Internet of Things is a network constituted by uniquely identifiable commodity objects or devices equipped with some sensing system. Internet of Things paradigm enables the objects, also called things, for sensing, which subsequently interoperate and communicates with other objects for data exchange through an existing physical network infrastructure. Therefore, Internet of Things promotes a seamless amalgamation between the smart devices, scatter around us, and the physical world to ensure full automation that eventually ameliorates human life. Some of the examples of Internet of Things-enabled commodity devices or things include heart monitoring implants, automobiles with embedded sensors, firefighter’ devices, smart thermostat systems, and Wi-Fi enabled washer/dryers. As the arena of Internet of Things is expanding, the number of Internet of Things-enabled applications is also rapidly growing, which results in massive growth of smart devices in multiple order comparatively.

This swift increase in the number of sensing things is responsible for generating and storage of a plethora amount of diversified data at much faster rate. The Internet of Things things sense and collect the data from the highly sparse geographical environments. The data is exchanged with remotely stationed peer devices for numerous quick and efficient operations such agglomeration; this is where the traditional data management mechanisms succumb and opportunity for some new powerful technologies arises. As a result, today, the cloud computing technology has emerged as one such innovation that have been invented to efficiently tackle the growing Internet of Things issues. Internet of Things paradigm is increasingly encouraging the ubiquitous connectivity of the intelligent objects within internal or external world. The continuous rapid growth of large number of Internet of Things-enabled objects and storage technology have resulted into the massive amount of heterogeneous digital footprints and sizeable traces. A vast amount of data is being generated by various sensing sources every day. It is observed that the primary sources of Internet of Things are sensor-enabled devices, unlike the traditional Big Data, where social media is the major contributor in data collection as compared to the sensing systems. Therefore, Internet of Things can be seen as a subset of traditional Big Data. The actual pattern and nature of such data is indistinct, but is certainly large, complex, heterogonous, structure and unstructured. Literature demonstrates some important attributes of Internet of Things such as volume, variety, and velocity and some core constituents of Internet of Things like sensor-embedded devices, intelligence for quick decision making, and connectivity for data sharing.

Apparently, to obtain constructive insights from Internet of Things, gigantic efforts are required for Internet of Things modeling in contrast to that of traditional data. Also, the rapid growth of sensing devices under Internet of Things purview is generating such a large scale complex and heterogeneous data that the available computing capacity of the existing systems unable to successfully match up the data challenges and today, this has emerged as one of the core issues for the data science community. The storage capacity and also the processing power of the existing data computing systems are failed in handling the data stress. As Internet of Things and its applications are majorly impacting the human life, the scientific communities contemplate a broader outreach from the processing and sharing of Internet of Things across the variety of the several commodity devices around us. Consequently, the development of new capable technologies is encouraged to cater the current data processing need.


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