Adaptive aggregation based IoT traffic patterns for optimizing smart city network performance
Internet of Things (IoT) technology drives lifestyle changes in smart city infrastructure due to rapid growth of services and activities that develop well-being. One of the main challenges that resulted from the exponential spread of IoT is the dense number of nodes with the huge amount of data over...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016822002113 |
| _version_ | 1797978813276094464 |
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| author | Amin S. Ibrahim Khaled Y. Youssef Ahmed H. Eldeeb Mohamed Abouelatta Hesham Kamel |
| author_facet | Amin S. Ibrahim Khaled Y. Youssef Ahmed H. Eldeeb Mohamed Abouelatta Hesham Kamel |
| author_sort | Amin S. Ibrahim |
| collection | DOAJ |
| description | Internet of Things (IoT) technology drives lifestyle changes in smart city infrastructure due to rapid growth of services and activities that develop well-being. One of the main challenges that resulted from the exponential spread of IoT is the dense number of nodes with the huge amount of data over different networks that influence the collision probability, and network congestion. Existing aggregation techniques worked to solve these challenges with overlooking the IoT traffic characteristics and their types. In this paper, adaptive aggregation techniques are proposed based on IoT traffic types to overcome IoT network issues. These techniques can abstract data, reduce number of packets sent with low traffic congestion, and reduce the recurring packet headers. The proposed adaptive aggregation techniques are accomplished over the IoT smart city networks that are architectured and practically tested to examine the simulation results. It is anticipated that the adaptive aggregation results could optimize the operational efficiency of IoT smart city networks in most key performance metrics, compared to the existing aggregation techniques. |
| first_indexed | 2024-04-11T05:29:38Z |
| format | Article |
| id | doaj.art-b6fccdc43b924fa49c1914260fe0ff50 |
| institution | Directory Open Access Journal |
| issn | 1110-0168 |
| language | English |
| last_indexed | 2024-04-11T05:29:38Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj.art-b6fccdc43b924fa49c1914260fe0ff502022-12-23T04:38:06ZengElsevierAlexandria Engineering Journal1110-01682022-12-01611295539568Adaptive aggregation based IoT traffic patterns for optimizing smart city network performanceAmin S. Ibrahim0Khaled Y. Youssef1Ahmed H. Eldeeb2Mohamed Abouelatta3Hesham Kamel4Electronics and Communications Engineering Department, Thebes Higher Institute for Engineering, Cairo, Egypt; Corresponding author.Communications Engineering Department, Faculty of Navigation Science and Space Technology, BeniSuef University, BeniSuef, EgyptElectronics and Communications Department, School of Engineering, Canadian Higher Engineering Institute, Canadian International College, 6th October, Giza, EgyptElectronics and Communications Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, EgyptElectronics and Communications Department, School of Engineering, Canadian Higher Engineering Institute, Canadian International College, 6th October, Giza, EgyptInternet of Things (IoT) technology drives lifestyle changes in smart city infrastructure due to rapid growth of services and activities that develop well-being. One of the main challenges that resulted from the exponential spread of IoT is the dense number of nodes with the huge amount of data over different networks that influence the collision probability, and network congestion. Existing aggregation techniques worked to solve these challenges with overlooking the IoT traffic characteristics and their types. In this paper, adaptive aggregation techniques are proposed based on IoT traffic types to overcome IoT network issues. These techniques can abstract data, reduce number of packets sent with low traffic congestion, and reduce the recurring packet headers. The proposed adaptive aggregation techniques are accomplished over the IoT smart city networks that are architectured and practically tested to examine the simulation results. It is anticipated that the adaptive aggregation results could optimize the operational efficiency of IoT smart city networks in most key performance metrics, compared to the existing aggregation techniques.http://www.sciencedirect.com/science/article/pii/S1110016822002113IoTAdaptive aggregationIoT Traffic characteristicsSmart cityTraffic aggregationPerformance evaluation |
| spellingShingle | Amin S. Ibrahim Khaled Y. Youssef Ahmed H. Eldeeb Mohamed Abouelatta Hesham Kamel Adaptive aggregation based IoT traffic patterns for optimizing smart city network performance Alexandria Engineering Journal IoT Adaptive aggregation IoT Traffic characteristics Smart city Traffic aggregation Performance evaluation |
| title | Adaptive aggregation based IoT traffic patterns for optimizing smart city network performance |
| title_full | Adaptive aggregation based IoT traffic patterns for optimizing smart city network performance |
| title_fullStr | Adaptive aggregation based IoT traffic patterns for optimizing smart city network performance |
| title_full_unstemmed | Adaptive aggregation based IoT traffic patterns for optimizing smart city network performance |
| title_short | Adaptive aggregation based IoT traffic patterns for optimizing smart city network performance |
| title_sort | adaptive aggregation based iot traffic patterns for optimizing smart city network performance |
| topic | IoT Adaptive aggregation IoT Traffic characteristics Smart city Traffic aggregation Performance evaluation |
| url | http://www.sciencedirect.com/science/article/pii/S1110016822002113 |
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