scholarly journals An Efficient Multitask Scheduling Model for Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Hongsheng Yin ◽  
Honggang Qi ◽  
Jingwen Xu ◽  
Xin Huang ◽  
Anping He
Keyword(s):  
Wireless Sensor Network ◽  
Data Processing ◽  
Sensor Network ◽  
Queuing Theory ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Queuing Model ◽  
Average Delay ◽  
Data Packets ◽  
Proposed Model

The sensor nodes of multitask wireless network are constrained in performance-driven computation. Theoretical studies on the data processing model of wireless sensor nodes suggest satisfying the requirements of high qualities of service (QoS) of multiple application networks, thus improving the efficiency of network. In this paper, we present the priority based data processing model for multitask sensor nodes in the architecture of multitask wireless sensor network. The proposed model is deduced with the M/M/1 queuing model based on the queuing theory where the average delay of data packets passing by sensor nodes is estimated. The model is validated with the real data from the Huoerxinhe Coal Mine. By applying the proposed priority based data processing model in the multitask wireless sensor network, the average delay of data packets in a sensor nodes is reduced nearly to 50%. The simulation results show that the proposed model can improve the throughput of network efficiently.

scholarly journals DATA TRAFFIC TRUST MODEL FOR CLUSTERED WIRELESS SENSOR NETWORK

2021 ◽  
Vol 9 (1) ◽  
pp. 1225-1229
Author(s):  
Dr. Senthilkumar A, Dr. Lekashri S, Abhay Chaturvedi, Dr. R. Manikandan
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Trust Management ◽  
Large Scale ◽  
Sampling Rate ◽  
Trust Model ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Data Traffic ◽  
Data Packets

Trust is an essential parameter among sensor nodes to provide secured and successful communication. Many trust management schemes have been proposed earlier for large scale Wireless Sensor Network (WSN) however not cooperates well in terms of low dependability, memory overheads, large communication etc, therefore a system called Data Traffic Trust Scheme (DTTS) for clustered WSN is proposed here. Here the trust nodes are identified through the data traffic sampling rate. The trust rate is identified through the number of sent and receive data packets and the malicious packets are diagnosed through the un-matching packet rate. The simulation results are evaluated to show the efficiency for the proposed scheme.

scholarly journals SRDA: Smart Reputation-Based Data Aggregation Protocol for Wireless Sensor Network

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Chaoran Li ◽  
Yun Liu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Aggregation ◽  
Data Accuracy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Threats ◽  
Wireless Sensor Nodes ◽  
Data Packets ◽  
Multihop Network

Wireless sensor network is a self-organizing multihop network, which is composed of a large number of wireless sensor nodes and usually deployed in unattended environment to collect target information. At present, WSN is facing a growing range of security threats owing to its wireless and resource-constrained characteristics. Compromised sensor nodes can easily corrupt data accuracy and integrity by falsifying sensed information, selectively forwarding or misdirecting received data packets during the process of data aggregation. To solve these security problems, we propose a smart reputation-based data aggregation protocol for WSNs (SRDA) that can provide adequate protection of data accuracy and integrity for wireless sensor network. The simulation results indicate that SRDA can effectively identify the compromised nodes and isolate them from the network by the deployment of the smart reputation system.

scholarly journals A Novel Wireless Sensor Network Architecture Based on Cloud Computing and Big Data

2017 ◽  
Vol 13 (12) ◽  
pp. 18 ◽  
Author(s):  
Changtong Song
Keyword(s):  
Big Data ◽  
Wireless Sensor Network ◽  
Data Processing ◽  
Sensor Network ◽  
Network Architecture ◽  
Wireless Sensor ◽  
Big Data Processing ◽  
Optimal Network ◽  
Proposed Model ◽  
The Relationship

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: DE; mso-bidi-language: AR-SA;">To explore big data processing and its application in wireless sensor network (WSN), this paper studies structural construction of the WSN based on big data processing, and numerically simulates SVC4WSN and MDF4LWSN architectures. Moreover, the relationship between the optimal network layer and node communication radius was verified at different node densities. The results indicate that the proposed model achieved better lifecycle and loading balancing effect than the other network.</span>

