Providing a New Model for Discovering Cloud Services Based on Ontology
Due to its efficient, flexible, and dynamic substructure in information technology and service quality parameters estimation, cloud computing has become one of the most important issues in computer world. Discovering cloud services has been posed as a fundamental issue in reaching out high efficiency. In order to do one’s own operations in cloud space, any user needs to request several various services either simultaneously or according to a working routine. These services can be presented by different cloud producers or different decision-making policies. Therefore, service management is one of the important and challenging issues in cloud computing. With the advent of semantic web and practical services accordingly in cloud computing space, access to different kinds of applications has become possible. Ontology is the core of semantic web and can be used to ease the process of discovering services. A new model based on ontology has been proposed in this paper. The results indicate that the proposed model has explored cloud services based on user search results in lesser time compared to other models.
Keywords:cloud, computing, service, semantic, web, ontology
P. Samimi, Y. Teimouri, M. Mukhtar, “A combinatorial double auction resource allocation model in cloud computing”, Information Sciences, Vol. 357, pp. 201-216, 2016 DOI: https://doi.org/10.1016/j.ins.2014.02.008
X. Ji, F. Zeng, M. Lin, “Data transmission strategies for resource monitoring in cloud computing platforms”, Optik - International Journal for Light and Electron Optics, Vol. 127, No. 16, pp. 6726-6734, 2016 DOI: https://doi.org/10.1016/j.ijleo.2016.04.114
W. Kong, Y. Lei, J. Ma, “Virtual machine resource scheduling algorithm for cloud computing based on auction mechanism”, Optik - International Journal for Light and Electron Optics, Vol. 127, No. 12, pp. 5099-5104, 2016 DOI: https://doi.org/10.1016/j.ijleo.2016.02.061
M. Rani, R. Nayak, O. P. Vyas, “An ontology-based adaptive personalized e-learning system, assisted by software agents on cloud storage”, Knowledge-Based Systems, Vol. 90, pp. 33-48, 2015
R. Guerfel, Z. Sbai, R. B. Ayed, “Towards a System for Cloud Service Discovery and Composition Based on Ontology”, in: Lecture Notes in Computer Science, Vol. 9330, pp. 34-43, Springer, 2015 DOI: https://doi.org/10.1007/978-3-319-24306-1_4
A. Alfazi, T. H. Noor, Q. Z. Sheng, Y. Xu, “Towards Ontology-Enhanced Cloud Services Discovery”, in: Lecture Notes in Computer Science, Vol. 8933, pp. 616-629, Springer, 2014 DOI: https://doi.org/10.1007/978-3-319-14717-8_48
Y. M. Afify , I. F. Moawad, N. L. Badr, M. F. Tolba, “Cloud Services Discovery and Selection: Survey and New Semantic-Based System”, in: Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations, Vol. 70, pp. 449-477, Springer, 2014 DOI: https://doi.org/10.1007/978-3-662-43616-5_17
T. Labidi, A. Mtibaa, F. Gargouri, “Ontology-Based Context-Aware SLA Management for Cloud Computing, Model and Data Engineering”, Lecture Notes in Computer Science, Vol. 8748, pp. 193-208, Springer, 2014 DOI: https://doi.org/10.1007/978-3-319-11587-0_19
M. Parhi, B. K. Pattanayak, M.R. Patra, “A Multi-agent-Based Framework for Cloud Service Description and Discovery Using Ontology”, in: Intelligent Computing, Communication and Devices, Vol. 308, pp. 337-348, Springer, 2015 DOI: https://doi.org/10.1007/978-81-322-2012-1_35
T. Uchibayashi, B. Apduhan, N. Shiratori, “Towards a Cloud Ontology Clustering Mechanism to Enhance IaaS Service Discovery and Selection”, International Conference on Computational Science and Its Applications, Part I, pp. 545-556, Springer, 2015 DOI: https://doi.org/10.1007/978-3-319-21404-7_40
M. Olaifa , S. Ojo, T. Zuva, “An Adaptive Multi Agent Service Discovery for Peer to Peer Cloud Services”, in: Emerging Trends and Advanced Technologies for Computational Intelligence, Studies in Computational Intelligence, Vol. 647, pp. 147-163, Springer, 2016 DOI: https://doi.org/10.1007/978-3-319-33353-3_8
J. Shetty, D. A. D’Mello, “An XML based Data Representation Model to Discover Infrastructure Services”, International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials, pp.119-125, 2015 DOI: https://doi.org/10.1109/ICSTM.2015.7225400
M. Rani, R. Nayak, O. P. Vyas, “An ontology-based adaptive personalized e-learning system, assisted by software agents on cloud storage”, Knowledge-Based Systems, Vol. 90, pp. 33-48, 2015 DOI: https://doi.org/10.1016/j.knosys.2015.10.002
T. Han, K. M. Sim, “An Ontology-enhanced Cloud Service Discovery System”, International MultiConference of Engineers and Computer Scientists, Vol. 1, pp. 1-6, 2010
How to Cite
MetricsAbstract Views: 868
PDF Downloads: 318
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.