A Review on Cloud, Fog, Roof, and Dew Computing: IoT Perspective

A Review on Cloud, Fog, Roof, and Dew Computing: IoT Perspective

Ishtiaq Ahammad, Ashikur Rahman Khan, Zayed Us Salehin
Copyright: © 2021 |Pages: 28
DOI: 10.4018/IJCAC.2021100102
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The internet of things (IoT) offers a range of benefits for its users, ranging from quicker and more precise perception of our ecosystem to more cost-effective monitoring of manufacturing applications, by taking internet access to the things. Due to the ubiquitous existence of the internet, there's been an increasing pace in the IoT. Such a growing pace has brought about the term of IoT ecosystem. This exponential growing IoT ecosystem will encounter several challenges in its path. Computing domains were used from very initial stage to assist the IoT ecosystem and mitigate those challenges. To understand the impact of computing domains in IoT ecosystem, this paper performs the elaborative study on cloud, fog, roof, and dew computing including their interaction, benefits, and limitations in IoT ecosystem. The brief comparative analysis on these four computing domains are then performed. The impact of internet and offline computing on these computing domains are then analyzed in depth. Finally, this paper presents the suggestions of potential appropriate computing domain strategies for IoT ecosystems.
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The IoT is composed of devices which access to internet and exchange data among themselves. IoT devices include chip-equipped things for collecting and communicating data across a network. Current and future IoT devices are vast in scale. Consumers frequently use their mobile phones to connect with IoT devices, be it a home thermostat or smart watch. With the emergence of IoT, our communication capabilities will not be limited to mobile platforms only. Instead, it will enlarge to all of the things we exist side by side. The IoT will constitute an essential part of integrated living and industrialization activities. The IoT framework by now connects billions of devices already and this number is rising extremely rapidly (Ninikrishna, T. et al, 2017). According to the Statista Research department's projection (Statista, 2020), an approximate 26.66 billion IoT-connected devices have been in use worldwide by the end of 2019. It will be 30.73 billion by the end of 2020. By 2025 there will be 75.44 billion devices globally connected to IoT. There'll be 79 ZB of data produced by those tens of billions of IoT devices in 2025 (Mass, F., 2019). This will trigger organizations to re-examine their strategies on data collection, maintenance, and use. The McKinsey Global Institute reports a financial impact of as much as $11.1 trillion per annum in 2025 (Puliafito, C. et al, 2019) for IoT systems.

The Internet of Things (IoT), powered by forthcoming communication technologies (e.g., 5G), and new developments in artificial intelligence (e.g., deep learning), is about to bring a high impact in the way we interact with things, services and people in the next few years. Even though the term IoT has been around for almost 20 years now, currently we are still in the very early stages, with a handful of commercial applications and numerous initial proof-of-concept projects in pilot sites. Full-fledged IoT systems are still not present in our daily lives, with the exception perhaps of some very specific applications, such as traffic management services (e.g., Waze) and ride hailing services (e.g., Uber).

In the current stage of IoT deployment, developers and integrators have to build and deploy the entire end-to-end software, hardware and communication infrastructure for providing a smart application. Sensors and actuators must be installed as well as platforms and applications must be developed. In the future, when billions of devices will be connected, sensing and actuation systems will be already in place. In such scenario, new applications will be required to use existing legacy sensing and actuation systems, for streamlining application deployment, backward compatibility and cost savings.! This situation will build a complex ecosystem of hardware, software and communication components that will require new IoT smart applications to interact with a variety of other existing and new pieces needed for filing the gaps and enabling end-to-end smart application deployments to come true. In Europe, the need for ecosystems comprised of platforms and businesses have been already identified by different projects such as

Recent and upcoming communication technologies (e.g. Li-Fi, 5G) and recent innovations in artificial intelligence (e.g. machine learning, deep learning) will power the future IoT. In the past decade Deep learning has been used by many researchers for designing computational system which can analyze this massive amount of data in time efficient manner (Srivastava, M., 2020). The deep learning models works very well with huge volume of data than the lesser data (Memon, M. et al, 2020). In recent IoT implementation process, developers and integrators will develop and deploy the whole end-end software, hardware, and communications system to deliver a smart application. When tens of billions of devices are connected in coming years, sensing and actuation systems would already be in position. In this scenario, the use of current legacy sensing and actuation system requires new programs to standardize application deployment, additional features, and reduced costs. This scenario will create a complicated ecosystem of elements in software, hardware, and communication which can be termed as IoT ecosystem. Innovative IoT smart application would be necessary for the ecosystem to communicate with a number of other current and emerging parts that required filling the holes and allowing end-end smart application deployments to happen.

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