scholarly journals Integrated data reduction model in wireless sensor networks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Walaa M. El-Sayed ◽  
Hazem M. El-Bakry ◽  
Salah M. El-Sayed
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Finite Impulse Response ◽  
High Energy ◽  
Sensor Nodes ◽  
Recursive Least Squares ◽  
Wireless Sensor ◽  
Radio Communication ◽  
Clustering Model

Wireless sensor networks (WSNs) are periodically collecting data through randomly dispersed sensors (motes), which typically consume high energy in radio communication that mainly leans on data transmission within the network. Furthermore, dissemination mode in WSN usually produces noisy values, incorrect measurements or missing information that affect the behaviour of WSN. In this article, a Distributed Data Predictive Model (DDPM) was proposed to extend the network lifetime by decreasing the consumption in the energy of sensor nodes. It was built upon a distributive clustering model for predicting dissemination-faults in WSN. The proposed model was developed using Recursive least squares (RLS) adaptive filter integrated with a Finite Impulse Response (FIR) filter, for removing unwanted reflections and noise accompanying of the transferred signals among the sensors, aiming to minimize the size of transferred data for providing energy efficient. The experimental results demonstrated that DDPM reduced the rate of data transmission to ∼20%. Also, it decreased the energy consumption to 95% throughout the dataset sample and upgraded the performance of the sensory network by about 19.5%. Thus, it prolonged the lifetime of the network.

scholarly journals A Data-Based Fault-Detection Model for Wireless Sensor Networks

2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Data Transmission ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensors And Actuators ◽  
Detection Model ◽  
Management Platform

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.

scholarly journals Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Energy Efficient ◽  
Fog Computing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hierarchical Routing

Abstract Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime

scholarly journals Performance Analysis of Q-Leach Algorithm in WSN

2020 ◽  
Vol 5 (10) ◽  
pp. 1-4
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Short Range ◽  
Sensor Node ◽  
Life Time ◽  
Time Span ◽  
Sensor Nodes ◽  
Wireless Sensor

Sensor nodes are exceedingly energy compelled instrument, since it is battery operated instruments. In wsn network, every node is liable to the data transmission through the wireless mode [1]. Wireless sensor networks (WSN) is made of a huge no. of small nodes with confined functionality. The essential theme of the wireless sensor network is energy helpless and the WSN is collection of sensor. Every sensor terminal is liable to sensing, store and information clan and send it forwards into sink. The communication within the node is done via wireless network [3].Energy efficiency is the main concentration of a desining the better routing protocol. LEACH is a protocol. This is appropriate for short range network, since imagine that whole sensor node is capable of communication with inter alia and efficient to access sink node, which is not always correct for a big network. Hence, coverage is a problem which we attempt to resolve [6]. The main focus within wireless sensor networks is to increase the network life-time span as much as possible, so that resources can be utilizes efficiently and optimally. Various approaches which are based on the clustering are very much optimal in functionality. Life-time of the network is always connected with sensor node’s energy implemented at distant regions for stable and defect bearable observation [10].

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.

scholarly journals Qualification of Cluster Header and Cluster Member in Wireless Sensor Networks

2019 ◽  
Vol 8 (2S6) ◽  
pp. 101-105
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Sensor Node ◽  
Data Transfer ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node

Many researches have been proposed for efficiency of data transmission from sensor nodes to sink node for energy efficiency in wireless sensor networks. Among them, cluster-based methods have been preferred In this study, we used the angle formed with the sink node and the distance of the cluster members to calculate the probability of cluster head. Each sensor node sends measurement values to header candidates, and the header candidate node measures the probability value of the header with the value received from its candidate member nodes. To construct the cluster members, the data transfer direction is considered. We consider angle, distance, and direction as cluster header possibility value. Experimental results show that data transmission is proceeding in the direction of going to the sink node. We calculated and displayed the header possibility value of the neighbor nodes of the sensor node and confirmed the candidates of the cluster header for data transfer as the value. In this study, residual energy amount of each sensor node is not considered. In the next study, we calculate the value considering the residual energy amount of the node when measuring the header possibility value of the cluster.

scholarly journals AR-RBFS: Aware-Routing Protocol Based on Recursive Best-First Search Algorithm for Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Farzad Kiani
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Data Transmission ◽  
Search Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Second Phase

Energy issue is one of the most important problems in wireless sensor networks. They consist of low-power sensor nodes and a few base station nodes. They must be adaptive and efficient in data transmission to sink in various areas. This paper proposes an aware-routing protocol based on clustering and recursive search approaches. The paper focuses on the energy efficiency issue with various measures such as prolonging network lifetime along with reducing energy consumption in the sensor nodes and increasing the system reliability. Our proposed protocol consists of two phases. In the first phase (network development phase), the sensors are placed into virtual layers. The second phase (data transmission) is related to routes discovery and data transferring so it is based on virtual-based Classic-RBFS algorithm in the lake of energy problem environments but, in the nonchargeable environments, all nodes in each layer can be modeled as a random graph and then begin to be managed by the duty cycle method. Additionally, the protocol uses new topology control, data aggregation, and sleep/wake-up schemas for energy saving in the network. The simulation results show that the proposed protocol is optimal in the network lifetime and packet delivery parameters according to the present protocols.

