CFRO: Cloudlet Federation for Resource Optimization
A Cloud computing paradigm augments the limited resources of mobile devices resulting in increased distance, limited Internet bandwidth, and seamless connectivity challenges between a remote cloud and mobile devices. Cloudlet computing based solutions are widely used to address these challenges by b...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9108247/ |
| _version_ | 1818857112644616192 |
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| author | Muhammad Ziad Nayyer Imran Raza Syed Asad Hussain |
| author_facet | Muhammad Ziad Nayyer Imran Raza Syed Asad Hussain |
| author_sort | Muhammad Ziad Nayyer |
| collection | DOAJ |
| description | A Cloud computing paradigm augments the limited resources of mobile devices resulting in increased distance, limited Internet bandwidth, and seamless connectivity challenges between a remote cloud and mobile devices. Cloudlet computing based solutions are widely used to address these challenges by bringing the computational facility closer to the user. The ever growing number of mobile devices, Internet of Things (IoT) sensors and Information Communication Technology (ICT) infrastructure used for smart cities demand more resources. The existing cloudlet based solutions are unable to manage the ever-increasing demand for power, storage, and computational resources, and therefore forward the resource extensive tasks to a remote cloud, limiting cloudlet computing benefits. We present the Cloudlet Federation for Resource Optimization (CFRO), a federated cloudlet model for resource optimization to address these resource scarcity challenges. The proposed model exerts the features of scalability, resource collaboration, and robustness. The underlying scheme for resource optimization has been modeled as a Nested Multi Objective Resource Optimization Problem (NMOROP) and a novel algorithm has been proposed to solve it. The detailed analysis and comparative results show that the proposed model offers improved performance and more resource elasticity as compared to the conventional cloudlet model. |
| first_indexed | 2024-12-19T08:35:13Z |
| format | Article |
| id | doaj.art-3de695614cb240ffbbcda4f8bb8512d9 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T08:35:13Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-3de695614cb240ffbbcda4f8bb8512d92022-12-21T20:29:03ZengIEEEIEEE Access2169-35362020-01-01810623410624610.1109/ACCESS.2020.29999389108247CFRO: Cloudlet Federation for Resource OptimizationMuhammad Ziad Nayyer0https://orcid.org/0000-0001-6014-4397Imran Raza1https://orcid.org/0000-0003-3118-4634Syed Asad Hussain2Department of Computer Science, GIFT University, Gujranwala, PakistanDepartment of Computer Science, COMSATS University Islamabad, Lahore Campus, Lahore, PakistanDepartment of Computer Science, COMSATS University Islamabad, Lahore Campus, Lahore, PakistanA Cloud computing paradigm augments the limited resources of mobile devices resulting in increased distance, limited Internet bandwidth, and seamless connectivity challenges between a remote cloud and mobile devices. Cloudlet computing based solutions are widely used to address these challenges by bringing the computational facility closer to the user. The ever growing number of mobile devices, Internet of Things (IoT) sensors and Information Communication Technology (ICT) infrastructure used for smart cities demand more resources. The existing cloudlet based solutions are unable to manage the ever-increasing demand for power, storage, and computational resources, and therefore forward the resource extensive tasks to a remote cloud, limiting cloudlet computing benefits. We present the Cloudlet Federation for Resource Optimization (CFRO), a federated cloudlet model for resource optimization to address these resource scarcity challenges. The proposed model exerts the features of scalability, resource collaboration, and robustness. The underlying scheme for resource optimization has been modeled as a Nested Multi Objective Resource Optimization Problem (NMOROP) and a novel algorithm has been proposed to solve it. The detailed analysis and comparative results show that the proposed model offers improved performance and more resource elasticity as compared to the conventional cloudlet model.https://ieeexplore.ieee.org/document/9108247/Cloud federation (CF)cloudlet computing (CC)fog computing (FC)internet of Things (IoT)mobile cloud computing (MCC)mobile edge computing (MEC) |
| spellingShingle | Muhammad Ziad Nayyer Imran Raza Syed Asad Hussain CFRO: Cloudlet Federation for Resource Optimization IEEE Access Cloud federation (CF) cloudlet computing (CC) fog computing (FC) internet of Things (IoT) mobile cloud computing (MCC) mobile edge computing (MEC) |
| title | CFRO: Cloudlet Federation for Resource Optimization |
| title_full | CFRO: Cloudlet Federation for Resource Optimization |
| title_fullStr | CFRO: Cloudlet Federation for Resource Optimization |
| title_full_unstemmed | CFRO: Cloudlet Federation for Resource Optimization |
| title_short | CFRO: Cloudlet Federation for Resource Optimization |
| title_sort | cfro cloudlet federation for resource optimization |
| topic | Cloud federation (CF) cloudlet computing (CC) fog computing (FC) internet of Things (IoT) mobile cloud computing (MCC) mobile edge computing (MEC) |
| url | https://ieeexplore.ieee.org/document/9108247/ |
| work_keys_str_mv | AT muhammadziadnayyer cfrocloudletfederationforresourceoptimization AT imranraza cfrocloudletfederationforresourceoptimization AT syedasadhussain cfrocloudletfederationforresourceoptimization |