An Optimization Model with Network Edges for Multimedia Sensors Using Artificial Intelligence of Things

In modern years, network edges have been explored by many applications to lower communication and management costs. They are also integrated with the internet of things (IoT) to achieve network design, in terms of scalability and heterogeneous services for multimedia applications. Many proposed solu...

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Autores principales:	Amjad Rehman, Khalid Haseeb, Tanzila Saba, Jaime Lloret, Sandra Sendra
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	multimedia sensors optimizing resources software-defined networks delay controlled artificial intelligence of things Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/c289eea9491347959c975d68a560bc8c
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id	oai:doaj.org-article:c289eea9491347959c975d68a560bc8c
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spelling	oai:doaj.org-article:c289eea9491347959c975d68a560bc8c2021-11-11T19:07:07ZAn Optimization Model with Network Edges for Multimedia Sensors Using Artificial Intelligence of Things10.3390/s212171031424-8220https://doaj.org/article/c289eea9491347959c975d68a560bc8c2021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7103https://doaj.org/toc/1424-8220In modern years, network edges have been explored by many applications to lower communication and management costs. They are also integrated with the internet of things (IoT) to achieve network design, in terms of scalability and heterogeneous services for multimedia applications. Many proposed solutions are performing a vital role in the development of robust protocols and reducing the response time for critical networks. However, most of them are not able to support the forwarding processes of high multimedia traffic under dynamic characteristics with constraint bandwidth. Moreover, they increase the rate of data loss in an uncertain environment and compromise network performance by increasing delivery delay. Therefore, this paper presents an optimization model with mobile edges for multimedia sensors using artificial intelligence of things, which aims to maintain the process of real-time data collection with low consumption of resources. Moreover, it improves the unpredictability of network communication with the integration of software-defined networks (SDN) and mobile edges. Firstly, it utilizes the artificial intelligence of things (AIoT), forming the multi-hop network and guaranteed the primary services for constraints network with stable resources management. Secondly, the SDN performs direct association with mobile edges to support the load balancing for multimedia sensors and centralized the management. Finally, multimedia traffic is heading towards applications in an unchanged form and without negotiating using the sharing of subkeys. The experimental results demonstrated its effectiveness for delivery rate by an average of 35%, processing delay by an average of 29%, network overheads by an average of 41%, packet drop ratio by an average of 39%, and packet retransmission by an average of 34% against existing solutions.Amjad RehmanKhalid HaseebTanzila SabaJaime LloretSandra SendraMDPI AGarticlemultimedia sensorsoptimizing resourcessoftware-defined networksdelay controlledartificial intelligence of thingsChemical technologyTP1-1185ENSensors, Vol 21, Iss 7103, p 7103 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	multimedia sensors optimizing resources software-defined networks delay controlled artificial intelligence of things Chemical technology TP1-1185
spellingShingle	multimedia sensors optimizing resources software-defined networks delay controlled artificial intelligence of things Chemical technology TP1-1185 Amjad Rehman Khalid Haseeb Tanzila Saba Jaime Lloret Sandra Sendra An Optimization Model with Network Edges for Multimedia Sensors Using Artificial Intelligence of Things
description	In modern years, network edges have been explored by many applications to lower communication and management costs. They are also integrated with the internet of things (IoT) to achieve network design, in terms of scalability and heterogeneous services for multimedia applications. Many proposed solutions are performing a vital role in the development of robust protocols and reducing the response time for critical networks. However, most of them are not able to support the forwarding processes of high multimedia traffic under dynamic characteristics with constraint bandwidth. Moreover, they increase the rate of data loss in an uncertain environment and compromise network performance by increasing delivery delay. Therefore, this paper presents an optimization model with mobile edges for multimedia sensors using artificial intelligence of things, which aims to maintain the process of real-time data collection with low consumption of resources. Moreover, it improves the unpredictability of network communication with the integration of software-defined networks (SDN) and mobile edges. Firstly, it utilizes the artificial intelligence of things (AIoT), forming the multi-hop network and guaranteed the primary services for constraints network with stable resources management. Secondly, the SDN performs direct association with mobile edges to support the load balancing for multimedia sensors and centralized the management. Finally, multimedia traffic is heading towards applications in an unchanged form and without negotiating using the sharing of subkeys. The experimental results demonstrated its effectiveness for delivery rate by an average of 35%, processing delay by an average of 29%, network overheads by an average of 41%, packet drop ratio by an average of 39%, and packet retransmission by an average of 34% against existing solutions.
format	article
author	Amjad Rehman Khalid Haseeb Tanzila Saba Jaime Lloret Sandra Sendra
author_facet	Amjad Rehman Khalid Haseeb Tanzila Saba Jaime Lloret Sandra Sendra
author_sort	Amjad Rehman
title	An Optimization Model with Network Edges for Multimedia Sensors Using Artificial Intelligence of Things
title_short	An Optimization Model with Network Edges for Multimedia Sensors Using Artificial Intelligence of Things
title_full	An Optimization Model with Network Edges for Multimedia Sensors Using Artificial Intelligence of Things
title_fullStr	An Optimization Model with Network Edges for Multimedia Sensors Using Artificial Intelligence of Things
title_full_unstemmed	An Optimization Model with Network Edges for Multimedia Sensors Using Artificial Intelligence of Things
title_sort	optimization model with network edges for multimedia sensors using artificial intelligence of things
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/c289eea9491347959c975d68a560bc8c
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An Optimization Model with Network Edges for Multimedia Sensors Using Artificial Intelligence of Things

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