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Energy Conservation in Multimedia Big Data Computing and the Internet of Things—A Challenge

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Multimedia Big Data Computing for IoT Applications

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 163))

Abstract

In the recent days, wide-ranging cellular devices and purchaser gadgets in the Internet of Things (IoT) have created immense multimedia information in different types of media (for example, content, pictures, video, and sound). Due to this, there is a great increase in the research challenges for creating strategies and tools in addressing Multimedia Big Data (MMBD) for future IoT. As the worldwide framework for the ongoing data society, IoT empowers progressed benefits by interconnecting (virtual as well as physical) things dependent on existing and advancing interoperable data and correspondence advancements. An immense measure of connected objects will be installed universally in a couple of years. In the meantime, the utilization of MMBD has been developing colossally since recent years, while organizations are rapidly getting on what they remain to pick up. Actually, these two advances are affecting and molding one another. In spite of the fact that they emerge from various application situations, MMBD can be together utilized with machine learning, AI, factual, and other progressed procedures, models, and techniques to investigate or locate the profound incentive behind the immense information originated from IoT. Actually, the registering knowledge, including transformative calculation, neural systems, and the fuzzy hypothesis, is relied upon to assume a vital job for these issues. It is as yet one of the most scorching and most challenging fields to create novel processing knowledge for the reasonable situations concerned with the MMBD for future IoT. In this paper, we focus on one of the most important research domains in MMBD IoT, Energy Conservation. IoT devices communicate through the wireless communication medium and are expected to transmit information whenever needed. The battery life of IoT devices is an important concern for researchers and device manufacturers. Many exhaustive efforts have been put by researchers in this area. Since most IoT devices are usually deployed in remote and hostile environments out of reach for human users, it may not be possible to charge and recharge batteries frequently. Moreover, in MMBD IoT applications, a large volume of multimedia traffic needs to be processed, which consumes precious network resources such as bandwidth and energy. Thus, devising protocols for conserving energy of IoT devices in such environments has become a very interesting topic of research. There are various ways to achieve energy conservation in the MMBD IoT environment. Some of the popular research inclinations are designing energy-efficient communication protocols, developing of mechanisms that enable IoT devices to self-generate, recycle, store and harvest energy, and modifying underlying protocol stack of communication technologies to support energy efficiency. Our paper mainly focuses on the investigation of existing technologies and mechanisms in the above domains. We first present the need for energy conservation briefly and then discuss the key points of existing solutions for saving energy in IoT communications. At the end of the paper, we summarize our findings to describe the advantages and limitations of existing mechanisms and provide insights into possible research directions.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, India

    Pimal Khanpara & Kruti Lavingia

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  1. Pimal Khanpara
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  2. Kruti Lavingia
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Correspondence to Pimal Khanpara .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India

    Sudeep Tanwar

  2. Department of Electronics and Communication Engineering, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India

    Sudhanshu Tyagi

  3. Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India

    Neeraj Kumar

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Khanpara, P., Lavingia, K. (2020). Energy Conservation in Multimedia Big Data Computing and the Internet of Things—A Challenge. In: Tanwar, S., Tyagi, S., Kumar, N. (eds) Multimedia Big Data Computing for IoT Applications. Intelligent Systems Reference Library, vol 163. Springer, Singapore. https://doi.org/10.1007/978-981-13-8759-3_2

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