Big Data in Internet of Things: Architecture and Open Research Challenges

Abstract

Big data analytics and the Internet of Things (IoT) are currently most evolving topics in the field of technology. The leading idea behind the internet of things is that almost every device that has some mac address must be linked with each other. One of the most unique features of IoT is its real-time communication of information about these devices linked together. In the past few years, huge piles of data had been generated due to the miniaturization and diversifying of physical devices that can have mac address. These huge piles of data have compromised the storage and data collection mechanism. Furthermore, this pyramid of data is completely useless without any analytical power. However, the solutions are still in their embryonic stage and this field lacks a comprehensive study and surveys. The four main distinct features about IoT are a) data processing, data change (OTLP), and high-speed data flow (b) huge data sizes generally in TBs and PBs (c) highly diverse structural and unstructured data, query language (d) diverse source of data. This paper explores the state-of-the-art research efforts projected towards these data analytics. Furthermore, data analytic methods and technologies for mining these big data are discussed.