{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T11:10:41Z","timestamp":1790161841197,"version":"4.1.0"},"reference-count":41,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004686","name":"King Faisal University","doi-asserted-by":"publisher","award":["KFU264620"],"award-info":[{"award-number":["KFU264620"]}],"id":[{"id":"10.13039\/501100004686","id-type":"DOI","asserted-by":"publisher"}]},{"award":["KFU264620"],"award-info":[{"award-number":["KFU264620"]}],"id":[{"id":"https:\/\/ror.org\/00dn43547","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Mission-critical Internet of Things (MC-IoT) applications, such as remote surgery, autonomous drone swarms, industrial safety monitoring, etc., have ultra-stringent requirements for reliability (99.999%), latency (sub-millisecond) and inter-slice isolation that require dedicated network slices with carefully orchestrated virtual network function (VNF) chains. While prior solutions to VNF orchestration seek to merge often conflicting requirements into a single objective with a scalar reward, or to statically configure the allocation of resources that fail to adjust to dynamic mission-critical workloads, both strategies are inadequate. In this paper, we propose a network slicing-aware NFV orchestration framework called SliceNFV, which uses multi-objective deep reinforcement learning (MO-DRL) to optimize the resource allocation of VNFs per slice, the inter-slice isolation enforcement, and the efficiency of the cross-slice resource sharing. It is formulated as the orchestration problem as a multi-objective constrained Markov decision process (MO-CMDP), and a novel Pareto-Conditioned Proximal Policy Optimization (PC-PPO) algorithm is developed to learn a portfolio of non-dominated orchestration policies, allowing the operator to choose operating points along the reliability\u2013efficiency frontier without retraining. A temporal convolutional network (TCN) is a scalable network that uses a predictive slice-aware VNF scaling mechanism to forecast the arrival of mission-critical events and scale resources in advance to avoid SLA breaches. The results of extensive simulation-based assessment across three progressive scenarios\u2014steady-state operation, mission-critical demand surge and infrastructure degradation\u2014highlight that SliceNFV offers 99.998% reliability when operating under an SLA violation rate of 0.08%, whereas all other baselines exceed their corresponding SLAs; in addition, SliceNFV significantly improves Pareto hypervolume by 36.4% over traditional multi-objective approaches while increasing infrastructure utilization to 76%.<\/jats:p>","DOI":"10.3390\/s26196023","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T10:17:26Z","timestamp":1790158646000},"page":"6023","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Network-Slice-AwareVNF Orchestration for Mission-Critical IoT in 6G Networks: A Multi-Objective Deep Reinforcement Learning Approach"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9313-4643","authenticated-orcid":false,"given":"Abdulrahman K.","family":"Alnaim","sequence":"first","affiliation":[{"name":"Department of Management Information Systems, College of Business Administration, King Faisal University, Alahsa 31982, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1394-7159","authenticated-orcid":false,"given":"Ahmed M.","family":"Alwakeel","sequence":"additional","affiliation":[{"name":"Faculty of Computers & Information Technology, University of Tabuk, Tabuk 71491, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1109\/MVT.2025.3532887","article-title":"The ITU vision and framework for 6G: Scenarios, capabilities, and enablers","volume":"20","author":"Liu","year":"2025","journal-title":"IEEE Veh. 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