Big Data & Disruptive Computing Platforms Braced Internet of Things: Facets & Trends

Abstract

The Internet of Things (IoT) has been evolving in tandem with centralized cloud computing to fog computing, edge computing, Semantic computing, etc. Pervasive IoT applications like Healthcare applications generate a huge amount of sensor data and imaging data that needs to be handled rightly for further processing. In traditional IoT ecosystem, Cloud computing ensures solution for efficient management of huge data with its ability to access shared resources and provide common infrastructure in a ubiquitous manner. Majority of the IoT applications are highly sensitive to time and necessities latency bounded execution. There is time delay introduced when the data transmission occurs between the cloud and the application which is unacceptable. This chapter will disclose the various facets and trends in the integration/coupling of evolving computing platforms and disruptive technologies like Fog/Edge Computing, Big Data, blockchain with IoT that overcomes challenges existing in the traditional deployment of IoT environment. Further, there are several issues with IoT and Cloud Computing framework like each individual part of the IoT architecture could act as a point of failure that can interrupt the whole network and secondly, the centralized cloud model is vulnerable to loss of integrity of data. This chapter will review and reveal the trends in bracing computing approaches, managing the huge data using datacenters in Internet of Things ecosystem. The review is advocated with a case study on waste management system applied with the fog/edge computing and cloud computing. Further, various trends in applicability of block chain in the IoT ecosystem is also reviewed. This chapter discusses the fundamental facets of various computing paradigms and approaches that may help to address issues of big data through creating IoT ecosystems.