connected to the Internet is higher than 50 billion, the Internet of Things (IoT) devices focus on sensing accuracy, communication efficiency, and low power consumption because IoT device deployment is mainly for correct information acquisition, remote node accessing, and longer-term operation with lower battery changing requirements. Thus, recently, there have been rich activities for original research in these domains. Various sensors used by processing devices can be heterogeneous or homogeneous. Since the devices are primarily expected to operate independently in an autonomous manner, the abilities of connection, communication, and ambient energy scavenging play significant roles, especially in a large-scale deployment. This paper classifies wireless sensor nodes into two major categories based the types of the sensor array (heterogeneous/homogeneous). It also emphasizes on the utilization of ad hoc networking and energy harvesting mechanisms as a fundamental cornerstone to building a self-governing, sustainable, and perpetually-operated sensor system. We review systems representative of each category and depict trends in system development.

Technology Research on the Fault Diagnosis of Wireless Sensor Network System

2013 ◽  
Vol 846-847 ◽  
pp. 442-445
Author(s):  
Chun Lin He
Keyword(s):  
Fault Diagnosis ◽  
Sensor Network ◽  
Simulation Experiment ◽  
Temporal Correlation ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network System ◽  
Technology Research ◽  
Spatio Temporal ◽  
Network Fault

The fault diagnosis technology have emerged and developed rapidly with the development of wireless sensor networks and requirements of applications improve. This paper describes two commonly used sensor network fault modeling. What is more, in order to solve this problem that sensor nodes are vulnerable and therefore produce wrong data, the paper proposes a distributed fault detecting algorithm based on spatio-temporal correlation among data of adjacent nodes. The simulation experiment shows that the algorithm can efficiently detect errors in the network and very few errors are introduced.

scholarly journals Power Reduction with Sleep/Wake on Redundant Data (SWORD) in a Wireless Sensor Network for Energy-Efficient Precision Agriculture

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3450 ◽  
Author(s):  
Haider Jawad ◽  
Rosdiadee Nordin ◽  
Sadik Gharghan ◽  
Aqeel Jawad ◽  
Mahamod Ismail ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Power Consumption ◽  
Precision Agriculture ◽  
Data Communication ◽  
Power Reduction ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Climate Conditions ◽  
Redundant Data ◽  
Comparison Results

The use of wireless sensor networks (WSNs) in modern precision agriculture to monitor climate conditions and to provide agriculturalists with a considerable amount of useful information is currently being widely considered. However, WSNs exhibit several limitations when deployed in real-world applications. One of the challenges faced by WSNs is prolonging the life of sensor nodes. This challenge is the primary motivation for this work, in which we aim to further minimize the energy consumption of a wireless agriculture system (WAS), which includes air temperature, air humidity, and soil moisture. Two power reduction schemes are proposed to decrease the power consumption of the sensor and router nodes. First, a sleep/wake scheme based on duty cycling is presented. Second, the sleep/wake scheme is merged with redundant data about soil moisture, thereby resulting in a new algorithm called sleep/wake on redundant data (SWORD). SWORD can minimize the power consumption and data communication of the sensor node. A 12 V/5 W solar cell is embedded into the WAS to sustain its operation. Results show that the power consumption of the sensor and router nodes is minimized and power savings are improved by the sleep/wake scheme. The power consumption of the sensor and router nodes is improved by 99.48% relative to that in traditional operation when the SWORD algorithm is applied. In addition, data communication in the SWORD algorithm is minimized by 86.45% relative to that in the sleep/wake scheme. The comparison results indicate that the proposed algorithms outperform power reduction techniques proposed in other studies. The average current consumptions of the sensor nodes in the sleep/wake scheme and the SWORD algorithm are 0.731 mA and 0.1 mA, respectively.

scholarly journals Fault-Tolerant Anomaly Detection Method in Wireless Sensor Networks

Information ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 236 ◽  
Author(s):  
Nengsong Peng ◽  
Weiwei Zhang ◽  
Hongfei Ling ◽  
Yuzhao Zhang ◽  
Lixin Zheng
Keyword(s):  
Sensor Networks ◽  
Anomaly Detection ◽  
Sensor Network ◽  
Detection Method ◽  
Fault Tolerant ◽  
False Negative ◽  
False Negative Rate ◽  
Temporal Correlation ◽  
Sensor Nodes ◽  
Wireless Sensor

