Scheduling of Big Data application workflows in cloud and inter-cloud environments

Large amount of data is being generated every day and is creating new challenges and opportunities which lead to extraordinary new knowledge and discoveries in many application domains ranging from science and engineering to business. One of the main challenges in this era of Big Data is how to efficiently manage and analyse such scale of data. This is challenging not only due to the size of the data, but also due to its heterogeneous nature and geographic location. In this sense, clouds are becoming an increasingly popular infrastructure for enabling large-scale data intensive scientific and business applications. Cloud provides a suitable environment for processing Big Data applications to process large volumes of data and parallel processing of data. Due to the geographical distribution of data different varieties of data it is of more advantage to use a federated Inter-Cloud environment where moving of large volumes of data can be avoided. Workflows are used to allocate and schedule execution of Big Data applications in an optimized manner. In this paper we present the need of execution of Big Data Application workflows on Cloud and Inter-Cloud environments.