{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:40:43Z","timestamp":1760236843423,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,27]],"date-time":"2021-12-27T00:00:00Z","timestamp":1640563200000},"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>Nowadays, 5G networks are emerged and designed to integrate all the achievements of mobile and fixed communication networks, in which it can provide ultra-high data speeds and enable a broad range of new services with new cloud computing structures such as fog and edge. In spite of this, the complex nature of the system, especially with the varying network conditions, variety of possible mechanisms, hardware, and protocols, makes communication between these technologies challenging. To this end, in this paper, we proposed a new distributed and fog (DD-fog) framework for software development, in which fog and mobile edge computing (MEC) technologies and microservices approach are jointly considered. More specifically, based on the computational and network capabilities, this framework provides a microservices migration between fog structures and elements, in which user query statistics in each of the fog structures are considered. In addition, a new modern solution was proposed for IoT-based application development and deployment, which provides new time constraint services like a tactile internet, autonomous vehicles, etc. Moreover, to maintain quality service delivery services, two different algorithms have been developed to pick load points in the search mechanism for congestion of users and find the fog migration node. Finally, simulation results proved that the proposed framework could reduce the execution time of the microservice function by up to 70% by deploying the rational allocation of resources reasonably.<\/jats:p>","DOI":"10.3390\/fi14010013","type":"journal-article","created":{"date-parts":[[2021,12,28]],"date-time":"2021-12-28T01:18:15Z","timestamp":1640654295000},"page":"13","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["DD-FoG: Intelligent Distributed Dynamic FoG Computing Framework"],"prefix":"10.3390","volume":"14","author":[{"given":"Volkov","family":"Artem","sequence":"first","affiliation":[{"name":"Department of Telecommunication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 Saint Petersburg, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kovalenko","family":"Vadim","sequence":"additional","affiliation":[{"name":"Department of Telecommunication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 Saint Petersburg, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7154-2307","authenticated-orcid":false,"given":"Ibrahim A.","family":"Elgendy","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Computers and Information, Menoufia University, Shibin el Kom 32511, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0213-8145","authenticated-orcid":false,"given":"Ammar","family":"Muthanna","sequence":"additional","affiliation":[{"name":"Department of Telecommunication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 Saint Petersburg, Russia"},{"name":"Department of Computer Science, RUDN University, Peoples\u2019 Friendship University of Russia, 6 Miklukho-Maklaya Str., 117198 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrey","family":"Koucheryavy","sequence":"additional","affiliation":[{"name":"Department of Telecommunication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 Saint Petersburg, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,27]]},"reference":[{"key":"ref_1","first-page":"22","article-title":"A Comprehensive Survey on Core Technologies and Services for 5G Security: Taxonomies, Issues, and Solutions","volume":"11","author":"Park","year":"2021","journal-title":"Hum.-Centric Comput. Inf. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Khayyat, M., Alshahrani, A., Alharbi, S., Elgendy, I., Paramonov, A., and Koucheryavy, A. (2020). Multilevel service-provisioning-based autonomous vehicle applications. Sustainability, 12.","DOI":"10.3390\/su12062497"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Alshahrani, A., Elgendy, I.A., Muthanna, A., Alghamdi, A.M., and Alshamrani, A. (2020). Efficient multi-player computation offloading for VR edge-cloud computing systems. Appl. Sci., 10.","DOI":"10.3390\/app10165515"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.future.2019.02.056","article-title":"Evaluation and efficiency comparison of evolutionary algorithms for service placement optimization in fog architectures","volume":"97","author":"Guerrero","year":"2019","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3341145","article-title":"Machine learning methods for reliable resource provisioning in edge-cloud computing: A survey","volume":"52","author":"Duc","year":"2019","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"ref_6","unstructured":"Rec, I. (2020). ITU-R M. 2083-0. IMT Vision\u2014Framework and Overall Objectives of the Future Development of IMT, International Telecommunication Union."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1504\/IJSTM.2020.106744","article-title":"Provisioning big data applications as services on containerised cloud: A microservices-based approach","volume":"26","author":"Gao","year":"2020","journal-title":"Int. J. Serv. Technol. Manag."