Resource management activities like resource scheduling and allocation for jobs are crucial for efficient and effective workload management in distributed computing systems. The current proliferating of Cloud-based Internet of Things(IoT) systems are collecting a large amount of data called big data. Many CloudIoT systems require an efficient and speedy process of these data due to time-sensitive nature of the application. Others CloudIoT systems may not be so time-sensitive, hence, can wait for the resources to get free. In this project, you will use publicly available Google, Alibaba, and AWS cloud dataset to model a novel resource scheduling and forecasting algorithm for the cloud cluster computing system. You will –
- Review of the related literature to define the best methodology to approach and frame the problem
- Process Google, Alibaba, and AWS using HPC and model their resource scheduling and management techniques.
- Develop a novel resource scheduling and management technique and middleware for improved performance of CloudIoT paradigm based cloud computing.