Efficiency of Semantic Web Implementation on Cloud Computing: A Review

Kazheen Ismael Taher; Rezgar Hasan Saeed; Rowaida  Kh. Ibrahim; Zryan Najat Rashid; Lailan  M. Haji; Naaman  Omar; Hivi Ismat Dino

doi:10.48161/qaj.v1n3a72

Authors

Kazheen Ismael Taher Dept. of Computer Network Sulaimani Polytechnic University Sulaimani-Iraq
Rezgar Hasan Saeed Computer Science Dept. Near East University Cyprus
Rowaida Kh. Ibrahim Computer science Dept. University of Zakho Duhok -Iraq
Zryan Najat Rashid Dept. of Computer Network Sulaimani Polytechnic University Sulaimani-Iraq
Lailan M. Haji Computer science Dept. University of Zakho Duhok -Iraq
Naaman Omar Information Technology Dept. Duhok Polytechnic University Duhok-Iraq
Hivi Ismat Dino Computer science Dept. University of Zakho Duhok -Iraq

DOI:

https://doi.org/10.48161/qaj.v1n3a72

Keywords:

Semantic web, Cloud Computing, Semantic Technologies, cloud-driven.

Abstract

Semantic web and cloud technology systems have been critical components in creating and deploying applications in various fields. Although they are self-contained, they can be combined in various ways to create solutions, which has recently been discussed in depth. We have shown a dramatic increase in new cloud providers, applications, facilities, management systems, data, and so on in recent years, reaching a level of complexity that indicates the need for new technology to address such tremendous, shared, and heterogeneous services and resources. As a result, issues with portability, interoperability, security, selection, negotiation, discovery, and definition of cloud services and resources may arise. Semantic Technologies, which has enormous potential for cloud computing, is a vital way of re-examining these issues. This paper explores and examines the role of Semantic-Web Technology in the Cloud from a variety of sources. In addition, a "cloud-driven" mode of interaction illustrates how we can construct the semantic web and provide automated semantical annotations to web applications on a large scale by leveraging Cloud computing properties and advantages.

Downloads

Download data is not yet available.

References

Hassan, R.J., et al., State of art survey for iot effects on smart city technology: challenges, opportunities, and solutions. Asian Journal of Research in Computer Science, 2021: p. 32-48.

Adedugbe, O., et al., Leveraging cloud computing for the semantic web: review and trends. Soft Computing, 2020. 24(8): p. 5999-6014.

Adedugbe, O., E. Benkhelifa, and R. Campion. Towards Cloud driven semantic annotation. in 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA). 2017. IEEE.

Abdullah, P.Y., et al., HRM system using cloud computing for Small and Medium Enterprises (SMEs). Technology Reports of Kansai University, 2020. 62(04): p. 04.

Yahia, H.S., et al., Comprehensive survey for cloud computing based nature-inspired algorithms optimization scheduling. Asian Journal of Research in Computer Science, 2021: p. 1-16.

Ageed, Z.S., et al., A survey of data mining implementation in smart city applications. Qubahan Academic Journal, 2021. 1(2): p. 91-99.

Wu, Y., et al. Automatically semantic annotation of network document based on domain knowledge graph. in 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC). 2017. IEEE.

Mell, P. and T. Grance, The NIST definition of cloud computing. 2011.

Rashid, Z.N., et al. Distributed cloud computing and distributed parallel computing: A review. in 2018 International Conference on Advanced Science and Engineering (ICOASE). 2018. IEEE.

Ageed, Z.S., et al., A state of art survey for intelligent energy monitoring systems. Asian Journal of Research in Computer Science, 2021: p. 46-61.

Martino, B.D., et al., An OWL ontology to support cloud portability and interoperability. International Journal of Web and Grid Services, 2015. 11(3): p. 303-326.

Di Martino, B., G. Cretella, and A. Esposito. Towards a unified owl ontology of cloud vendors' appliances and services at paas and saas level. in 2014 Eighth International Conference on Complex, Intelligent and Software Intensive Systems. 2014. IEEE.

