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Syst."],"published-print":{"date-parts":[[2026,9,30]]},"abstract":"<jats:p>Renowned for their lightweight and portability, containers are increasingly deployed in edge computing to deliver low-latency and privacy-preserving computing services for industrial real-time systems. While layer reuse can potentially improve the execution efficiency of container-dependent tasks, the existing work suffers from two issues: (1) inefficient disk space utilization, which compromises image pull efficiency and reuse utility, and (2) inadequate consideration of resource capacity, leading to practical limitations. This article addresses the container-dependent task scheduling problem in edge computing-assisted industrial real-time systems by introducing a novel Layer Reuse-based Collaborative Scheduling (LRCS) framework. First, to ensure practical applicability, we comprehensively consider resource capacities and the cost terms of the task completion time. Second, a framework that collaborates scheduling and execution nodes in a weakly coupled manner is proposed. At the execution nodes, LRCS maximizes disk utilization by evicting layers only when disk space is insufficient. The eviction is modeled as a 0-1 knapsack problem, where dynamic layer value assessment enhances the reuse rate. At the scheduling node, LRCS formulates container-dependent task scheduling as a multidimensional online bin-packing problem. A value-based learning algorithm optimizes long-term processing efficiency by adjusting the scheduling order of online tasks. Experimental validation on a testbed using real device data and comparisons with state-of-the-art layer reuse-based algorithms demonstrate that the proposed algorithm outperforms all baselines.<\/jats:p>","DOI":"10.1145\/3779131","type":"journal-article","created":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T12:01:37Z","timestamp":1764590497000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Layer-Reused Collaborative Scheduling for Container-Dependent Tasks in Industrial Real-Time Systems"],"prefix":"10.1145","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1729-3383","authenticated-orcid":false,"given":"Haotong","family":"Zhang","sequence":"first","affiliation":[{"name":"South China University of Technology","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6876-1795","authenticated-orcid":false,"given":"Weiwei","family":"Lin","sequence":"additional","affiliation":[{"name":"South China University of Technology","place":["Guangzhou, China"]},{"name":"Pengcheng Laboratory","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8042-764X","authenticated-orcid":false,"given":"Yuebin","family":"Huang","sequence":"additional","affiliation":[{"name":"South China University of Technology","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-0626-6949","authenticated-orcid":false,"given":"Haijie","family":"Wu","sequence":"additional","affiliation":[{"name":"South China University of Technology","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5546-8995","authenticated-orcid":false,"given":"Chenjieting","family":"Wu","sequence":"additional","affiliation":[{"name":"South China University of Technology","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5224-4048","authenticated-orcid":false,"given":"Keqin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science, State University of New York at New Paltz","place":["New Paltz, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,8,26]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3359297"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2024.3396161"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2024.3377899"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2023.3324704"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3246176"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3266643"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2023.3301718"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2023.3264005"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3214199"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2023.3290023"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3246539"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2023.3320752"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3142157"},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/3445814.3446757"},{"key":"e_1_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3119181"},{"key":"e_1_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2024.3399651"},{"issue":"11","key":"e_1_3_1_18_2","article-title":"Dynamic microservice deployment and offloading for things\u2013edge\u2013cloud computing","volume":"11","author":"Tian Xianzhong","year":"2024","unstructured":"Xianzhong Tian, Huixiao Meng, Yifan Shen, Junxian Zhang, Yuzhe Chen, and Yanjun Li. 2024. 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