This project aims to develop a distributed computing system that processes large datasets in parallel across multiple cloud nodes to improve computation speed and system scalability.
Study distributed computing models and parallel processing Set up multiple cloud compute instances Implement task distribution mechanism Develop data partitioning logic Configure message queues for communication Implement fault tolerance handling Benchmark performance against single-node execution Monitor CPU and memory utilization Optimize task scheduling algorithms Document distributed architecture and performance metrics
