{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:44:07Z","timestamp":1760363047113,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,9]],"date-time":"2021-04-09T00:00:00Z","timestamp":1617926400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As service latency and core network load relates to performance issues in the conventional cloud-based computing environment, the fog computing system has gained a lot of interest. However, since the load can be concentrated on specific fog computing nodes because of spatial and temporal service characteristics, performance degradation can occur, resulting in quality of service (QoS) degradation, especially for delay-sensitive services. Therefore, this paper proposes a prioritized task distribution scheme, which considers static as well as opportunistic fog computing nodes according to their mobility feature. Based on the requirements of offloaded tasks, the proposed scheme supports delay sensitive task processing at the static fog node and delay in-sensitive tasks by means of opportunistic fog nodes for task distribution. To assess the performance of the proposed scheme, we develop an analytic model for the service response delay. Extensive simulation results are given to validate the analytic model and to show the performance of the proposed scheme, compared to the conventional schemes in terms of service response delay and outage probability.<\/jats:p>","DOI":"10.3390\/s21082635","type":"journal-article","created":{"date-parts":[[2021,4,12]],"date-time":"2021-04-12T05:52:00Z","timestamp":1618206720000},"page":"2635","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Prioritized Task Distribution Considering Opportunistic Fog Computing Nodes"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5247-0296","authenticated-orcid":false,"given":"Yeunwoong","family":"Kyung","sequence":"first","affiliation":[{"name":"School of Computer Engineering, Hanshin University, Osan 18101, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1109\/MCE.2017.2776462","article-title":"Building a sustainable Internet of Things: Energy-efficient routing using low-power sensors will meet the need","volume":"7","author":"Roy","year":"2018","journal-title":"IEEE Consum. Electron. Mag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1109\/TNSM.2018.2888481","article-title":"QoS-Aware Fog Resource Provisioning and Mobile Device Power Control in IoT Networks","volume":"16","author":"Yao","year":"2019","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3941","DOI":"10.1109\/TVT.2016.2550105","article-title":"Deve: Offloading Delay-Tolerant Data Traffic to Connected Vehicle Networks","volume":"65","author":"Si","year":"2016","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"9073","DOI":"10.1109\/TVT.2018.2865211","article-title":"Delay-Tolerant Data Traffic to Software-Defined Vehicular Networks with Mobile Edge Computing in Smart City","volume":"67","author":"Li","year":"2018","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1166","DOI":"10.1109\/SURV.2011.081611.00102","article-title":"From delay-tolerant networks to vehicular delay-tolerant networks","volume":"14","author":"Pereira","year":"2012","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/MCC.2015.23","article-title":"Principles for engineering IoT cloud systems","volume":"2","author":"Truong","year":"2015","journal-title":"IEEE Cloud Comput."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"25445","DOI":"10.1109\/ACCESS.2017.2766923","article-title":"A framework of fog computing: Architecture, challenges, and optimization","volume":"5","author":"Liu","year":"2017","journal-title":"IEEE Access"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1109\/MC.2016.245","article-title":"Fog Computing: Helping the Internet of Things Realize Its Potential","volume":"49","author":"Dastjerdi","year":"2016","journal-title":"IEEE Comput."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1109\/TNSE.2018.2852762","article-title":"Towards Workload Balancing in Fog Computing Empowered IoT","volume":"7","author":"Fan","year":"2018","journal-title":"IEEE Trans. Netw. Sci. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Iorga, M., Feldman, L., Barton, R., Martin, M.J., Goren, N., and Mahmoudi, C. (2018). Fog Computing Conceptual Model.","DOI":"10.6028\/NIST.SP.500-325"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LCOMM.2017.2690678","article-title":"Latency Aware Workload Offloading in the Cloudlet Network","volume":"21","author":"Sun","year":"2017","journal-title":"IEEE Commun. