Resource Management and Scheduling for Big Data Applications in Cloud Computing Environments

TL;DR

This paper explores resource management and scheduling techniques for big data applications in cloud computing, focusing on layered architectures and SLA-based job scheduling to optimize performance and resource utilization.

Contribution

It provides a comprehensive overview of resource management architectures and discusses recent advances in SLA-based scheduling for big data in cloud environments.

Findings

Analysis of layered resource management architectures

Review of SLA-based scheduling techniques

Identification of best practices in cloud big data management

Abstract

This chapter presents software architectures of the big data processing platforms. It will provide an in-depth knowledge on resource management techniques involved while deploying big data processing systems on cloud environment. It starts from the very basics and gradually introduce the core components of resource management which we have divided in multiple layers. It covers the state-of-art practices and researches done in SLA-based resource management with a specific focus on the job scheduling mechanisms.