{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T11:19:16Z","timestamp":1787224756974,"version":"build-2736575974"},"reference-count":34,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,7,28]],"date-time":"2022-07-28T00:00:00Z","timestamp":1658966400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000830","name":"NATO Science for Peace and Security","doi-asserted-by":"publisher","award":["SPS G5428"],"award-info":[{"award-number":["SPS G5428"]}],"id":[{"id":"10.13039\/501100000830","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000830","name":"NATO Science for Peace and Security","doi-asserted-by":"publisher","award":["OIA-1757207"],"award-info":[{"award-number":["OIA-1757207"]}],"id":[{"id":"10.13039\/501100000830","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"US National Science Foundation","doi-asserted-by":"publisher","award":["SPS G5428"],"award-info":[{"award-number":["SPS G5428"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"US National Science Foundation","doi-asserted-by":"publisher","award":["OIA-1757207"],"award-info":[{"award-number":["OIA-1757207"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Recently, a multi-agent based network automation architecture has been proposed. The architecture is named multi-agent based network automation of the network management system (MANA-NMS). The architectural framework introduced atomized network functions (ANFs). ANFs should be autonomous, atomic, and intelligent agents. Such agents should be implemented as an independent decision element, using machine\/deep learning (ML\/DL) as an internal cognitive and reasoning part. Using these atomic and intelligent agents as a building block, a MANA-NMS can be composed using the appropriate functions. As a continuation toward implementation of the architecture MANA-NMS, this paper presents a network traffic prediction agent (NTPA) and a network traffic classification agent (NTCA) for a network traffic management system. First, an NTPA is designed and implemented using DL algorithms, i.e., long short-term memory (LSTM), gated recurrent unit (GRU), multilayer perceptrons (MLPs), and convolutional neural network (CNN) algorithms as a reasoning and cognitive part of the agent. Similarly, an NTCA is designed using decision tree (DT), K-nearest neighbors (K-NN), support vector machine (SVM), and naive Bayes (NB) as a cognitive component in the agent design. We then measure the NTPA prediction accuracy, training latency, prediction latency, and computational resource consumption. The results indicate that the LSTM-based NTPA outperforms compared to GRU, MLP, and CNN-based NTPA in terms of prediction accuracy, and prediction latency. We also evaluate the accuracy of the classifier, training latency, classification latency, and computational resource consumption of NTCA using the ML models. The performance evaluation shows that the DT-based NTCA performs the best.<\/jats:p>","DOI":"10.3390\/fi14080230","type":"journal-article","created":{"date-parts":[[2022,7,28]],"date-time":"2022-07-28T20:49:28Z","timestamp":1659041368000},"page":"230","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Multi-Agent-Based Traffic Prediction and Traffic Classification for Autonomic Network Management Systems for Future Networks"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9062-8499","authenticated-orcid":false,"given":"Sisay Tadesse","family":"Arzo","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87106, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1491-2081","authenticated-orcid":false,"given":"Zeinab","family":"Akhavan","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87106, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mona","family":"Esmaeili","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87106, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Devetsikiotis","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87106, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2439-277X","authenticated-orcid":false,"given":"Fabrizio","family":"Granelli","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Computer Science (DISI), University of Trento, 38123 Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/SURV.2009.090303","article-title":"Towards autonomic network management: An analysis of current and future research directions","volume":"11","author":"Samaan","year":"2009","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1109\/MIC.2017.3481338","article-title":"Autonomic networking: Architecture design and standardization","volume":"21","author":"Long","year":"2017","journal-title":"IEEE Internet Comput."