Abstrait

Dynamic Resource Allocation Using Nephele Framework in Cloud

Anand Prabu P, Dhanasekar P, Sairamprabhu S G

In recent years ad hoc parallel data processing is one of the emerging applications for Infrastructure-as-a- Service (IaaS) cloud environment. The current processing frameworks have been designed for homogenous cloud setup, which consequently leads to increased processing time and cost. In this paper we present Nephele, a first data processing framework for exploiting dynamic resource allocation in a cloud environment. Particular tasks of a processing job can be assigned to different types of virtual machines which are automatically instantiated and terminated during the job execution. Based on this framework, we perform Map Reduce-inspired processing jobs on an IaaS cloud system and compare the results to the popular data processing framework Hadoop.