Task Scheduling and Cost Optimization Models for Hadoop Framework of IoT Big Data in Cloud

Internet of Things (IoT) embedded with chips and sensors can connect to humans, devices, internet and clouds intelligently. Large volume of data generated from various IoT devices will bring radical changes within today’s datacenters and will require new Big Data analytic strategies. Due to skills shortage and to keep up with the amounts of incoming data, enterprises will move towards the Cloud Computing platforms such as IaaS and PaaS. Since, the value of IoT is in the data, enterprises have to move quicker to start analyzing their data in order to get better business. In this year of the project, workload and data locality aware task scheduling models will be developed for processing the IoT Big Data in Hadoop framework. Scheduling algorithms will be designed for the input jobs of Big Data generated from the IoT devices in smart homes and communities taking node heterogeneity into account. A multi-cluster multi node Hadoop platform for Big Data analytic will be implemented to analyze the ECG and nutrition data for health care management and data visualization applications will be developed in Android mobiles.

Project ID:PB10408-5705
External Project ID:MOST104-2221-E182-004