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"5031","DOI":"10.1109\/TVT.2019.2904244","article-title":"Collaborative Cloud and Edge Computing for Latency Minimization","volume":"68","author":"Ren","year":"2019","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Yousefpour, A., Ishigaki, G., and Jue, J.P. (2017, January 25\u201330). Fog Computing: Towards Minimizing Delay in the Internet of Things. Proceedings of the 2017 IEEE 1st International Conference on Edge Computing, Honolulu, HI, USA.","DOI":"10.1109\/IEEE.EDGE.2017.12"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Yi, S., Li, C., and Li, Q. (2015, January 21). A Survey of Fog Computing: Concepts, Applications and Issues. Proceedings of the ACM Mobidata, Hangzhou, China.","DOI":"10.1145\/2757384.2757397"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/j.future.2020.02.001","article-title":"Achieving Security Scalability and Flexibility Using Fog-Based Context-Aware Access Control","volume":"107","author":"Kayes","year":"2020","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Kayes, A.S.M., Kalaria, R., Sarker, I.H., Islam, M.S., Watters, P.A., Ng, A., Hammoudeh, M., Badsha, S., and Kumara, I. (2020). A Survey of Context-Aware Access Control Mechanisms for Cloud and Fog Networks: Taxonomy and Open Research Issues. Sensors, 20.","DOI":"10.3390\/s20092464"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4150","DOI":"10.1109\/JIOT.2018.2875520","article-title":"Folo: Latency and Quality Optimized Task Allocation in Vehicular Fog Computing","volume":"6","author":"Zhu","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"8897","DOI":"10.1109\/JIOT.2019.2924182","article-title":"Opportunistic Fog for IoT: Challenges and Opportunities","volume":"6","author":"Fernando","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1109\/MNET.2019.1800309","article-title":"Mobile Edge Computing-Enabled Internet of Vehicles: Toward Energy-Efficient Scheduling","volume":"33","author":"Ning","year":"2019","journal-title":"IEEE Netw."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"4961","DOI":"10.1109\/JIOT.2020.2972041","article-title":"Dependency-Aware Task Scheduling in Vehicular Edge Computing","volume":"7","author":"Liu","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3113","DOI":"10.1109\/TVT.2019.2894851","article-title":"Computation Resource Allocation and Task Assignment Optimization in Vehicular Fog Computing: A Contract-Matching Approach","volume":"68","author":"Zhou","year":"2019","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"4568","DOI":"10.1109\/TII.2018.2816590","article-title":"Offloading in Internet of Vehicles: A Fog-enabled Real-time Traffic Management System","volume":"14","author":"Wang","year":"2018","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1090","DOI":"10.3390\/s16071090","article-title":"Distributed Task Offloading in Heterogeneous Vehicular Crowd Sensing","volume":"16","author":"Liu","year":"2016","journal-title":"Sensors"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"43356","DOI":"10.1109\/ACCESS.2019.2908263","article-title":"Mobility-Aware Task Offloading and Migration Schemes in Fog Computing Networks","volume":"7","author":"Wang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2015\/875371","article-title":"Pseudonyms in IPv6 ITS Communications: Use of Pseudonyms, Performance Degradation, and Optimal Pseudonyms Change","volume":"11","author":"Lee","year":"2015","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3903","DOI":"10.1109\/TVT.2013.2245928","article-title":"Mobility-Aware Call Admission Control Algorithm with Handoff Queue in Mobile Hotspots","volume":"62","author":"Kim","year":"2013","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_27","unstructured":"Kleinrock, L. (1975). Queueing Systems: Theory, Wiley."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1145\/3314212.3314216","article-title":"Thoughts on Load Distribution and the Role of Programmable Switches","volume":"49","author":"McCauley","year":"2019","journal-title":"ACM SIGCOMM Comput. Commun. Rev."},{"key":"ref_29","unstructured":"Zhao, L., Yang, K., Tan, Z., Li, X., Sharma, S., and Liu, Z. (2020). A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading. IEEE Trans. Intell. Transp. Syst., 1\u201311."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/8\/2635\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:26:34Z","timestamp":1760361994000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/8\/2635"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,9]]},"references-count":29,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2021,4]]}},"alternative-id":["s21082635"],"URL":"https:\/\/doi.org\/10.3390\/s21082635","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2021,4,9]]}}}