Mobile edge Computing Architecture Basaed Task Overflooding And Energy Reduction Using Quality of Service For AR Applications
Download| Volume 4 Issue 1 2023 | |
|---|---|
| Author(s): |
Ali Raza engr.abbasi17@gmail.com Sana kanwal sanakanwal96@gmail.com Zkanwal Khanzada kanwalraiskz@gmail.com |
| Abstract | The advent of 5G technology, driven by the proliferation of mobile devices, has led to a surge in mobile traffic and the emergence of various services like Mobile portals, Mobile commerce, Mobile health care, Mobile government, Mobile banking, and more. These services are made possible through the utilization of Cloud Computing Resources (CCR). In order to overcome resource constraints, mobile devices rely on connecting to cloud servers to offload computational tasks and optimize resource utilization. This involves leveraging multiple edge servers and considering factors such as remaining battery life. The concept of Mobile Edge computing (MEG) has introduced mathematical models to address this challenge. To tackle this issue, a proposed solution called Mobile Edge Computing Architecture focuses on task offloading and energy reductions. By enabling direct traffic between end users, this solution ensures high-quality service for applications like Augmented Reality (AR) The primary objective of the Mobile Edge Computing (MEC) solution is to efficiently distribute tasks among Mobile Edge devices while minimizing energy consumption and latency. Our research has shown that a task offloading scheme can significantly improve overall computation efficiency in the context of international 5G networks. Furthermore, we have proposed the use of the Reinforcement algorithm, leveraging techniques such as Machine Learning and FLIPS technology. These advancements aim to enhance the latency experienced in MEC offerings, attached to it. The RMTC faces the challenge of accommodating the increasing diversity of radio access technologies. The growing demand for Mobile edge computing (MEC) can be attributed to several factors. |
| Keywords | Mobile edge computing (MEC), Augmented Reality (AR), Reinforcement Algorithm |
| Year | 2023 |
| Volume | 4 |
| Issue | 1 |
| Type | Research paper, manuscript, article |
| Recognized by | Higher Education Commission of Pakistan, HEC | Category | Journal Name | ILMA Journal of Technology & Software Management | Publisher Name | ILMA University | Jel Classification | -- | DOI | - | ISSN no (E, Electronic) | 2790-590X | ISSN no (P, Print) | 2709-2240 | Country | Pakistan | City | Karachi | Institution Type | University | Journal Type | Open Access | Manuscript Processing | Blind Peer Reviewed | Format | Paper Link | https://ijtsm.ilmauniversity.edu.pk/arc/Vol4/i1/3.pdf | Page |