Fuzzy-Based Multi-Modal Query-Forwarding in Mini-Datacenters
The rapid growth of Internet of Things (IoT) enabled devices in industrial environments and the associated increase in data generation are paving the way for the development of localized, distributed datacenters. In this paper, we have proposed a novel mini-datacenter in the form of wireless sensor...
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MDPI AG
2025-07-01
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| Series: | Computers |
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| Online Access: | https://www.mdpi.com/2073-431X/14/7/261 |
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| author | Sami J. Habib Paulvanna Nayaki Marimuthu |
| author_facet | Sami J. Habib Paulvanna Nayaki Marimuthu |
| author_sort | Sami J. Habib |
| collection | DOAJ |
| description | The rapid growth of Internet of Things (IoT) enabled devices in industrial environments and the associated increase in data generation are paving the way for the development of localized, distributed datacenters. In this paper, we have proposed a novel mini-datacenter in the form of wireless sensor networks to efficiently handle query-based data collection from Industrial IoT (IIoT) devices. The mini-datacenter comprises a command center, gateways, and IoT sensors, designed to manage stochastic query-response traffic flow. We have developed a duplication/aggregation query flow model, tailored to emphasize reliable transmission. We have developed a dataflow management framework that employs a multi-modal query forwarding approach to forward queries from the command center to gateways under varying environments. The query forwarding includes coarse-grain and fine-grain strategies, where the coarse-grain strategy uses a direct data flow using a single gateway at the expense of reliability, while the fine-grain approach uses redundant gateways to enhance reliability. A fuzzy-logic-based intelligence system is integrated into the framework to dynamically select the appropriate granularity of the forwarding strategy based on the resource availability and network conditions, aided by a buffer watching algorithm that tracks real-time buffer status. We carried out several experiments with gateway nodes varying from 10 to 100 to evaluate the framework’s scalability and robustness in handling the query flow under complex environments. The experimental results demonstrate that the framework provides a flexible and adaptive solution that balances buffer usage while maintaining over 95% reliability in most queries. |
| format | Article |
| id | doaj-art-94b0649fcc2647efbe810cc4e4a1ccff |
| institution | DOAJ |
| issn | 2073-431X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computers |
| spelling | doaj-art-94b0649fcc2647efbe810cc4e4a1ccff2025-08-20T02:45:54ZengMDPI AGComputers2073-431X2025-07-0114726110.3390/computers14070261Fuzzy-Based Multi-Modal Query-Forwarding in Mini-DatacentersSami J. Habib0Paulvanna Nayaki Marimuthu1Department of Computer Engineering, College of Engineering and Petroleum, Kuwait University, Safat 13060, KuwaitDepartment of Computer Engineering, College of Engineering and Petroleum, Kuwait University, Safat 13060, KuwaitThe rapid growth of Internet of Things (IoT) enabled devices in industrial environments and the associated increase in data generation are paving the way for the development of localized, distributed datacenters. In this paper, we have proposed a novel mini-datacenter in the form of wireless sensor networks to efficiently handle query-based data collection from Industrial IoT (IIoT) devices. The mini-datacenter comprises a command center, gateways, and IoT sensors, designed to manage stochastic query-response traffic flow. We have developed a duplication/aggregation query flow model, tailored to emphasize reliable transmission. We have developed a dataflow management framework that employs a multi-modal query forwarding approach to forward queries from the command center to gateways under varying environments. The query forwarding includes coarse-grain and fine-grain strategies, where the coarse-grain strategy uses a direct data flow using a single gateway at the expense of reliability, while the fine-grain approach uses redundant gateways to enhance reliability. A fuzzy-logic-based intelligence system is integrated into the framework to dynamically select the appropriate granularity of the forwarding strategy based on the resource availability and network conditions, aided by a buffer watching algorithm that tracks real-time buffer status. We carried out several experiments with gateway nodes varying from 10 to 100 to evaluate the framework’s scalability and robustness in handling the query flow under complex environments. The experimental results demonstrate that the framework provides a flexible and adaptive solution that balances buffer usage while maintaining over 95% reliability in most queries.https://www.mdpi.com/2073-431X/14/7/261Internet of Thingsmini-datacenterfuzzy logicdistributed computingedge-computingreliability |
| spellingShingle | Sami J. Habib Paulvanna Nayaki Marimuthu Fuzzy-Based Multi-Modal Query-Forwarding in Mini-Datacenters Computers Internet of Things mini-datacenter fuzzy logic distributed computing edge-computing reliability |
| title | Fuzzy-Based Multi-Modal Query-Forwarding in Mini-Datacenters |
| title_full | Fuzzy-Based Multi-Modal Query-Forwarding in Mini-Datacenters |
| title_fullStr | Fuzzy-Based Multi-Modal Query-Forwarding in Mini-Datacenters |
| title_full_unstemmed | Fuzzy-Based Multi-Modal Query-Forwarding in Mini-Datacenters |
| title_short | Fuzzy-Based Multi-Modal Query-Forwarding in Mini-Datacenters |
| title_sort | fuzzy based multi modal query forwarding in mini datacenters |
| topic | Internet of Things mini-datacenter fuzzy logic distributed computing edge-computing reliability |
| url | https://www.mdpi.com/2073-431X/14/7/261 |
| work_keys_str_mv | AT samijhabib fuzzybasedmultimodalqueryforwardinginminidatacenters AT paulvannanayakimarimuthu fuzzybasedmultimodalqueryforwardinginminidatacenters |