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Cloud computing is a relatively new paradigm that provides extensive services to various customers (Ziebell et al., 2019). The data-intensive application running on Cloud may benefit from the machine-understandable Semantic Web technologies (Hossain et al., 2019).
The semantic web technologies have recently gained attention towards proposing viable solutions to Cloud-computing related problems (Elzein et al., 2018). The machine-understandable representation of information has opened new paradigms (Olakanmi & Dada, 2019). This scenario has opened new potentials to researchers and scientists in managing large amounts of data in the best possible and available ways using the recent archive (Ali, 2019), process and execution mechanism (Bellini et al., 2015; Lee et al., 2013; Silva et al., 2013).
The current challenges related to big data and its emergence have complicated efficient data management due to the exponential growth of data (Acosta et al., 2017; Siow et al., 2017; X. Wang et al., 2015). The current Cloud resources seem insufficient to manage large data repositories and extract knowledge from them (Herzfeldt et al., 2019). Although companies are providing excellent services in terms of data archive, application deployments, and fact findings from existing data, still keeping in mind the current explosion of data, we need more robust and resilient solutions towards better management of Cloud data (Destefano et al., 2016; Wu et al., 2019). Semantic Web technologies provide one possible solution to the problem, Several researchers have used these technologies in solving similar problems (Fang et al., 2016; Niknia & Mirtaheri, 2015; Srinivasulu et al., 2015).
The cyber physical system concepts have introduced new platforms in the form of the industry 4.0 revolution (S. Wang et al., 2016). The current need to integrate Cloud capabilities to align with the industry 4.0 standards is practically realized (AlZu'bi et al., 2020)(Tewari & Gupta, 2020)(H. Wang et al., 2020)(D. Li et al., 2019)(Bhushan & Gupta, 2019). Besides, the intrusion of big data generated from industry-related objects has resulted in new challenges for researchers to devise robust query control and management mechanisms (Liao et al., 2016; Samanthula et al., 2015; Verginadis et al., 2017). Additionally, the smart cities concept enables the smart devices to generate many queries related to each smart city notion. At times, we need to prioritize the queries that demand immediate attention; for instance, the queries related to fire, temperate, explosive detection and natural disaster alarms, etc. Such high priority queries are mixed with low priority queries generated from other objects of smart cities (Liu et al., 2016; Rady et al., 2019; Ye et al., 2018). Since the smart devices are being controlled through network resources and being managed by Cloud applications, the semantic web technologies may offer great help in identifying and addressing the potential queries from low priority queries (Kaoutar et al., 2018; Niknia & Mirtaheri, 2015; Srinivasulu et al., 2015).