Bellini, P., D. Cenni, and P. Nesi, Smart cloud engine and solution based on knowledge base. Procedia Computer Science, 2015. 68: p. 3-16.

Somasundaram, T.S., et al., Semantic-enabled CARE Resource Broker (SeCRB) for managing grid and cloud environment. The Journal of Supercomputing, 2014. 68(2): p. 509-556.

Brabra, H., et al. Semantic web technologies in cloud computing: a systematic literature review. in 2016 IEEE International Conference on Services Computing (SCC). 2016. IEEE.

Di Modica, G. and O. Tomarchio, Matching the business perspectives of providers and customers in future cloud markets. Cluster Computing, 2015. 18(1): p. 457-475.

Joshi, K.P., Y. Yesha, and T. Finin, Automating cloud services life cycle through semantic technologies. IEEE Transactions on Services Computing, 2012. 7(1): p. 109-122.

Rashid, Z.N., S.R. Zeebaree, and A. Shengul. Design and analysis of proposed remote controlling distributed parallel computing system over the Cloud. in 2019 International Conference on Advanced Science and Engineering (ICOASE). 2019. IEEE.

Hitzler, P., M. Krotzsch, and S. Rudolph, Foundations of semantic web technologies. 2009: CRC press.

Selamat, S.A.A.-Z.A., Electronic Learning Management System Based on Semantic Web Technology: A Review. Int. J. Adv. Electron. Comput. Sci, 2017. 4(3): p. 1-6.

Woodworth, J., M.A. Salehi, and V. Raghavan. S3C: An architecture for space-efficient semantic search over encrypted data in the Cloud. in 2016 IEEE International Conference on Big Data (Big Data). 2016. IEEE.

Ibrahim, R., S. Zeebaree, and K. Jacksi, Survey on Semantic Similarity Based on Document Clustering. Adv. sci. technol. eng. syst. j, 2019. 4(5): p. 115-122.

Ismail, S. and T. Shaikh. ALiterature REVIEW ON SEMANTIC WEB–UNDERSTANDING THE PIONEERS'PERSPECTIVE. in The Sixth International Conference on Computer Science, Engineering and Applications. 2016.

Coronado, M., C.A. Iglesias, and E. Serrano, Modelling rules for automating the Evented WEb by semantic technologies. Expert Systems with Applications, 2015. 42(21): p. 7979-7990.

Abdulqadir, H.R., et al., A study of moving from cloud computing to fog computing. Qubahan Academic Journal, 2021. 1(2): p. 60-70.

Berlanga, R., V. Nebot, and M. Pérez, Tailored semantic annotation for semantic search. Journal of Web Semantics, 2015. 30: p. 69-81.

Shukur, H., et al., Cloud computing virtualization of resources allocation for distributed systems. Journal of Applied Science and Technology Trends, 2020. 1(3): p. 98-105.

Alam, F., et al., Towards a semantic web stack applicable for both RDF and topic maps: a survey. University of engineering and Technology Taxila. Technical Journal, 2015. 20(2): p. 114.

Abdulla, A.I., et al., Internet of Things and Smart Home Security. Technol. Rep. Kansai Univ, 2020. 62(5): p. 2465-2476.

Ye, J., et al., Semantic web technologies in pervasive computing: A survey and research roadmap. Pervasive and Mobile Computing, 2015. 23: p. 1-25.

Gutiérrez, Y., D. Tomás, and I. Moreno, Developing an ontology schema for enriching and linking digital media assets. Future Generation Computer Systems, 2019. 101: p. 381-397.

Basu, A., Semantic web, ontology, and linked data, in Web services: concepts, methodologies, tools, and applications. 2019, IGI Global. p. 127-148.

Wang, X., X. Zhang, and M. Li, A survey on semantic sensor web: sensor ontology, mapping and query. International Journal of u-and e-Service, Science and Technology, 2015. 8(10): p. 325-342.

Abdulraheem, A.S., et al., Home automation system based on IoT. 2020.

Zebari, S.R. and N.O. Yaseen, Effects of Parallel Processing Implementation on Balanced Load-Division Depending on Distributed Memory Systems. J. Univ. Anbar Pure Sci, 2011. 5(3): p. 50-56.

