DC Field | Value | Language |
dc.contributor.author | LAREDJ, IMad EDdine | - |
dc.date.accessioned | 2024-10-13T10:07:52Z | - |
dc.date.available | 2024-10-13T10:07:52Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | https://repository.esi-sba.dz/jspui/handle/123456789/745 | - |
dc.description | Supervisor : Mr. Jean-François Dollinger / Mr. Simon Caillard / Mr. Abdelkader Amrane | en_US |
dc.description.abstract | The rapid proliferation of mobile devices, exceeding 7.1 billion users globally in 2024, has
completely transformed the way communicate, work, interact with technology on a daily
basis. This surge has introduced new challenges in computational capabilities and user experiences,
prompting a shift towards distributed computing paradigms such as cloud-edge
computing. Cloud computing has provided extensive computational resources to mobile devices,
with edge computing further enhancing performance by localising computation and
storage, which in return reduces latency. In response to the increasing complexity of mobile
applications, task offloading has emerged as a vital optimization strategy, allowing resourceconstrained
devices to delegate tasks to more powerful cloud or edge resources, promoting
faster, energy-aware execution. This paper analyzes some of the existing task offloading methods,
particularly in the context of edge-cloud computing, through a comprehensive study of
current methodologies, benefits and limitations. | en_US |
dc.language.iso | en | en_US |
dc.subject | Task Offloading | en_US |
dc.subject | High Performance Computing | en_US |
dc.subject | Task Placement | en_US |
dc.subject | Cloud Computing | en_US |
dc.subject | Edge Computing | en_US |
dc.subject | Distributed Computing | en_US |
dc.title | A Review of Task Offloading Techniques for Edge-Cloud Computing | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Ingénieur
|