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Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing

With the increasing number of mobile devices and IoT devices across a wide range of real-life applications, our mobile cloud computing devices will not cope with this growing number of audiences soon, which implies and demands the need to shift to fog computing. Task scheduling is one of the most de...

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Autores principales: Ali, Abid, Iqbal, Muhammad Munawar, Jamil, Harun, Akbar, Habib, Muthanna, Ammar, Ammi, Meryem, Althobaiti, Maha M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747413/
https://www.ncbi.nlm.nih.gov/pubmed/35009649
http://dx.doi.org/10.3390/s22010108
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author Ali, Abid
Iqbal, Muhammad Munawar
Jamil, Harun
Akbar, Habib
Muthanna, Ammar
Ammi, Meryem
Althobaiti, Maha M.
author_facet Ali, Abid
Iqbal, Muhammad Munawar
Jamil, Harun
Akbar, Habib
Muthanna, Ammar
Ammi, Meryem
Althobaiti, Maha M.
author_sort Ali, Abid
collection PubMed
description With the increasing number of mobile devices and IoT devices across a wide range of real-life applications, our mobile cloud computing devices will not cope with this growing number of audiences soon, which implies and demands the need to shift to fog computing. Task scheduling is one of the most demanding scopes after the trust computation inside the trustable nodes. The mobile devices and IoT devices transfer the resource-intensive tasks towards mobile cloud computing. Some tasks are resource-intensive and not trustable to allocate to the mobile cloud computing resources. This consequently gives rise to trust evaluation and data sync-up of devices joining and leaving the network. The resources are more intensive for cloud computing and mobile cloud computing. Time, energy, and resources are wasted due to the nontrustable nodes. This research article proposes a multilevel trust enhancement approach for efficient task scheduling in mobile cloud environments. We first calculate the trustable tasks needed to offload towards the mobile cloud computing. Then, an efficient and dynamic scheduler is added to enhance the task scheduling after trust computation using social and environmental trust computation techniques. To improve the time and energy efficiency of IoT and mobile devices using the proposed technique, the energy computation and time request computation are compared with the existing methods from literature, which identified improvements in the results. Our proposed approach is centralized to tackle constant SyncUPs of incoming devices’ trust values with mobile cloud computing. With the benefits of mobile cloud computing, the centralized data distribution method is a positive approach.
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spelling pubmed-87474132022-01-11 Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing Ali, Abid Iqbal, Muhammad Munawar Jamil, Harun Akbar, Habib Muthanna, Ammar Ammi, Meryem Althobaiti, Maha M. Sensors (Basel) Article With the increasing number of mobile devices and IoT devices across a wide range of real-life applications, our mobile cloud computing devices will not cope with this growing number of audiences soon, which implies and demands the need to shift to fog computing. Task scheduling is one of the most demanding scopes after the trust computation inside the trustable nodes. The mobile devices and IoT devices transfer the resource-intensive tasks towards mobile cloud computing. Some tasks are resource-intensive and not trustable to allocate to the mobile cloud computing resources. This consequently gives rise to trust evaluation and data sync-up of devices joining and leaving the network. The resources are more intensive for cloud computing and mobile cloud computing. Time, energy, and resources are wasted due to the nontrustable nodes. This research article proposes a multilevel trust enhancement approach for efficient task scheduling in mobile cloud environments. We first calculate the trustable tasks needed to offload towards the mobile cloud computing. Then, an efficient and dynamic scheduler is added to enhance the task scheduling after trust computation using social and environmental trust computation techniques. To improve the time and energy efficiency of IoT and mobile devices using the proposed technique, the energy computation and time request computation are compared with the existing methods from literature, which identified improvements in the results. Our proposed approach is centralized to tackle constant SyncUPs of incoming devices’ trust values with mobile cloud computing. With the benefits of mobile cloud computing, the centralized data distribution method is a positive approach. MDPI 2021-12-24 /pmc/articles/PMC8747413/ /pubmed/35009649 http://dx.doi.org/10.3390/s22010108 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ali, Abid
Iqbal, Muhammad Munawar
Jamil, Harun
Akbar, Habib
Muthanna, Ammar
Ammi, Meryem
Althobaiti, Maha M.
Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing
title Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing
title_full Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing
title_fullStr Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing
title_full_unstemmed Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing
title_short Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing
title_sort multilevel central trust management approach for task scheduling on iot-based mobile cloud computing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747413/
https://www.ncbi.nlm.nih.gov/pubmed/35009649
http://dx.doi.org/10.3390/s22010108
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