{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T03:24:18Z","timestamp":1762917858530,"version":"build-2065373602"},"reference-count":51,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,1,3]],"date-time":"2018-01-03T00:00:00Z","timestamp":1514937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>In recent years, virtual learning environments are gaining more and more momentum, considering both the technologies deployed in their support and the sheer number of terminals directly or indirectly interacting with them. This essentially means that every day, more and more smart devices play an active role in this exemplary Web of Things scenario. This digital revolution, affecting education, appears clearly intertwined with the earliest forecasts of the Internet of Things, envisioning around 50 billions heterogeneous devices and gadgets to be active by 2020, considering also the deployment of the fog computing paradigm, which moves part of the computational power to the edge of the network. Moreover, these interconnected objects are expected to produce more and more significant streams of data, themselves generated at unprecedented rates, sometimes to be analyzed almost in real time. Concerning educational environments, this translates to a new type of big data stream, which can be labeled as educational big data streams. Here, pieces of information coming from different sources (such as communications between students and instructors, as well as students\u2019 tests, etc.) require accurate analysis and mining techniques in order to retrieve fruitful and well-timed insights from them. This article presents an overview of the current state of the art of virtual learning environments and their limitations; then, it explains the main ideas behind the paradigms of big data streams and of fog computing, in order to introduce an e-learning architecture integrating both of them. Such an action aims to enhance the ability of virtual learning environments to be closer to the needs of all the actors in an educational scenario, as demonstrated by a preliminary implementation of the envisioned architecture. We believe that the proposed big stream and fog-based educational framework may pave the way towards a better understanding of students\u2019 educational behaviors and foster new research directions in the field.<\/jats:p>","DOI":"10.3390\/fi10010004","type":"journal-article","created":{"date-parts":[[2018,1,3]],"date-time":"2018-01-03T12:00:06Z","timestamp":1514980806000},"page":"4","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["A Virtual Learning Architecture Enhanced by Fog Computing and Big Data Streams"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5948-5845","authenticated-orcid":false,"given":"Riccardo","family":"Pecori","sequence":"first","affiliation":[{"name":"SMARTEST Research Centre, eCampus University, Via Isimbardi 10, 22060 Novedrate, CO, Italy"},{"name":"Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze 181\/A, 43124 Parma, PR, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2018,1,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ducange, P., Pecori, R., and Mezzina, P. (2017). A glimpse on big data analytics in the framework of marketing strategies. Soft Comput., 1\u201318.","DOI":"10.1007\/s00500-017-2536-4"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"37","DOI":"10.4018\/IJDST.2016010103","article-title":"Applying Security to a big stream cloud Architecture for the Internet of Things","volume":"7","author":"Belli","year":"2016","journal-title":"Int. J. Distrib. Syst. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Bonomi, F., Milito, R., Natarajan, P., and Zhu, J. (2014). Fog computing: A Platform for Internet of Things and Analytics. Big Data and Internet of Things: A Roadmap for Smart Environments, Springer.","DOI":"10.1007\/978-3-319-05029-4_7"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Ducange, P., Pecori, R., Sarti, L., and Vecchio, M. (2016, January 19\u201321). Educational big data Mining: How to Enhance virtual learning environments. Proceedings of the International Joint Conference SOCO\u201916-CISIS\u201916-ICEUTE\u201916, San Sebasti\u00e1n, Spain.","DOI":"10.1007\/978-3-319-47364-2_66"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.compedu.2014.08.017","article-title":"Cloud computing and education: A state-of-the-art survey","volume":"80","year":"2015","journal-title":"Comput. Educ."},{"key":"ref_6","first-page":"89","article-title":"Unraveling Students\u2019 Interaction Around a Tangible Interface using Multimodal Learning Analytics","volume":"7","author":"Schneider","year":"2015","journal-title":"J. Educ. Data Min."},{"key":"ref_7","first-page":"20","article-title":"Multi-Armed Bandits for Intelligent Tutoring Systems","volume":"7","author":"Clement","year":"2015","journal-title":"J. Educ. Data Min."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1016\/j.compedu.2010.09.012","article-title":"Efficient learning using a virtual learning environment in a university class","volume":"56","author":"Stricker","year":"2011","journal-title":"Comput. Educ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2505","DOI":"10.1016\/j.compedu.2011.06.017","article-title":"Design characteristics of virtual learning environments: State of research","volume":"57","author":"Mueller","year":"2011","journal-title":"Comput. Educ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1109\/TLT.2015.2441718","article-title":"Increasing Students Awareness of Their Behavior in Online Learning Environments with Visualizations and Achievement Badges","volume":"8","author":"Auvinen","year":"2015","journal-title":"IEEE Trans. Learn. Technol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.compedu.2012.11.026","article-title":"The role of authenticity in design-based learning environments: The case of engineering education","volume":"64","author":"Strobel","year":"2013","journal-title":"Comput. Educ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1109\/TLT.2015.2438864","article-title":"Low Cost Ubiquitous Context-Aware Wireless Communications Laboratory for Undergraduate Students","volume":"9","author":"Pardo","year":"2016","journal-title":"IEEE Trans. Learn. