An efficient framework for scheduling security-critical tasks in resource-limited mobile edge computing using...

Area of Science:

• Computer Science
• Network Engineering

Background:

• Mobile Edge Computing (MEC) decentralizes network functions, processing mobile application resources at cell base stations.
• Optimization challenges in MEC impact user experience and Quality of Service (QoS).
• Offloading workloads to MEC servers offers low-latency and high-throughput computing.

Purpose of the Study:

• To develop a security-critical task scheduling method for resource-limited MEC environments.
• To enhance offloading performance, energy efficiency, and reduce latency.
• To secure critical tasks, improving user experience and QoS.

Main Methods:

• Implementing a security-critical task scheduling approach in MEC.
• Utilizing the developed HGR-GJOS algorithm for task scheduling.
• Optimizing task assignment to minimize workflow execution time and energy consumption.

Main Results:

• Improved offloading performance and energy efficiency in resource-limited MEC.
• Reduced latency issues for security-critical tasks.
• Enhanced user experience and Quality of Service (QoS).

Conclusions:

• The proposed scheduling method effectively manages security-critical tasks in MEC.
• The HGR-GJOS algorithm optimizes resource allocation, minimizing execution time and energy use.
• This research contributes to better performance and security in MEC systems.