{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T00:02:24Z","timestamp":1784851344641,"version":"3.55.0"},"reference-count":31,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T00:00:00Z","timestamp":1635465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Sen. Netw."],"published-print":{"date-parts":[[2022,5,31]]},"abstract":"<jats:p>We are embracing an era of Internet of Things (IoT). The latency brought by unstable wireless networks caused by limited resources of IoT devices seriously impacts the quality of services of users, particularly the service delay they experienced. Mobile Edge Computing (MEC) technology provides promising solutions to delay-sensitive IoT applications, where cloudlets (edge servers) are co-located with wireless access points in the proximity of IoT devices. The service response latency for IoT applications can be significantly shortened due to that their data processing can be performed in a local MEC network. Meanwhile, most IoT applications usually impose Service Function Chain (SFC) enforcement on their data transmission, where each data packet from its source gateway of an IoT device to the destination (a cloudlet) of the IoT application must pass through each Virtual Network Function (VNF) in the SFC in an MEC network. However, little attention has been paid on such a service provisioning of multi-source IoT applications in an MEC network with SFC enforcement.<\/jats:p>\n          <jats:p>In this article, we study service provisioning in an MEC network for multi-source IoT applications with SFC requirements and aiming at minimizing the cost of such service provisioning, where each IoT application has multiple data streams from different sources to be uploaded to a location (cloudlet) in the MEC network for aggregation, processing, and storage purposes. To this end, we first formulate two novel optimization problems: the cost minimization problem of service provisioning for a single multi-source IoT application, and the service provisioning problem for a set of multi-source IoT applications, respectively, and show that both problems are NP-hard. Second, we propose a service provisioning framework in the MEC network for multi-source IoT applications that consists of uploading stream data from multiple sources of the IoT application to the MEC network, data stream aggregation and routing through the VNF instance placement and sharing, and workload balancing among cloudlets. Third, we devise an efficient algorithm for the cost minimization problem built upon the proposed service provisioning framework, and further extend the solution for the service provisioning problem of a set of multi-source IoT applications. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms are promising.<\/jats:p>","DOI":"10.1145\/3484200","type":"journal-article","created":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T15:01:59Z","timestamp":1635519719000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Service Provisioning for Multi-source IoT Applications in Mobile Edge Computing"],"prefix":"10.1145","volume":"18","author":[{"given":"Jing","family":"Li","sequence":"first","affiliation":[{"name":"Australian National University, Canberra, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weifa","family":"Liang","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong, P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zichuan","family":"Xu","sequence":"additional","affiliation":[{"name":"Dalian University of Technology, Liaoning, P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohua","family":"Jia","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong, P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wanlei","family":"Zhou","sequence":"additional","affiliation":[{"name":"City University of Macau, Macao, P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,10,29]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"Georgia Tech. 2019. GT-ITM. 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Service provisioning for IoT applications with multiple sources in mobile edge computing. In Proceedings of the IEEE 45th Conference on Local Computer Networks (LCN\u201920). IEEE, 42\u201353."},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS47924.2020.00072"},{"key":"e_1_3_1_19_2","article-title":"Data collection maximization in IoT-sensor networks via an energy-constrained UAV","author":"Li Yuchen","year":"2021","unstructured":"Yuchen Li, Weifa Liang, Wenzheng Xu, Zichuan Xu, Xiaohua Jia, Yinlong Xu, and Haibin Kan. 2021. Data collection maximization in IoT-sensor networks via an energy-constrained UAV. IEEE Trans. Mobile Comput. (2021). https:\/\/doi.org\/10.1109\/TMC.2021.3084972","journal-title":"IEEE Trans. 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Throughput maximization for online request admissions in mobile cloudlets. In Proceedings of the 38th Annual IEEE Conference on Local Computer Networks. 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