},{"key":"ref_3","unstructured":"Hexa-X (2022, June 22). D5.1\u2014A Flagship for B5G\/6G Vision and Intelligent Fabric of Technology Enablers Connecting Human, Physical, and Digital Worlds. Available online: https:\/\/hexa-x.eu\/wp-content\/uploads\/2022\/01\/Hexa-X_D5.1_full_version_v1.0.pdf."},{"key":"ref_4","unstructured":"(2022, June 22). D5.1\u2014AI-dRiven Communication Computation Co-Design: Gap Analysis and Blueprint. Available online: https:\/\/hexa-x.eu\/wp-content\/uploads\/2021\/09\/Hexa-X_D4.1_slideset.pdf."},{"key":"ref_5","unstructured":"(2022, June 22). ETSI, Network Functions Virtualisation (nfv); Terminology for Main Concepts in nfv., ETSI Industry Specification Group (ISG), Gs Nfv 003-V1.4.1, Volume 1. Available online: http:\/\/www.etsi.org\/standards-search."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1109\/SURV.2011.042711.00078","article-title":"A survey of autonomic network architectures and evaluation criteria","volume":"14","author":"Movahedi","year":"2012","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Behringer, M., Dutta, A., Hertoghs, Y., and Bjarnason, S. (2014, January 5\u20139). Autonomic networking-from theory to practice. Proceedings of the IEEE Network Operations and Management Symposium (NOMS), Krakow, Poland.","DOI":"10.1109\/NOMS.2014.6838294"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1109\/TNSM.2016.2598420","article-title":"Resource allocation in nfv: A comprehensive survey","volume":"13","author":"Herrera","year":"2016","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1311","DOI":"10.1109\/TNET.2020.2979667","article-title":"Multi-resource allocation for network slicing","volume":"28","author":"Fossati","year":"2020","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Berrayana, W., Youssef, H., and Pujolle, G. (2012, January 27\u201331). A generic cross-layer architecture for autonomic network management with network wide knowledge. Proceedings of the 8th International Wireless Communications and Mobile Computing Conference (IWCMC), Limassol, Cyprus.","DOI":"10.1109\/IWCMC.2012.6314182"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/MVT.2014.2380633","article-title":"Customizable autonomic network management: Integrating autonomic network management and software-defined networking","volume":"10","author":"Tsagkaris","year":"2015","journal-title":"IEEE Veh. Technol. Mag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3595","DOI":"10.1109\/TNSM.2021.3059752","article-title":"Multi-agent based autonomic network management architecture","volume":"18","author":"Arzo","year":"2021","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"12 021","DOI":"10.1109\/JIOT.2021.3075901","article-title":"A theoretical discussion and survey of network automation for iot: Challenges and opportunity","volume":"8","author":"Arzo","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_14","first-page":"1573","article-title":"Msn: A playground framework for design and evaluation of microservices-based sdn controller","volume":"30","author":"Arzo","year":"2021","journal-title":"J. Netw. Syst. Manag."},{"key":"ref_15","unstructured":"Foundation, O.N. (2022, June 22). Open Network Operating System (onos). Available online: https:\/\/docs.onosproject.org\/."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"16548","DOI":"10.1109\/JIOT.2021.3074830","article-title":"Agents-Based Algorithm for a Distributed Information System in Internet of Things","volume":"8","author":"Forestiero","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Serugunda, C.N., Arzo, S.T., Granelli, F., Bassoli, R., Devetsikiotis, M., and Fitzek, F.H. (2021, January 7\u201311). Autonomous network traffic classifier agent for autonomic network management system. Proceedings of the IEEE Global Communications Conference (GLOBECOM), Madrid, Spain.","DOI":"10.1109\/GLOBECOM46510.2021.9685568"},{"key":"ref_18","unstructured":"Dowell, M.L., and Bonnell, R.D. (1991, January 10\u201312). Learning for distributed artificial intelligence systems. Proceedings of the The Twenty-Third Southeastern Symposium on System Theory, Columbia, SC, USA."},{"key":"ref_19","unstructured":"Shaw, M.J., Harrow, B., and Herman, S. (1991, January 8\u201311). Distributed artificial intelligence for multiagent problem solving and group learning. Proceedings of the Twenty-Fourth Annual Hawaii International Conference on System Sciences, Kauai, HI, USA."