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1134\/S0361768820080083","article-title":"Analytic Study of Containerizing Stateful Stream Processing as Microservice to Support Digital Twins in Fog Computing","volume":"46","author":"Alaasam","year":"2020","journal-title":"Program. Comput. Softw."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"17172","DOI":"10.1109\/JIOT.2021.3077992","article-title":"Optimizing the Response Time in SDN-Fog Environments for Time-Strict IoT Applications","volume":"8","author":"Herrera","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Al-Ansi, A., Al-Ansi, A.M., Muthanna, A., Elgendy, I.A., and Koucheryavy, A. (2021). Survey on Intelligence Edge Computing in 6G: Characteristics, Challenges, Potential Use Cases, and Market Drivers. Future Internet, 13.","DOI":"10.3390\/fi13050118"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"8119","DOI":"10.1109\/JIOT.2020.3042433","article-title":"Secure and Optimized Load Balancing for Multitier IoT and Edge-Cloud Computing Systems","volume":"8","author":"Zhang","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2410","DOI":"10.1109\/TNSM.2020.3020249","article-title":"Efficient and secure multi-user multi-task computation offloading for mobile-edge computing in mobile IoT networks","volume":"17","author":"Elgendy","year":"2020","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/MCOM.2017.1600863","article-title":"Collaborative mobile edge computing in 5G networks: New paradigms, scenarios, and challenges","volume":"55","author":"Tran","year":"2017","journal-title":"IEEE Commun. Mag."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Li, Y., Anh, N.T., Nooh, A.S., Ra, K., and Jo, M. (2018, January 24\u201327). Dynamic mobile cloudlet clustering for fog computing. Proceedings of the 2018 international conference on electronics, information, and communication (iceic), Honolulu, HI, USA.","DOI":"10.23919\/ELINFOCOM.2018.8330676"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1109\/CC.2016.7445510","article-title":"Fog computing dynamic load balancing mechanism based on graph repartitioning","volume":"13","author":"Ningning","year":"2016","journal-title":"China Commun."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Volkov, A., Khakimov, A., Muthanna, A., Kirichek, R., Vladyko, A., and Koucheryavy, A. (2017, January 25\u201329). Interaction of the IoT traffic generated by a smart city segment with SDN core network. Proceedings of the International Conference on Wired\/Wireless Internet Communication, Moscow, Russia.","DOI":"10.1007\/978-3-319-61382-6_10"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Volkov, A., Muhathanna, A., Pirmagomedov, R., and Kirichek, R. (2017, January 25\u201329). SDN approach to control internet of thing medical applications traffic. Proceedings of the International Conference on Distributed Computer and Communication Networks, Moscow, Russia.","DOI":"10.1007\/978-3-319-66836-9_39"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Volkov, A., Proshutinskiy, K., Adam, A.B., Ateya, A.A., Muthanna, A., and Koucheryavy, A. (2019, January 23\u201327). SDN load prediction algorithm based on artificial intelligence. Proceedings of the International Conference on Distributed Computer and Communication Networks, Moscow, Russia.","DOI":"10.1007\/978-3-030-36625-4_3"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Muthanna, A., Volkov, A., Khakimov, A., Muhizi, S., Kirichek, R., and Koucheryavy, A. (2018, January 5\u20139). Framework of QoS management for time constraint services with requested network parameters based on SDN\/NFV infrastructure. Proceedings of the 10th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), Moscow, Russia.","DOI":"10.1109\/ICUMT.2018.8631274"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1049\/cmu2.12145","article-title":"Cross-layer multipath congestion control, routing and scheduling design in ad hoc wireless networks","volume":"15","author":"Aljubayri","year":"2021","journal-title":"IET Commun."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Ibrar, M., Wang, L., Muntean, G.M., Shah, N., Akbar, A., and Qureshi, K.I. (2021). SOSW: Scalable and optimal nearsighted location selection for fog node deployment and routing in SDN-based wireless networks for IoT systems. Ann. Telecommun.","DOI":"10.1007\/s12243-021-00845-z"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Bratton, D., and Kennedy, J. (2007, January 1\u20135). Defining a standard for particle swarm optimization. Proceedings of the 2007 IEEE swarm intelligence symposium, Honolulu, HI, USA.","DOI":"10.1109\/SIS.2007.368035"}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/14\/1\/13\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:53:54Z","timestamp":1760169234000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/14\/1\/13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,27]]},"references-count":22,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["fi14010013"],"URL":"https:\/\/doi.org\/10.3390\/fi14010013","relation":{},"ISSN":["1999-5903"],"issn-type":[{"type":"electronic","value":"1999-5903"}],"subject":[],"published":{"date-parts":[[2021,12,27]]}}}