Yousafzai, Abdullah and Yaqoob, Ibrar and Imran, Muhammad and Gani, Abdullah and Noor, Rafidah Md (2020) Process Migration-Based Computational Offloading Framework for IoT-Supported Mobile Edge/Cloud Computing. IEEE Internet of Things Journal, 7 (5). pp. 4171-4182. ISSN 2372-2541, DOI https://doi.org/10.1109/JIOT.2019.2943176.
Full text not available from this repository.Abstract
Mobile devices have become an indispensable component of Internet of Things (IoT). However, these devices have resource constraints in processing capabilities, battery power, and storage space, thus hindering the execution of computation-intensive applications that often require broad bandwidth, stringent response time, long-battery life, and heavy-computing power. Mobile cloud computing and mobile edge computing (MEC) are emerging technologies that can meet the aforementioned requirements using offloading algorithms. In this article, we analyze the effect of platform-dependent native applications on computational offloading in edge networks and propose a lightweight process migration-based computational offloading framework. The proposed framework does not require application binaries at edge servers and thus seamlessly migrates native applications. The proposed framework is evaluated using an experimental testbed. Numerical results reveal that the proposed framework saves almost 44% of the execution time and 84% of the energy consumption. Hence, the proposed framework shows profound potential for resource-intensive IoT application processing in MEC. © 2014 IEEE.
| Item Type: | Article |
|---|---|
| Funders: | Bright Spark Program from the University of Malaya under Grant BSP/APP/1635/2013, Deanship of Scientific Research, King Saud University through Research Group under Project RG-1435-051 |
| Uncontrolled Keywords: | Computational offloading; Internet of Things (IoT); mobile cloud; mobile edge computing (MEC); process migration; smart cities |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 04 Jun 2020 02:15 |
| Last Modified: | 04 Jun 2020 02:15 |
| URI: | http://eprints.um.edu.my/id/eprint/24645 |
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