Dr Priya Chandran

Simulation environments provide a comprehensive set of advantages to users, like cost effectiveness and capability to understand the shortcomings of the system under design, without physical implementation. Simulation platforms help the industry and academia, to document and publish their research outputs in a timely and cost efficient manner. The ECSim tool presented here, is meant for academic use in the initial stages of research. The platform provides an environment where the performance of erasure coded storage systems can be tested without much effort. The main highlight of the simulator is that it provides a very simple environment which can run on a standalone system. The environment does not require the user to be a programmer, since it provides an interactive command line interface to the user. The ability to simulate data center, clusters, master nodes, storage nodes with computing power, storage devices, bandwidth usage and disk I/O involved are notable features of ECSim.

Abstract Cloud-based MapReduce platforms offer ready to use MapReduce clusters. The problem of allocating Virtual Machines (VMs) carrying out the computation, for minimizing data transfer delay is a crucial one in this context, as the MapReduce tasks are communication intensive. The interaction between \{VMs\} may face varying delays, if the \{VMs\} are hosted in different Physical Machines (PMs). This work aims to optimize the data transfer delay between VMs, which is denoted by the distance between the VMs. We propose an approximation algorithm for \{VM\} allocation in data centers wherein the distances between \{VMs\} satisfy triangular inequality and an optimization algorithm for \{VM\} allocation in data centers where the distances between \{VMs\} do not satisfy triangular inequality. Simulations on CloudSim demonstrate the performance of our algorithms and the results affirm the reduction in job completion time compared to other allocation schemes.