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Hung, P., Lam, J., Wong, C., and Chan, T. (2015, January 27\u201329). A Study on Using Learning Management System with Mobile App. Proceedings of the International Symposium on Educational Technology (ISET), Wuhan, China.","DOI":"10.1109\/ISET.2015.41"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1109\/TLT.2014.2381467","article-title":"Towards User Support in Ubiquitous Learning Systems","volume":"8","author":"Gilman","year":"2015","journal-title":"IEEE Trans. Learn. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1080\/13614568.2015.1077277","article-title":"A recommendation module to help teachers build courses through the Moodle Learning Management System","volume":"22","author":"Limongelli","year":"2016","journal-title":"New Rev. Hypermedia Multimed."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1109\/TLT.2015.2434824","article-title":"Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles","volume":"9","author":"Sergis","year":"2016","journal-title":"IEEE Trans. Learn. Technol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.compedu.2016.06.004","article-title":"Understanding cloud-based VLE from the SDT and CET perspectives: Development and validation of a measurement instrument","volume":"101","author":"Hew","year":"2016","journal-title":"Comput. Educ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.future.2014.10.033","article-title":"Cloud E-learning for Mechatronics: CLEM","volume":"48","author":"Chao","year":"2015","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1109\/TLT.2016.2531685","article-title":"A Contextualized System for Supporting Active Learning","volume":"9","author":"Huete","year":"2016","journal-title":"IEEE Trans. Learn. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1109\/TLT.2015.2470683","article-title":"VirTUal remoTe labORatories Management System (TUTORES): Using cloud Computing to Acquire University Practical Skills","volume":"9","author":"Caminero","year":"2016","journal-title":"IEEE Trans. Learn. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1016\/j.chb.2015.01.032","article-title":"Aspect oriented design for team learning management system","volume":"51","year":"2015","journal-title":"Comput. Hum. Behav."},{"key":"ref_22","first-page":"255","article-title":"An E-learning System Architecture based on cloud computing","volume":"6","author":"Masud","year":"2012","journal-title":"Int. J. Comput. Electr. Autom. Control Inf. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.compedu.2016.07.003","article-title":"The use of a mobile learning management system and academic achievement of online students","volume":"102","author":"Han","year":"2016","journal-title":"Comput. Educ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1504\/IJLT.2014.062447","article-title":"E-learning and Educational Data Mining in cloud computing: An Overview","volume":"9","author":"Peralta","year":"2014","journal-title":"Int. J. Learn. Technol."},{"key":"ref_25","first-page":"15","article-title":"Mining big data in Real Time","volume":"37","author":"Bifet","year":"2013","journal-title":"Informatica"},{"key":"ref_26","unstructured":"Erl, T., Khattak, W., and Buhler, P. (2016). Big Data Fundamentals: Concepts, Drivers & Techniques, Prentice Hall Press."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MC.2013.326","article-title":"Storage Challenge: Where Will All That big data Go?","volume":"46","author":"Leavitt","year":"2013","journal-title":"Computer"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Carbone, P., G\u00e9vay, G.E., Hermann, G., Katsifodimos, A., Soto, J., Markl, V., and Haridi, S. (2017). Large-Scale Data Stream Processing Systems. Handbook of Big Data Technologies, Springer.","DOI":"10.1007\/978-3-319-49340-4_7"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.neucom.2017.01.078","article-title":"A survey on data preprocessing for data stream mining: Current status and future directions","volume":"239","author":"Krawczyk","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.future.2017.03.026","article-title":"Scalable real-time classification of data streams with concept drift","volume":"75","author":"Tennant","year":"2017","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Dastjerdi, A.V., Gupta, H., Calheiros, R.N., Ghosh, S.K., and Buyya, R. (arXiv, 2016). Fog computing: Principles, Architectures, and Applications, arXiv.","DOI":"10.1016\/B978-0-12-805395-9.00004-6"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. (2012, January 17). Fog computing and Its Role in the Internet of Things. Proceedings of the 1st Edition of the MCC Workshop on Mobile Cloud Computing, Helsinki, Finland.","DOI":"10.1145\/2342509.2342513"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Azimi, I., Anzanpour, A., Rahmani, A.M., Liljeberg, P., and Salakoski, T. (2016, January 18\u201319). Medical warning system based on Internet of Things using fog computing. Proceedings of the 2016 International Workshop on Big Data and Information Security (IWBIS), Jakarta, Indonesia.","DOI":"10.1109\/IWBIS.2016.7872884"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1109\/MIC.2017.26","article-title":"Challenges and Software Architecture for fog computing","volume":"21","author":"Hao","year":"2017","journal-title":"IEEE Int. Comput."