E-learning in Higher Education in India: Experiences and Challenges—An Exploratory Study

Resource allocation for Big data streams in cloud systems involves select-
ing the appropriate cloud resources. Since incorrect resource allocation results in

either under provisioning or over provisioning, accurate resource allocation becomes
challenging in Big data applications. Hence, the objective of this work is to design
an optimal solution for resource allocation for minimizing the network bandwidth
and response delay. In this paper, a task allocation and re-allocation mechanism for
Big data applications is designed. It consists of two important agents: RE-allocation
Agent (REA) and Resource Agent (RA). The RA is responsible for mapping the user
requirements to the available VMs. The REA monitors the resources and chooses the
VMs for resource reconfiguration. Then, it dispatches an allocation or de-allocation
request to RA, running in the physical system, based on the varying requirements ofvirtual machines. Experimental results show that the proposed TARA has less exe-
cution time and achieves better utilization of resources, when compared to existing