Cloud-Based Distributed Data Processing System Using Parallel Execution Framework
PinsoutCloud ComputingProject Objectives:
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.
Project Tasks:
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
Educational Qualifications
B.TechB.EBCAMCA
Required Skills
Distributed Computing & Parallel Processing (Mapreduce, Spark, Hadoop Concepts)Cloud Infrastructure Management (Aws Ec2, Azure Vm, Gcp Compute Engine)Data Partitioning & Task Scheduling AlgorithmsMessage Queues & Inter-Process Communication (Kafka, Rabbitmq, Etc.)Performance Monitoring & Optimization (Cpu, Memory, Scalability Benchmarking)
