Load balancing streamed healthcare data using MR technique

Internet of Things (loT) is a promising area which enables remote health monitoring. Providing timely notifications during emergency situations supports the remote monitoring. Processing and analysis of massive data generated is a challenge faced by health industry. The enormity of data generated through connected devices and analysis thereof is a bigger challenge for traditional data management systems. Cloud Computing is an assuring technology which endows services on demand for processing, storing and analyzing the data. In order to address these challenges Hadoop MapReduce framework is used for processing and balancing the scaled data that has been distributed on the network. The real time health care applications deployed on the cloud offer timely and precised services. This paper provides an outlook on data handling from real time applications in terms of its storage, deployment and processing. The work depicts that it requires remarkably less time for executing the task when compared with conventional methods.