Secure workflow scheduling algorithm utilizing hybrid optimization in mobile edge computing environments

The rapid advancement of mobile communication technology and devices has greatly improved our way of life. It also presents a new possibility that data sources can be used to accomplish computing tasks at nearby locations. Mobile Edge Computing (MEC) is a computing model that provides computer resou...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computer communications Jg. 226-227; S. 107929
Hauptverfasser: Sajnani, Dileep Kumar, Li, Xiaoping, Mahesar, Abdul Rasheed
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.10.2024
Schlagworte:
Feedback artificial tree
Mobile edge computing
Remora optimization algorithm
Security
Workflow scheduling
Remora optimization algorithm
Security
Workflow scheduling
Feedback artificial tree
Mobile edge computing
ISSN:0140-3664
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The rapid advancement of mobile communication technology and devices has greatly improved our way of life. It also presents a new possibility that data sources can be used to accomplish computing tasks at nearby locations. Mobile Edge Computing (MEC) is a computing model that provides computer resources specifically designed to handle mobile tasks. Nevertheless, there are certain obstacles that must be carefully tackled, specifically regarding the security and quality of services in the workflow scheduling over MEC. This research proposes a new method called Feedback Artificial Remora Optimization (FARO)-based workflow scheduling method to address the issues of scheduling processes with improved security in MEC. In this context, the fitness functions that are taken into account include multi-objective, such as CPU utilization, memory utilization, encryption cost, and execution time. These functions are used to enhance the scheduling of workflow tasks based on security considerations. The FARO algorithm is a combination of the Feedback Artificial Tree (FAT) and the Remora Optimization Algorithm (ROA). The experimental findings have demonstrated that the developed approach surpassed current methods by a large margin in terms of CPU use, memory consumption, encryption cost, and execution time, with values of 0.012, 0.010, 0.017, and 0.036, respectively.
ISSN:0140-3664
DOI:10.1016/j.comcom.2024.107929