Mobilouds: An energy efficient MCC collaborative framework with extended mobile participation for next generation networks
Journal article
Panneerselvam, J., Hardy, J., Liu, Lu, Yuan, Bo and Antonopoulos, Nikolaos 2017. Mobilouds: An energy efficient MCC collaborative framework with extended mobile participation for next generation networks. IEEE Access. https://doi.org/10.1109/ACCESS.2016.2602321
| Authors | Panneerselvam, J., Hardy, J., Liu, Lu, Yuan, Bo and Antonopoulos, Nikolaos |
|---|---|
| Abstract | Given the emergence of mobile cloud computing (MCC), its associated energy implications are witnessed at larger scale. With offloading computationally intensive tasks to the cloud datacentres being the basic concept behind MCC, most of the mobile terminal resources participating in the MCC collaborative execution are wasted as they remain idle until the mobile terminals receive responses from the datacentres. This is an additional wastage of resources alongside the cloud resources are already being addressed as massive energy consumers. Though the energy consumed of the idle mobile resources is insignificant in comparison with the cloud counterpart, such consumptions have drastic impacts on the mobile devices causing unnecessary battery drains. To this end, this paper proposes Mobilouds which encompass a multi-tier processing architecture with various levels of process cluster capacities and a software application to manage energy efficient utilization of such process clusters. Our proposed Mobilouds framework encourages the mobile device participation in the MCC collaborative execution, thereby reduces the presence of idle mobile resources and utilizes such idle resources in the actual task execution. Our performance evaluation results demonstrate that the Mobilouds framework offers the most energy-time balancing process clusters for task execution by effectively utilizing the available resources, in comparison with an entire cloud offloading strategy using 5G/4G networks. |
| Keywords | Mobile computing; Cloud computing |
| Year | 2017 |
| Journal | IEEE Access |
| Publisher | IEEE |
| ISSN | 21693536 |
| Digital Object Identifier (DOI) | https://doi.org/10.1109/ACCESS.2016.2602321 |
| Web address (URL) | http://hdl.handle.net/10545/621594 |
| hdl:10545/621594 | |
| Publication dates | 23 Jan 2017 |
| Publication process dates | |
| Deposited | 10 May 2017, 12:08 |
| Rights | Archived with thanks to IEEE Access |
| Contributors | University of Derby |
| File | File Access Level Open |
| File | File Access Level Open |
| File | File Access Level Open |
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