Department of Computer Science and Information Systems

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Fog computing in enabling 5G-driven emerging technologies for development of sustainable smart city infrastructures
(Springer, 2022-01) Gupta, Shashank
The usage of 5G-enabled IoT devices is rising exponentially as humans tend to shift towards a more automated lifestyle. A significant amount of IoT devices is expected to join the network as IoT has allowed interconnection and transmission among global devices which has resulted in generation of enormous diverse data. There is a requirement for a real-time, latency-specific, and network efficient computing paradigm in 5G-enabled smart city infrastructure. Fog computing presents trustworthy solutions to tackle these issues by combining edge users. They store, control, communicate, configure, measure, and manage big data produced by IoT devices. In this survey, the authors have performed a comprehensive study on fog computing and have classified various such paradigms. The authors have performed an extensive evaluation of features, along with the algorithmic and architectural packages deployed in the framework. This survey covers various 5G-enabled Industrial IoT (I-IoT) application settings and unleashes various fog framework-based solutions for numerous real-world application challenges in sustainable smart city infrastructures. Numerous contributions of fog computing towards latency-sensitive applications like healthcare 4.0, smart conveyance, smart waste management, smart energy handling, etc. has also been discussed. Fog computing framework apart from the abilities, also inherits various security flaws from cloud computing paradigm, and these flaws needs to be rectified in the interest of the end user. This survey presents a comprehensive review of state-of-the-art literature schemes to preserve the integrity of data in sustainable smart city infrastructure. Diverse phrases employed for investigating numerous security and privacy concerns in 5G enabled technologies are discussed in a sophisticated approach.
Leveraging big data analytics in 5G-enabled IoT and industrial IoT for the development of sustainable smart cities
(2022-07) Gupta, Shashank
There has been an exponential growth in the number of low-cost heterogeneous sensor devices that are connected to the internet in the existing infrastructure of smart cities in the past decade. These sensors and actuator devices are employed in various industries to collect invaluable data that greatly impacts business decisions. State-of-the-art research is being carried out to process the high-volume data collected in high velocity streams with high variability in order to draw meaningful insights to cater to business needs in various domains. Big data analytics finds diversified opportunities in 5G-enabled Internet of Things (IoT) and industrial IoT environment to study the data patterns and produce new results which provides big organizations a conducive environment to take informed decisions. This article presents an exhaustive investigation of the various applications and algorithms of the big data analytics in 5G-driven IoT and industrial IoT systems with a detailed taxonomy of the existing analytical systems and also the challenges specific to the applications in an IoT environment. A holistic understanding on the importance of security and privacy of big data during the development of smart city infrastructure in high velocity streaming process has been explained for a broad understanding of the big data streaming processes. A thorough analysis of important data mining algorithms such as classification, association rule mining, clustering, and prediction methods for big IoT data from the recent literature also has been presented to provide a clear understanding of existing issues in handling big data in 5G-enabled IoT for the development of sustainable smart city infrastructure.