Partial Offloading in Energy Harvested Mobile Edge Computing: A Direct Search Approach

In the next generation wireless communication paradigm, the number of devices are expected to increase exponentially after the concept of Internet of Things (IoT). These devices are power constrained, with limited processing capability. Therefore, in order to get the maximum advantage from these low...

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Main Authors: Asad Mahmood, Ashfaq Ahmed, Muhammad Naeem, Yue Hong
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9001132/
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author Asad Mahmood
Ashfaq Ahmed
Muhammad Naeem
Yue Hong
author_facet Asad Mahmood
Ashfaq Ahmed
Muhammad Naeem
Yue Hong
author_sort Asad Mahmood
collection DOAJ
description In the next generation wireless communication paradigm, the number of devices are expected to increase exponentially after the concept of Internet of Things (IoT). These devices are power constrained, with limited processing capability. Therefore, in order to get the maximum advantage from these low power IoT sensing devices, it is of utmost need to empower them. Similarly, the devices are not able to process the computationally intensive applications. In this work, Wireless Power Mobile Edge Cloud (WPMEC) is considered, which is an integration of Wireless Power Transfer (WPT) and Mobile Edge Cloud (MEC) to address low power devices' battery and computational capabilities. The WPMEC is charging the devices in the first phase using the WPT and in the second phase, the devices are offloading their computational intensive data to the MEC. Partial offloading scheme is first time introduced and analyzed with WPMEC. Performance of proposed solution is evaluated in terms of overall network computational energy efficiency. Extensive simulations have been carried out to validate the proposed solution. It is shown that the proposed partial offloading scheme with WPMEC outperforms the binary and local computational schemes.
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spelling doaj.art-084fe6a7e5f542f2a6a4c19954c201862022-12-21T22:40:05ZengIEEEIEEE Access2169-35362020-01-018367573676310.1109/ACCESS.2020.29748099001132Partial Offloading in Energy Harvested Mobile Edge Computing: A Direct Search ApproachAsad Mahmood0https://orcid.org/0000-0001-8978-3336Ashfaq Ahmed1https://orcid.org/0000-0002-6194-7551Muhammad Naeem2https://orcid.org/0000-0001-9734-4608Yue Hong3https://orcid.org/0000-0003-1022-0480College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, ChinaDepartment of Electrical and Computer Engineering, COMSATS University Islamabad at Wah Campus, Wah Cantt, PakistanDepartment of Electrical and Computer Engineering, COMSATS University Islamabad at Wah Campus, Wah Cantt, PakistanCollege of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, ChinaIn the next generation wireless communication paradigm, the number of devices are expected to increase exponentially after the concept of Internet of Things (IoT). These devices are power constrained, with limited processing capability. Therefore, in order to get the maximum advantage from these low power IoT sensing devices, it is of utmost need to empower them. Similarly, the devices are not able to process the computationally intensive applications. In this work, Wireless Power Mobile Edge Cloud (WPMEC) is considered, which is an integration of Wireless Power Transfer (WPT) and Mobile Edge Cloud (MEC) to address low power devices' battery and computational capabilities. The WPMEC is charging the devices in the first phase using the WPT and in the second phase, the devices are offloading their computational intensive data to the MEC. Partial offloading scheme is first time introduced and analyzed with WPMEC. Performance of proposed solution is evaluated in terms of overall network computational energy efficiency. Extensive simulations have been carried out to validate the proposed solution. It is shown that the proposed partial offloading scheme with WPMEC outperforms the binary and local computational schemes.https://ieeexplore.ieee.org/document/9001132/Wireless Power TransferMobile Edge Cloud ComputingEergy Efficiency
spellingShingle Asad Mahmood
Ashfaq Ahmed
Muhammad Naeem
Yue Hong
Partial Offloading in Energy Harvested Mobile Edge Computing: A Direct Search Approach
IEEE Access
Wireless Power Transfer
Mobile Edge Cloud Computing
Eergy Efficiency
title Partial Offloading in Energy Harvested Mobile Edge Computing: A Direct Search Approach
title_full Partial Offloading in Energy Harvested Mobile Edge Computing: A Direct Search Approach
title_fullStr Partial Offloading in Energy Harvested Mobile Edge Computing: A Direct Search Approach
title_full_unstemmed Partial Offloading in Energy Harvested Mobile Edge Computing: A Direct Search Approach
title_short Partial Offloading in Energy Harvested Mobile Edge Computing: A Direct Search Approach
title_sort partial offloading in energy harvested mobile edge computing a direct search approach
topic Wireless Power Transfer
Mobile Edge Cloud Computing
Eergy Efficiency
url https://ieeexplore.ieee.org/document/9001132/
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AT yuehong partialoffloadinginenergyharvestedmobileedgecomputingadirectsearchapproach