Publications

Abstract : In the world of big data and Internet of things (IoT), data grows exponentially in terms of petabytes, and subsequent processing in large scale needs commodity-based clusters to run these applications. Mobile users cannot get the commodity cluster to run parallel, complex, and scientific applications. The portable devices can form a cloudlet and use the cloud based on available resources and required resources which can be taken care by our proposed scheduler engine. We are aware that the mobile devices have resource limitations, however the combinations of several component such as portable devices and cloud computing will help to fulfill the limitation in terms of resources. To encounter the problem of performing data intensive jobs using the mobile devices and also achieve interoperability with the cloudlet and different vendors of the cloud, we have proposed various architectures to integrate IoT and big data along with MCC. The proposed architectures use middleware for the integration of MCC and big data for various technological frameworks; in our approach, we use various appliances, sensors, and portable devices having efficient utilization of the resources on the cloud and cloudlets.