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Cimorelli, F., Priscoli, F.D., Pietrabissa, A., Celsi, L.R., Suraci, V., and Zuccaro, L. (2016, January 21\u201324). A distributed load balancing algorithm for the control plane in software defined networking. Proceedings of the 24th Mediterranean Conference on Control and Automation (MED), Athens, Greece.","DOI":"10.1109\/MED.2016.7535946"},{"key":"ref_36","unstructured":"Solon, O. (2017, January 03). Glitch in Amazon Web Servers Causes Problems for Popular Sites. Available online: http:\/\/www.theguardian.com\/technology\/2017\/feb\/28\/amazon-web-server-crash-internet-problems."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Belli, L., Cirani, S., Ferrari, G., Melegari, L., and Picone, M. (2014, January 2\u20134). A Graph-Based cloud Architecture for big stream Real-Time Applications in the Internet of Things. Proceedings of the Advances in Service-Oriented and Cloud Computing: Workshops of ESOCC 2014, Manchester, UK. Revised Selected Papers.","DOI":"10.1007\/978-3-319-14886-1_10"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Albeanu, G., and Popentiu-Vladicescu, F. (2014, January 24\u201325). A reliable e-learning architecture based on fog-computing and smart devices. Proceedings of the 10th International Scientific Conference on eLearning and Software for Education, Bucharest, Romania.","DOI":"10.12753\/2066-026X-14-001"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Pecori, R., and Veltri, L. (2014, January 17\u201319). Trust-based routing for Kademlia in a sybil scenario. Proceedings of the 22nd International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, Croatia.","DOI":"10.1109\/SOFTCOM.2014.7039131"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.comnet.2015.11.010","article-title":"S-Kademlia: A trust and reputation method to mitigate a Sybil attack in Kademlia","volume":"94","author":"Pecori","year":"2016","journal-title":"Comput. Netw."},{"key":"ref_41","first-page":"18","article-title":"Of Needles and Haystacks: Building an Accurate Statewide Dropout Early Warning System in Wisconsin","volume":"7","author":"Knowles","year":"2015","journal-title":"J. Educ. Data Min."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Sani, L., Amoretti, M., Vicari, E., Mordonini, M., Pecori, R., Roli, A., Villani, M., Cagnoni, S., and Serra, R. (December, January 29). Efficient Search of Relevant Structures in Complex Systems. Proceedings of the AI*IA 2016 Advances in Artificial Intelligence: 15th International Conference of the Italian Association for Artificial Intelligence, Genova, Italy.","DOI":"10.1007\/978-3-319-49130-1_4"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1007\/s10489-014-0603-4","article-title":"An evolutionary algorithm for the discovery of rare class association rules in learning management systems","volume":"42","author":"Luna","year":"2015","journal-title":"Appl. Intell."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1111\/exsy.12135","article-title":"Early dropout prediction using data mining: A case study with high school students","volume":"33","author":"Cano","year":"2016","journal-title":"Expert Syst."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1080\/18756891.2015.1113748","article-title":"Improving Meta-learning for Algorithm Selection by Using Multi-label Classification: A Case of Study with Educational Data Sets","volume":"8","author":"Olmo","year":"2015","journal-title":"Int. J. Comput. Intell. Syst."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.ijhcs.2014.12.002","article-title":"Evaluation and selection of group recommendation strategies for collaborative searching of learning objects","volume":"76","author":"Zapata","year":"2015","journal-title":"Int. J. Hum. Comput. Stud."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1007\/s11517-015-1448-7","article-title":"Drowsiness detection using heart rate variability","volume":"54","author":"Vicente","year":"2016","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MNET.2016.7474338","article-title":"Mobile cellular big data: Linking cyberspace and the physical world with social ecology","volume":"30","author":"Xu","year":"2016","journal-title":"IEEE Netw."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10916-015-0338-8","article-title":"A Fatigue Measuring Protocol for Wireless Body Area Sensor Networks","volume":"39","author":"Akram","year":"2015","journal-title":"J. Med. Syst."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1016\/j.procs.2015.08.415","article-title":"E-learning Systems Based on cloud Computing: A Review","volume":"62","author":"Bahrami","year":"2015","journal-title":"Proc. Comput. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.pmcj.2015.05.005","article-title":"A survey on energy-aware security mechanisms","volume":"24","author":"Merlo","year":"2015","journal-title":"Perv. Mob. Comput."}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/10\/1\/4\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:49:55Z","timestamp":1760194195000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/10\/1\/4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,1,3]]},"references-count":51,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2018,1]]}},"alternative-id":["fi10010004"],"URL":"https:\/\/doi.org\/10.3390\/fi10010004","relation":{},"ISSN":["1999-5903"],"issn-type":[{"type":"electronic","value":"1999-5903"}],"subject":[],"published":{"date-parts":[[2018,1,3]]}}}