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"28573","DOI":"10.1109\/ACCESS.2018.2831228","article-title":"Multi-agent systems: A survey","volume":"6","author":"Dorri","year":"2018","journal-title":"IEEE Access"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1109\/TCDS.2018.2840971","article-title":"Decision making in multi agent systems: A survey","volume":"10","author":"Rizk","year":"2018","journal-title":"IEEE Trans. Cogn. Dev. Syst."},{"key":"ref_22","unstructured":"Hexa-X (2022, June 22). D1.2\u2014Expanded 6G Vision, Use Cases and Societal Values\u2014Including Aspects of Sustainability, Security and Spectrum. Available online: https:\/\/hexa-x.eu\/wp-content\/uploads\/2021\/05\/Hexa-X_D1.2.pdf."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Kim, H., Lee, D., Jeong, S., Choi, H., Yoo, J., and Hong, J.W. (2019, January 24\u201328). Machine learning-based method for prediction of virtual network function resource demands. Proceedings of the IEEE Conference on Network Softwarization (NetSoft), Paris, France.","DOI":"10.1109\/NETSOFT.2019.8806687"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Yang, S., Yu, X., and Zhou, Y. (2020, January 12\u201314). Lstm and gru neural network performance comparison study: Taking yelp review dataset as an example. Proceedings of the International Workshop on Electronic Communication and Artificial Intelligence (IWECAI), Shanghai, China.","DOI":"10.1109\/IWECAI50956.2020.00027"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ramakrishnan, N., and Soni, T. (2018, January 17\u201320). Network traffic prediction using recurrent neural networks. Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA), Orlando, FL, USA.","DOI":"10.1109\/ICMLA.2018.00035"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Wang, W., Bai, Y., Yu, C., Gu, Y., Feng, P., Wang, X., and Wang, R. (2018, January 23\u201327). A network traffic flow prediction with deep learning approach for large-scale metropolitan area network. Proceedings of the IEEE\/IFIP Network Operations and Management Symposium, Taipei, Taiwan.","DOI":"10.1109\/NOMS.2018.8406252"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Neagoe, V.-E., Ciotec, A.-D., and Cucu, G.-S. (2018, January 14\u201316). Deep convolutional neural networks versus multilayer perceptron for financial prediction. Proceedings of the International Conference on Communications (COMM), Bucharest, Romania.","DOI":"10.1109\/ICComm.2018.8484751"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Navada, A., Ansari, A.N., Patil, S., and Sonkamble, B.A. (2011, January 27\u201328). Overview of Use of Decision Tree Algorithms in Machine Learning. Proceedings of the 2011 IEEE Control and System Graduate Research Colloquium, Shah Alam, Malaysia.","DOI":"10.1109\/ICSGRC.2011.5991826"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Ray, S. (2019). A Quick Review of Machine Learning Algorithms. Int. Conf. Mach. Learn., 35\u201339.","DOI":"10.1109\/COMITCon.2019.8862451"},{"key":"ref_30","unstructured":"Huang, J., Lu, J., and Ling, C.X. (2003, January 22\u201322). Comparing naive Bayes, decision trees, and SVM with AUC and accuracy. Proceedings of the Third IEEE International Conference on Data Mining, Melbourne, FL, USA."},{"key":"ref_31","unstructured":"(2021, January 05). Support Vector Machine-Mitosis Technologies. Available online: https:\/\/www.mitosistech.com\/support-vector-machine\/."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Alfred, R., Lim, Y., Ibrahim, A.A.A., and Anthony, P. (2019). A review on agent communication language. Computational Science and Technology, Springer.","DOI":"10.1007\/978-981-13-2622-6"},{"key":"ref_33","unstructured":"(2022, June 23). O. S. de Informac\u00edon Internet S.L. Revision d0b241de., \u201cosbrain-0.6.5\u201d. Available online: https:\/\/osbrain.readthedocs.io\/en\/stable\/."},{"key":"ref_34","unstructured":"ZeroMQ (2022, June 22). An Open-Source Universal Messaging Library. Available online: https:\/\/zeromq.org."}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/14\/8\/230\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:58:05Z","timestamp":1760140685000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/14\/8\/230"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,28]]},"references-count":34,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["fi14080230"],"URL":"https:\/\/doi.org\/10.3390\/fi14080230","relation":{},"ISSN":["1999-5903"],"issn-type":[{"value":"1999-5903","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,28]]}}}