scholarly journals Detecting malicious nodes using data aggregation protocols in wireless sensor networks

2017 ◽  
Vol 7 (1.1) ◽  
pp. 594
Author(s):  
P. Balamurugan ◽  
M. Shyamala Devi ◽  
V. Sharmila
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Data Aggregation ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Destination Node ◽  
Malicious Nodes ◽  
Secured Data

At present scenario, sensor devices are used in various fields for gathering information so all those data should be secured safely. Securing data is an important role in Wireless Sensor Networks (WSN). WSN is extremely essential for the purpose of reducing the complete redundancy and energy consumption during gathering data among sensor nodes. Optimized data aggregation is needed at cluster head and Base Station (BS) for secured data transmission. Data aggregation is performed in all routers while forwarding data from source to destination node. The complete life time of sensor networks is reducing because of using energy inefficient nodes for the purpose of aggregation. So this paper introduces the optimized methods for securing data (OMSD) which is trust based weights and also completely about the attacks and some methods for secured data transmission. 

scholarly journals Ambrosia: Reduction in Data Transfer from Sensor to Server for Increased Lifetime of IoT Sensor Nodes

2021 ◽  
Author(s):  
Shikhar Suryavansh ◽  
Abu Benna ◽  
Chris Guest ◽  
Somali Chaterji
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Reduction ◽  
Data Transmission ◽  
Data Transfer ◽  
Streaming Data ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Lifetime

Abstract Data transmission accounts for significant energy consumption in wireless sensor networks where streaming data is generated by the sensors. This impedes their use in many settings, including livestock monitoring over large pastures (which forms our target application). We present Ambrosia, a lightweight protocol that utilizes a window-based timeseries forecasting mechanism for data reduction. Ambrosia employs a configurable error threshold to ensure that the accuracy of end applications is unaffected by the data transfer reduction. Experimental evaluations using LoRa and BLE on a real livestock monitoring deployment demonstrate 60% reduction in data transmission and a 2X increase in battery lifetime.

scholarly journals DHCFL: Dual Head Clustering Based on Fuzzy Logic for Wireless Sensor Networks

2020 ◽  
Vol 8 (5) ◽  
pp. 1049-1054
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Data Transmission ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Research Work ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor

Wireless Sensor Networks (WSN) are constructed by interconnecting miniature sensor nodes for monitoring the environment uninterrupted. These miniature nodes are having the sensing, processing and communication capability in a smaller scale powered by a battery unit. Proper energy conservation is required for the entire system. Clustering mechanism in WSN advances the lifetime and stability in the network. It achieves data aggregation and reduces the number of data transmission to the Base station (BS). But the Cluster Head (CH) nodes are affected by rapid energy depletion problem due to overload. A CH node spends its energy for receiving data from its member nodes, aggregation and transmission to the BS. In CH election, multiple overlapping factors makes it difficult and inefficient which costs the lifetime of the network. In recent years, Fuzzy Logic is widely used for CH election mechanism for WSN. But the underlying problem of the CHs node continues. In this research work, a new clustering algorithm DHCFL is proposed which elects two CHs for a cluster which shares the load of a conventional CH node. Data reception and aggregation will be done by CH aggregator (CH-A) node and data transmission to the BS will be carried over by CH relay (CH-R) node. Both CH-A and CH-R nodes are elected through fuzzy logic which addresses the uncertainty in the network too. The proposed algorithm DHCFL is compared and tested in different network scenarios with existing clustering algorithms and it is observed that DHCFL outperforms other algorithms in all the network scenarios.

scholarly journals Communication Availability-Based Scheduling for Fair Data Collection with Path-Constrained Mobile Sink in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Youngtae Jo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Data Transmission ◽  
Sensor Node ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Traffic Load ◽  
Wireless Sensor ◽  
Sink Node

To effectively transfer sensing data to a sink node, system designers should consider the characteristic of wireless sensor networks in the way of data transmission. In particular, sensor nodes surrounding a fixed sink node have routinely suffered from concentrated network traffic so that their battery energy is rapidly exhausted. The lifetime of wireless sensor networks decreases due to the rapid power consumption of these sensor nodes. To address the problem, a mobile sink model has recently been chosen for traffic load distribution among sensor nodes. However, since a mobile sink continuously changes its location in sensor networks, it has a time limitation to communicate with each sensor node and unstable signal strength from each sensor node. Therefore, fair and stable data collection policy between a mobile sink and sensor nodes is necessary in this circumstance. In this paper, we propose a new scheduling policy to support fair and stable data collection for a mobile sink in wireless sensor networks. The proposed policy performs data collection scheduling based on the communication availability of data transmission between sensor nodes and a mobile sink.

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