Mutlag, Ammar Awad (2023) Multi-agent fog computing resource management model for critical healthcare applications. Doctoral thesis, Universiti Teknikal Malaysia Melaka.
![[img]](http://eprints.utem.edu.my/style/images/fileicons/text.png) |
Text (24 Pages)
Multi-agent fog computing resource management model for critical healthcare applications.pdf - Submitted Version Download (433kB) |
|
Text (Full Text)
Multi-agent fog computing resource management model for critical healthcare applications.pdf - Submitted Version Restricted to Registered users only Download (2MB) |
Abstract
Fog computing is a fairly new distributed computing technique which expands the capabilities of cloud computing to the edge of the network. Fog servers operate as an intermediary between cloud data centres and end-user devices. One of the aims of fog computing is to increase performance and reduce the amount of data being transferred to the cloud for processing, analyzing and storing. This approach allows the execution of a portion of a transaction at a fog server. However, cloud computing still suffers from resource management in healthcare application tasks. Critical healthcare application tasks require a quick response because it affects patients’ life. Fog computing is the best solution to get a fast response and less energy consumption. To significantly implement Fog computing, it’s paramount to manage the resources of Fog computing and develop interoperability among Fog and Cloud. Any modelling effort of Fog computing resource management, especially in healthcare applications, depends on scheduling the tasks which in turn involves three main factors; Load Balancing, Resource Availability, and Prioritization. Hence, the main contribution of this thesis is to develop a model of resource management that employ the aforementioned factors. From the literature, it is clear that the contribution of Multi-agent systems in scheduling is huge. In this thesis, the role of Multi-agent systems is to optimise critical healthcare tasks scheduling efficiently. The results have shown that the Multi-Agent Fog computing model (MAFCRMM) is very efficient in providing the fastest response for critical healthcare application tasks in terms of the number of energy consumption, instance cost, delay, and response time.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | Cloud computing, Cloud computing, Internet of things |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics |
| Divisions: | Library > Tesis > FTMK |
| Depositing User: | Unnamed user with email nuraina0324@gmail.com |
| Date Deposited: | 19 Sep 2024 16:40 |
| Last Modified: | 19 Sep 2024 16:40 |
| URI: | http://eprints.utem.edu.my/id/eprint/27721 |
| Statistic Details: | View Download Statistic |
Actions (login required)
 |
View Item |