Haji, L.M., et al., Impact of cloud computing and Internet of things on the future Internet. Technology Reports of Kansai University, 2020. 62(5): p. 2179-2190.

Grigoras, D. and P. Gepner. The Distributed Mobile Cloud Supporting the Internet of Things. in 2015 14th International Symposium on Parallel and Distributed Computing. 2015. IEEE.

Malallah, H., et al., A Comprehensive Study of Kernel (Issues and Concepts) in Different Operating Systems. Asian Journal of Research in Computer Science, 2021: p. 16-31.

Qaqos, N.N., S.R. Zeebaree, and B.K. Hussan, Opnet Based Performance Analysis and Comparison Among Different Physical Network Topologies. Academic Journal of Nawroz University, 2018. 7(3): p. 48-54.

Yasin, H.M., et al., IoT and ICT based Smart Water Management, Monitoring and Controlling System: A Review. Asian Journal of Research in Computer Science, 2021: p. 42-56.

Sahmim, S. and H. Gharsellaoui, Privacy and security in internet-based computing: cloud computing, Internet of things, Cloud of things: a review. Procedia computer science, 2017. 112: p. 1516-1522.

Ibrahim, I.M., Task scheduling algorithms in cloud computing: A review. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021. 12(4): p. 1041-1053.

Zebari, I.M., S.R. Zeebaree, and H.M. Yasin. Real Time Video Streaming From Multi-Source Using Client-Server for Video Distribution. in 2019 4th Scientific International Conference Najaf (SICN). 2019. IEEE.

Yasin, H.M., S.R. Zeebaree, and I.M. Zebari. Arduino Based Automatic Irrigation System: Monitoring and SMS Controlling. in 2019 4th Scientific International Conference Najaf (SICN). 2019. IEEE.

Nawaz, F., A. Mohsin, and N.K. Janjua, Service description languages in cloud computing: state-of-the-art and research issues. Service oriented computing and applications, 2019. 13(2): p. 109-125.

Haji, S.H., et al., Comparison of Software Defined Networking with Traditional Networking. Asian Journal of Research in Computer Science, 2021: p. 1-18.

Garg, S. and S. Garg. Automated cloud infrastructure, continuous integration and continuous delivery using docker with robust container security. in 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR). 2019. IEEE.

Kirrane, S., et al., A decade of Semantic Web research through the lenses of a mixed methods approach. Semantic Web, 2020(Preprint): p. 1-27.

Hsu, I.C. and Y.H. Lin, Integrated machine learning with semantic web for open government data recommendation based on cloud computing. Software: Practice and Experience, 2020. 50(12): p. 2293-2312.

Iatrellis, O., et al., Cloud computing and semantic web technologies for ubiquitous management of smart cities-related competences. Education and Information Technologies, 2021. 26(2): p. 2143-2164.

Modi, K.J. and S. Garg, A QoS-based approach for cloud-service matchmaking, selection and composition using the Semantic Web. Journal of Systems and Information Technology, 2019.

Das, N.N., et al. Semantic Big Data Searching in Cloud Storage. in 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon). 2019. IEEE.

Parra-Royon, M., G. Atemezing, and J.M. Benitez-Sanchez, Semantics of Data Mining Services in Cloud Computing. IEEE Transactions on Services Computing, 2020.

Ouchaou, L., et al. Semantic Networks Based Approach for SaaS Management in Cloud Computing. in 2018 International Conference on Smart Communications in Network Technologies (SaCoNeT). 2018. IEEE.

Adedugbe, O., E. Benkhelifa, and R. Campion. A cloud-driven framework for a holistic approach to semantic annotation. in 2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS). 2018. IEEE.

Abatal, A., H. Khallouki, and M. Bahaj. A semantic smart interconnected healthcare system using ontology and cloud computing. in 2018 4th International Conference on Optimization and Applications (ICOA). 2018. IEEE.

Mittal, S., et al. A question and answering system for management of cloud service level agreements. in 2017 IEEE 10th International Conference on Cloud Computing (CLOUD). 2017. IEEE.