A key issue in wireless sensor network applications is how to accurately detect anomalies in an unstable environment and determine whether an event has occurred. This instability includes the harsh environment, node energy insufficiency, hardware and software breakdown, etc. In this paper, a fault-tolerant anomaly detection method (FTAD) is proposed based on the spatial-temporal correlation of sensor networks. This method divides the sensor network into a fault neighborhood, event and fault mixed neighborhood, event boundary neighborhood and other regions for anomaly detection, respectively, to achieve fault tolerance. The results of experiment show that under the condition that 45% of sensor nodes are failing, the hit rate of event detection remains at about 97% and the false negative rate of events is above 92%.

scholarly journals A Distributed Collision-Free Data Aggregation Scheme for wireless sensor network

2018 ◽  
Vol 14 (8) ◽  
pp. 155014771879584 ◽  
Author(s):  
Danyang Qin ◽  
Yan Zhang ◽  
Jingya Ma ◽  
Ping Ji ◽  
Pan Feng
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Aggregation ◽  
Large Scale ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Delay ◽  
Free Data ◽  
Aggregation Scheme ◽  
Aggregation Technology

Due to the advantages of large-scale, data-centric and wide application, wireless sensor networks have been widely used in nowadays society. From the physical layer to the application layer, the multiply increasing information makes the data aggregation technology particularly important for wireless sensor network. Data aggregation technology can extract useful information from the network and reduce the network load, but will increase the network delay. The non-exchangeable feature of the battery of sensor nodes makes the researches on the battery power saving and lifetime extension be carried out extensively. Aiming at the delay problem caused by sleeping mechanism used for energy saving, a Distributed Collision-Free Data Aggregation Scheme is proposed in this article to make the network aggregate data without conflicts during the working states periodically changing so as to save the limited energy and reduce the network delay at the same time. Simulation results verify the better aggregating performance of Distributed Collision-Free Data Aggregation Scheme than other traditional data aggregation mechanisms.

scholarly journals EERP-DPM: Energy Efficient Routing Protocol Using Dual Prediction Model for Healthcare Using IoT

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Faris A. Almalki ◽  
Soufiene Ben Othman ◽  
Fahad A. Almalki ◽  
Hedi Sakli
Keyword(s):  
Energy Consumption ◽  
Prediction Model ◽  
Routing Protocol ◽  
Health Care Professionals ◽  
Energy Efficient ◽  
Temporal Correlation ◽  
Sensor Nodes ◽  
Energy Efficient Routing ◽  
Battery Lifetime ◽  
Redundant Data

Healthcare is one of the most promising domains for the application of Internet of Things- (IoT-) based technologies, where patients can use wearable or implanted medical sensors to measure medical parameters anywhere and anytime. The information collected by IoT devices can then be sent to the health care professionals, and physicians allow having a real-time access to patients’ data. However, besides limited batteries lifetime and computational power, there is spatio-temporal correlation, where unnecessary transmission of these redundant data has a significant impact on reducing energy consumption and reducing battery lifetime. Thus, this paper aims to propose a routing protocol to enhance energy-efficiency, which in turn prolongs the sensor lifetime. The proposed work is based on Energy Efficient Routing Protocol using Dual Prediction Model (EERP-DPM) for Healthcare using IoT, where Dual-Prediction Mechanism is used to reduce data transmission between sensor nodes and medical server if predictions match the readings or if the data are considered critical if it goes beyond the upper/lower limits of defined thresholds. The proposed system was developed and tested using MATLAB software and a hardware platform called “MySignals HW V2.” Both simulation and experimental results confirm that the proposed EERP-DPM protocol has been observed to be extremely successful compared to other existing routing protocols not only in terms of energy consumption and network lifetime but also in terms of guaranteeing reliability, throughput, and end-to-end delay.

Applications of Wireless Sensor Networks

2010 ◽  
pp. 1076-1090 ◽  
Author(s):  
Corinna Schmitt ◽  
Georg Carle
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Radio Communication ◽  
Power Resources ◽  
Limited Power

Today the researchers want to collect as much data as possible from different locations for monitoring reasons. In this context large-scale wireless sensor networks are becoming an active topic of research (Kahn1999). Because of the different locations and environments in which these sensor networks can be used, specific requirements for the hardware apply. The hardware of the sensor nodes must be robust, provide sufficient storage and communication capabilities, and get along with limited power resources. Sensor nodes such as the Berkeley-Mote Family (Polastre2006, Schmitt2006) are capable of meeting these requirements. These sensor nodes are small and light devices with radio communication and the capability for collecting sensor data. In this chapter the authors review the key elements for sensor networks and give an overview on possible applications in the field of monitoring.

Sign in / Sign up

Export Citation Format

Share Document