Role

Sole contributor: implemented the entire project including paper comprehension and algorithm realization

Course

EECE 7205 – Fundamentals of Computer Engineering

Objective

This project is based on the following paper: Lin, X., Wang, Y., Xie, Q., & Pedram, M. (2014, June). Energy and performance-aware task scheduling in a mobile cloud computing environment. In 2014 IEEE 7th International Conference on Cloud Computing (pp. 192–199). IEEE. The objective was to comprehend the proposed scheduling approach, replicate its method, and implement an energy-efficient scheduling algorithm based on task graphs and computation models. The project aimed to balance energy consumption and task latency under a mobile cloud computing architecture.

Technologies

Process scheduling & task graph modeling, Algorithm design & scheduler implementation, Python for graph algorithms and simulation

My Contributions

• Studied the paper and understood the theoretical background and model assumptions
• Built a framework for representing task dependencies via graphs
• Implemented energy-aware scheduling strategies balancing performance and power
• Developed a simulator to evaluate task execution under varying conditions
• Analyzed and visualized the impact of scheduling strategies on energy and latency

Results

• Successfully replicated the scheduling concepts from the paper in a working simulation
• Energy-aware approach showed significantly lower power usage under multi-task scenarios
• Visualized comparisons between strategies confirmed energy-latency trade-offs similar to the original paper

GitHub Repository

View GitHub Repository