NORA: Network Oriented Resource Allocation for Data Intensive Applications in the Cloud Environment

Optimization of data intensive applications is affected greatly by the nature of the platform, the distributed file system, the co-location of data and programs, and the proximity of resources. Data intensive applications running on a public cloud have been shown to exhibit degraded performance compared to a private cluster. This performance degradation is as a result of the inefficient resource allocation adopted in a virtualized, volatile and multi-tenancy environment such as a cloud. The placement of virtual machines is critical for improving performance in geo-clouds environment. We address degradation in performance by designing a scheduling algorithm that dynamically distributes virtual machines based on the characteristics of the job, the network characteristics and the real time performance of the data centers. Our algorithm also finds the best node(s) to host virtual machines that will yield maximum resource utilization and minimize bandwidth consumption. Our results show that incorporating these characteristics in a resource scheduling algorithm increases the performance of data intensive application than known traditional scheduling.