Samanta, A., Ha, T.T., Nguyen, T.G. and Mumtaz, S. ORCID: 0000-0001-6364-6149, 2022. Distributed resource distribution and offloading for resource-agnostic microservices in industrial IoT. IEEE Transactions on Vehicular Technology. ISSN 0018-9545
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Abstract
Due to increase in real-time mobile applications and Industrial Internet-of-Things (IIoT) devices, the edge computing paradigm provides a systematic and eccentric platform for real-time Internet-of-Things applications. Though the paradigm provides an effective infrastructure, however the resource requirements of IIoT devices change radically with time, which is described as a resource-agnostic property. Therefore, the estimation of resource requirements of IIoT devices is a critical and resilient assignment. In addition, it requires an extensive amount of resources to process the data traffic flows and microservice offloading. Hence, we present RAISE, a novel resource-agnostic microservice offloading scheme for mobile IIoT devices. RAISE efficiently estimates the resource-agnostic nature of IIoT devices to maximize their resource utilization in the network. Based on the estimated resource requirement, we propose a resource-agnostic microservice offloading scheme to maximize the success rate. Extensive experiments show that RAISE provides better performance in terms of network throughput and Quality-of-Service (QoS) than the other existing methods, SDTO and DTOS, in terms of cost and reliability.
Item Type: | Journal article | ||||||
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Publication Title: | IEEE Transactions on Vehicular Technology | ||||||
Creators: | Samanta, A., Ha, T.T., Nguyen, T.G. and Mumtaz, S. | ||||||
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) | ||||||
Date: | 2022 | ||||||
ISSN: | 0018-9545 | ||||||
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Rights: | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
Divisions: | Schools > School of Science and Technology | ||||||
Record created by: | Laura Ward | ||||||
Date Added: | 09 Dec 2022 09:23 | ||||||
Last Modified: | 09 Dec 2022 09:23 | ||||||
URI: | https://irep.ntu.ac.uk/id/eprint/47605 |
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