An Effective Congestion Control Algorithm based on Traffic Assignment and Reassignment in Wireless Sensor Network

2020 ◽  
Vol 13 (8) ◽  
pp. 1166-1174
Author(s):  
Chao Wang
Keyword(s):  
Wireless Sensor Network ◽  
Congestion Control ◽  
Sensor Network ◽  
Traffic Assignment ◽  
Transmission Rate ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Detection ◽  
Detection Technology ◽  
Average Transmission

Background: It is important to improve the quality of service by using congestion detection technology to find the potential congestion as early as possible in wireless sensor network. Methods: So an improved congestion control scheme based on traffic assignment and reassignment algorithm is proposed for congestion avoidance, detection and mitigation. The congestion area of the network is detected by predicting and setting threshold. When the congestion occurs, sensor nodes can be recovery quickly from congestion by adopting reasonable method of traffic reassignment. And the method can ensure the data in the congestion areas can be transferred to noncongestion areas as soon as possible. Results: The simulation results indicate that the proposed scheme can reduce the number of loss packets, improve the throughput, stabilize the average transmission rate of source node and reduce the end-to-end delay. Conclusion: : So the proposed scheme can enhance the overall performance of the network. Keywords: wireless sensor network; congestion control; congestion detection; congestion mitigation; traffic assignment; traffic reassignment.

A Study of Malware Propagation Dynamics in Wireless Sensor Network using Spatially Correlated Security Model

2020 ◽  
Vol 13 ◽  
Author(s):  
Satya Ranjan Biswal ◽  
Santosh Kumar Swain
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Network ◽  
Spatial Correlation ◽  
Malicious Code ◽  
Wireless Sensor ◽  
Epidemic Theory ◽  
Malware Propagation ◽  
Proposed Model ◽  
Propagation Dynamics

: Security is one of the important concern in both types of the network. The network may be wired or wireless. In case of wireless network security provisioning is more difficult in comparison to wired network. Wireless Sensor Network (WSN) is also a type of wireless network. And due to resource constraints WSN is vulnerable against malware attacks. Initially, the malware (virus, worm, malicious code, etc.) targets a single node of WSN for attack. When a node of WSN gets infected then automatically start to spread in the network. If nodes are strongly correlated the malware spreads quickly in the network. On the other hand, if nodes are weakly correlated the speed of malware spread is slow. A mathematical model is proposed for the study of malware propagation dynamics in WSN with combination of spatial correlation and epidemic theory. This model is based on epidemic theory with spatial correlation. The proposed model is Susceptible-Exposed-Infectious-Recover-Dead (SEIRD) with spatial correlation. We deduced the expression of basic reproduction number. It helps in the study of malware propagation dynamics in WSN. The stability analysis of the network has been investigated through proposed model. This model also helps in reduction of redundant information and saving of sensor nodes’ energy in WSN. The theoretical investigation verified by simulation results. A spatial correlation based epidemic model has been formulated for the study of dynamic behaviour of malware attacks in WSN.

scholarly journals A Remote Monitoring System of Logistics Carrier Based on Wireless Sensor Network

2018 ◽  
Vol 14 (01) ◽  
pp. 4
Author(s):  
Wang Weidong
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Monitoring Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Remote Monitoring System ◽  
Monitoring Center

To improve the efficiency of the remote monitoring system for logistics transportation, we proposed a remote monitoring system based on wireless sensor network and GPRS communication. The system can collect information from the wireless sensor network and transmit the information to the ZigBee interpreter. The monitoring system mainly includes the following parts: Car terminal, GPRS transmission network and monitoring center. Car terminal mainly consists by the Zigbee microcontroller and peripherals, wireless sensor nodes, RFID reader, GPRS wireless communication module composed of a micro-wireless monitoring network. The information collected by the sensor communicates through the GPRS and the monitoring center on the network coordinator, sends the collected information to the monitoring center, and the monitoring center realizes the information of the logistics vehicle in real time. The system has high applicability, meets the design requirements in the real-time acquisition and information transmission of the information of the logistics transport vehicles and goods, and realizes the function of remote monitoring.

