Towards Effective Communication Management in Cooperative Robotic-enabled Healthcare Systems: Open Challenges and Future Research Directions

dc.contributor.authorAdil, Muhammad
dc.contributor.authorKhan, Muhammad Khurram
dc.contributor.authorAli, Aitizaz
dc.contributor.authorAbulkasim, Hussein
dc.contributor.authorFarouk, Ahmed
dc.contributor.authorSong, Houbing
dc.contributor.authorJin, Zhanpeng
dc.date.accessioned2026-01-22T16:19:00Z
dc.date.issued2025-11-10
dc.description.abstractCooperative robotic healthcare systems (CRHS) are advanced technologies that enhance medical services by allowing robots to collaborate with healthcare professionals, making clinical practices safer and more efficient. However, for these systems to work efficiently, they need fast and reliable communication and computation, all while managing the limited resources and energy available in robot-embedded sensors. Therefore, this survey focuses on clarifying how various networking and computing decisions impact different aspects of this technology, such as latency, reliability, Quality of Service (QoS), and scalability, etc. We evaluated the recent research on resource allocation, as well as orchestration in edge, fog, and cloud computing, to have a holistic overview of what has been done so far in this field. Moreover, we analyzed communication technologies such as 5G, Ultra-Reliable Low-Latency Communication (URLLC), Time-Sensitive Networking (TSN), Software-Defined Networking (SDN), Network Function Virtualization (NFV), and network slicing to understand their role in RHCS QoS metrics. Our synthesis finds that (i) placing perception/control close to the edge consistently decreases end-to-end delay, (ii) SDN/NFV and time-sensitive networking improve predictable and real-time operation in multi-robot hospital environments; and (iii) learning-based scheduling and offloading often outperform static heuristics in variable workloads. Despite these advancements, we have identified several challenges in the literature, such as limited interoperability between different vendors and a lack of standardized benchmarks for Quality of Service (QoS), etc. Therefore, we conducted a comparative analysis to understand how specific design choices influence the QoS metrics of this technology. In addition, we have proposed potential research directions that address the open challenges to ensure the real deployment of this technology.
dc.description.sponsorshipThe authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia, for funding this research (IFKSU-HCRA-3-3). This work was also supported in part by the Guangdong Provincial Department of Science and Technology under Grant 2023CX10X070; in part by the Guangdong Provincial Key Laboratory of Human Digital Twin under Grant 2022B1212010004; in part by the Guangzhou Basic Research Program under Grant SL2023A04J00930; and in part by the Shenzhen Holdfound Foundation Endowed Professorship.
dc.description.urihttps://ieeexplore.ieee.org/document/11237130
dc.format.extent35 pages
dc.genrejournal articles
dc.genrepostprints
dc.identifierdoi:10.13016/m2ny8o-i8ic
dc.identifier.citationAdil, Muhammad, Muhammad Khurram Khan, Aitizaz Ali, et al. “Towards Effective Communication Management in Cooperative Robotic-Enabled Healthcare Systems: Open Challenges and Future Research Directions.” IEEE Internet of Things Journal, 2025, 1–1. https://doi.org/10.1109/JIOT.2025.3631333.
dc.identifier.urihttps://doi.org/10.1109/JIOT.2025.3631333
dc.identifier.urihttp://hdl.handle.net/11603/41529
dc.language.isoen
dc.publisherIEEE
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department
dc.relation.ispartofUMBC Faculty Collection
dc.rights© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.subjectCooperative Robotic-enabled Healthcare
dc.subjectRobots
dc.subjectQuality of service
dc.subjectCloud computing
dc.subjectDeep Learning
dc.subjectQuality of Service
dc.subjectDeep learning
dc.subjectReinforcement learning
dc.subjectResource management
dc.subjectReliability
dc.subjectMedical services
dc.subjectRobot sensing systems
dc.subjectCommunication Challenges
dc.subjectReviews
dc.subjectUMBC Security and Optimization for Networked Globe Laboratory (SONG Lab)
dc.subjectReinforcement Learning
dc.subjectMeasurement
dc.titleTowards Effective Communication Management in Cooperative Robotic-enabled Healthcare Systems: Open Challenges and Future Research Directions
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0003-2631-9223

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