Modelling a Deep Learning-Based Wireless Sensor Network Task Assignment Algorithm

2020 ◽  
pp. 84-109
Author(s):  
Titus Issac ◽  
Salaja Silas ◽  
Elijah Blessing Rajsingh
Keyword(s):  
Deep Learning ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Task Assignment ◽  
Human Interaction ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Feed Forward Neural Network ◽  
Functional Capabilities ◽  
Assignment Algorithm

The 21st century is witnessing the emergence of a wide variety of wireless sensor network (WSN) applications ranging from simple environmental monitoring to complex satellite monitoring applications. The advent of complex WSN applications has led to a massive transition in the development, functioning, and capabilities of wireless sensor nodes. The contemporary nodes have multi-functional capabilities enabling the heterogeneous WSN applications. The future of WSN task assignment envisions WSN to be heterogeneous network with minimal human interaction. This led to the investigative model of a deep learning-based task assignment algorithm. The algorithm employs a multilayer feed forward neural network (MLFFNN) trained by particle swarm optimization (PSO) for solving task assignment problem in a dynamic centralized heterogeneous WSN. The analyses include the study of hidden layers and effectiveness of the task assignment algorithms. The chapter would be highly beneficial to a wide range of audiences employing the machine and deep learning in WSN.

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.

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.

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.

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 Wormhole Detection Mechanism in Wireless Sensor Networks

2020 ◽  
Vol 9 (2) ◽  
pp. 1845-1847
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Base Station ◽  
Sensor Nodes ◽  
Base Stations ◽  
Wireless Sensor ◽  
Health Care Environment ◽  
Detection Mechanism ◽  
Primary Base ◽  
Power And Energy

A Wireless Sensor Network (WSN) is a component with sensor nodes that continuously observes environmental circumstances. Sensor nodes accomplish different key operations like sensing temperature and distance. It has been used in many applications like computing, signal processing, and network selfconfiguration to expand network coverage and build up its scalability. The Unit of all these sensors that exhibit sensing and transmitting information will offer more information than those offered by autonomously operating sensors. Usually, the transmitting task is somewhat critical as there is a huge amount of data and sensors devices are restricted. Being the limited number of sensor devices the network is exposed to different types of attacks. The Traditional security mechanisms are not suitable for WSN as they are generally heavy and having limited number of nodes and also these mechanisms will not eliminate the risk of other attacks. WSN are most useful in different crucial domains such as health care, environment, industry, and security, military. For example, in a military operation, a wireless sensor network monitors various activities. If an event is detected, these sensor nodes sense that and report the data to the primary (base) station (called sink) by making communication with other nodes. To collect data from WSN base Stations are commonly used. Base stations have more resources (e.g. computation power and energy) compared to normal sensor nodes which include more or less such limitations. Aggregation points will gather the data from neighboring sensor nodes to combine the data and forward to master (base) stations, where the data will be further forwarded or processed to a processing center. In this manner, the energy can be preserved in WSN and the lifetime of network is expanded.

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