Cross layer design with extensive virtual MIMO: FS-MUP optimization model for wireless sensor network

2020 ◽  
pp. 1-16
Author(s):  
Monali Prajapati ◽  
Dr. Jay Joshi
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Multiple Input Multiple Output ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Cross Layer Design ◽  
Virtual Mimo ◽  
Proposed Model ◽  
Multiple Input ◽  
Input Multiple Output

In the wireless sensor network (WSN), wireless communication is said to be the dominant power-consuming operation and it is a challenging one. Virtual Multiple-Input–Multiple-Output (V-MIMO) technology is considered to be the energy-saving method in the WSN. In this paper, a novel multihop virtual MIMO communication protocol is designed in the WSN via cross-layer design to enhance the energy efficiency, reliability, and end-to-end (ETE) and Quality of Service (QoS) provisioning. On the basis of the proposed protocol, the optimal set of parameters concerning the transmission and the overall consumed energy by each of the packets is found. Furthermore, the modeling of ETE latency and throughput of the protocol takes place with respect to the bit-error-rate (BER). A novel hybrid optimization algorithm referred as Flight Straight Moth Updated Particle Swarm Optimization (FS-MUP) is introduced to find the optimal BER that meets the QoS, ETE requirements of each link with lower power consumption. Finally, the performance of the proposed model is evaluated over the extant models in terms of Energy Consumption and BER as well.

Handling Failures of Static Sensor Nodes in Wireless Sensor Network by Use of Mobile Sensors

2011 ◽  
Author(s):  
Edison Pignaton de Freitas ◽  
Tales Heimfarth ◽  
Ivayr Farah Netto ◽  
Carlos Eduardo Pereira ◽  
Armando Morado Ferreira ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Mobile Sensors ◽  
Wireless Sensor

SE: A Simple and Efficient Strategy for Clustering and Routing in WSN

2014 ◽  
Vol 701-702 ◽  
pp. 1025-1028
Author(s):  
Yu Zhu Liang ◽  
Meng Jiao Wang ◽  
Yong Zhen Li
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocols ◽  
Information Needs ◽  
Network Performance ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Clustering Method ◽  
Position Information ◽  
Two Parameters

Clustering the sensor nodes and choosing the way for routing the data are two key elements that would affect the performance of a wireless sensor network (WSN). In this paper, a novel clustering method is proposed and a simple two-hop routing model is adopted for optimizing the network layer of the WSN. New protocol is characterized by simplicity and efficiency (SE). During the clustering stage, no information needs to be shared among the nodes and the position information is not required. Through adjustment of two parameters in SE, the network on any scale (varies from the area and the number of nodes) could obtain decent performance. This work also puts forward a new standard for the evaluation of the network performance—the uniformity of the nodes' death—which is a complement to merely taking the system lifetime into consideration. The combination of these two aspects provides a more comprehensive guideline for designing the clustering or routing protocols in WSN.

scholarly journals Overcoming Localization Errors due to Node Power Drooping in a Wireless Sensor Network

2011 ◽  
Vol 57 (3) ◽  
pp. 341-346 ◽  
Author(s):  
Safdar Khan ◽  
Boubaker Daachi ◽  
Karim Djouani
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Vital Role ◽  
Position Estimation ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Voltage ◽  
Localization Errors ◽  
Anchor Nodes ◽  
Received Signal Strength Indication

Overcoming Localization Errors due to Node Power Drooping in a Wireless Sensor NetworkReceived Signal Strength Indication (RSSI) plays a vital role in the range-free localization of sensor nodes in a wireless sensor network and a good amount of research has been made in this regard. One important factor is the battery voltage of the nodes (i.e., the MICAz sensors) which is not taken into account in the existing literature. As battery voltage level performs an indispensable role for the position estimation of sensor nodes through anchor nodes therefore, in this paper, we take into a account this crucial factor and propose an algorithm that overcomes the problem of decaying battery. We show the results, in terms of more precise localization of sensor nodes through simulation. This work is an extension to [1] and now we also use neural network to overcome the localization errors generated due to gradual battery voltage drooping.

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