2018Unpublished venueRequires access

Big Data, Cloud and IoT: An Assimilation

Priya, Isha Pathak, Atul Tripathi

Open publisher page 4 citations

Abstract

Internet of things, Big data, and Cloud computing are the most prevalent technologies in present time, leading to the unprecedented developments in intelligent systems. According to the future estimates, the proliferation of IoT devices will generate zettabytes of Big data every day. Real-time processing of generated multisource heterogeneous data streams is imperative to enhance the collective intelligence of these smart things. In this regard, Big data analysis on IoT-based data can provide key insights for organizations and individuals, facilitate the effective management of IoT, and present suitable business models. It will provide definitive directions in research and development of self-configured intelligent devices in IoT application areas. A shift from batch-processing to stream-processing frameworks is foreseen due to the need of managing and analyzing incessant data streams. Besides, high-speed voluminous unstructured data is driving changes towards the scalable distributed storage solutions to alleviate the challenges involved in the traditional frameworks. In this paper, we discuss how the advancements in Cloud computing furnish the resources for storage and analysis of Big data in IoT environment. In addition, we explore the services of Cloud computing which are expanding over the time to bridge the gap between IoT and Big data technologies. Finally, some applications utilizing the integration of these three technologies are considered to indicate the future trends.

About this research paper

What this paper is about

Internet of things, Big data, and Cloud computing are the most prevalent technologies in present time, leading to the unprecedented developments in intelligent systems. According to the future estimates, the proliferation of IoT devices will generate zettabytes of Big data every day. Real-time processing of generated multisource heterogeneous data streams is imperative to enhance the collective intelligence of these smart things. In this regard, Big data analysis on IoT-based data can provide key insights for organizations and individuals, facilitate the effective management of IoT, and present suitable business models. It will provide definitive directions in research and development of self-configured intelligent devices in IoT application areas. A shift from batch-processing to stream-processing frameworks is foreseen due to the need of managing and analyzing incessant data streams. Besides, high-speed voluminous unstructured data is driving changes towards the scalable distributed storage solutions to alleviate the challenges involved in the traditional frameworks. In this paper, we discuss how the advancements in Cloud computing furnish the resources for storage and analysis of Big data in IoT environment. In addition, we explore the services of Cloud computing which are expanding over the time to bridge the gap between IoT and Big data technologies. Finally, some applications utilizing the integration of these three technologies are considered to indicate the future trends.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Internet of things, Big data, and Cloud computing are the most prevalent technologies in present time, leading to the unprecedented developments in intelligent systems. According to the future estimates, the proliferation of IoT devices will generate zettabytes of Big data every day. Real-time processing of generated multisource heterogeneous data streams is imperative to enhance the collective intelligence of these smart things. In this regard, Big data analysis on IoT-based data can provide key insights for organizations and individuals, facilitate the effective management of IoT, and present suitable business models. It will provide definitive directions in research and development of self-configured intelligent devices in IoT application areas. A shift from batch-processing to stream-processing frameworks is foreseen due to the need of managing and analyzing incessant data streams. Besides, high-speed voluminous unstructured data is driving changes towards the scalable distributed storage solutions to alleviate the challenges involved in the traditional frameworks. In this paper, we discuss how the advancements in Cloud computing furnish the resources for storage and analysis of Big data in IoT environment. In addition, we explore the services of Cloud computing which are expanding over the time to bridge the gap between IoT and Big data technologies. Finally, some applications utilizing the integration of these three technologies are considered to indicate the future trends.

Key concepts: Big data, Cloud computing, Computer science, Scalability, Data science, Internet of Things, Data stream mining, Bridge (graph theory)

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