Recent Developments in Resource Management in Cloud Computing and Large Computing Clusters

Abstract

Cloud computing and large computing clusters consist of a large number of computing resources of different types ranging from storage, CPU, memory, I/O to network bandwidth. Cloud computing exposes resources as a single access point to end users through the use of virtualization technologies. A major issue in cloud computing is how to properly allocate cloud resources to different users or frameworks accessing the cloud. There are a lot of complex, diverse, and heterogeneous workloads that need to coexist in the cloud and large-scale compute clusters, thus the need for finding efficient means of assigning resources to the different users or workloads. Millions of jobs need to be scheduled in a small amount of time, so there is a need for a resource management and scheduling mechanism that can minimize latency and maximize efficiency. Cloud resource management involves allocating computing, processing, storage, and networking resources to cloud users, in such a way that their demands and performance objectives are met. Cloud providers need to ensure efficient and effective resource provisioning while being constrained by Service Level Agreements (SLAs). This chapter gives the differences and similarities between resource management in cloud computing and cluster computing, and provide detailed information about different types of scheduling approaches and open research issues.