Efficient Software-Defined Big Data Collection and Analysis using Internet of Things

Abstract

The Internet of Things (IoT) has been widely used in big data applications, remote sensing application, intelligent transportation system (ITS), smart homes/cities and urban planning, and so on. Apparently, to provide better services, the IoT devices are deployed throughout the city for data collection. As a result, the IoT devices and the modules involved in the communication consume a lot energy, bandwidth during data collection, and transmission. Moreover, internet enabled cars and smartphones have recently become an essential part of people’s life, which integrates more and more sensors. Though, various activities and had to predict and Network management, availability and constant data rate is a major issue in IoT devices communication. Therefore, to cope with such constraints, this paper presents a system architecture based on the Internet of Things and Software Defined Network. The SDN will act as a backbone of the whole system for round the clock network availability using SDN controller. IoT framework received big data from the IoT devices, analyzed this received big data in IoT framework, and finally push this in hand filtered intelligent information into cloud data source. SDN controller programmed the efficient solution to rout network traffic to IoT framework and after analysis submission of data at cloud repository. In this paper we proposed a combined integrated system that consists of three tiers. Every tier will play a vital role for the interconnected system. Tier- I: Provision of efficient and shortest route for network communication from IoT enabled devices to IoT framework. Tier - II: Collection of Big Data from IoT enabled devices and provide this data to IoT framework. Tier – III: Analysis on Big Data using Hadoop and Store analyzed Big Data at Cloud/Data storage repository. This whole process will lead toward Urban Planning.