TY - GEN
T1 - Remote Robotic Surgery
T2 - 18th International Conference of Network and Service Management, CNSM 2022
AU - Hentati, Amina
AU - Ebrahimzadeh, Amin
AU - Glitho, Roch H.
AU - Belqasmi, Fatna
AU - Mizouni, Rabeb
N1 - Publisher Copyright:
© 2022 IFIP.
PY - 2022
Y1 - 2022
N2 - Remote robotic surgery is one of the most interesting Tactile Internet (TI) applications. It has a huge potential to deliver healthcare services to remote locations. Moreover, it provides better precision and accuracy to diagnose and operate on patients. Remote robotic surgery requires ultra-low latency and ultra-high reliability. The aforementioned stringent requirements do not apply for all the multimodal data traffic (i.e., audio, video, and haptic) triggered during a surgery session. Hence, customizing resource allocation policies according to the different quality-of-service (QoS) requirements is crucial in order to achieve a cost-effective deployment of such system. In this paper, we focus on resource allocation in a softwarized 5G-enabled TI remote robotic surgery system through the use of Network Functions Virtualization (NFV). Specifically, this work is devoted to the joint placement and scheduling of application components in an NFV-based remote robotic surgery system, while considering haptic and video data. The problem is formulated as an integer linear program (ILP). Due to its complexity, we propose a greedy algorithm to solve the developed ILP in a computationally efficient manner. The simulation results show that our proposed algorithm is close to optimal and outperforms the benchmark solutions in terms of cost and admission rate. Furthermore, our results demonstrate that splitting application traffic to multiple VNF-forwarding graphs (VNF-FGs) with different QoS requirements achieves a significant gain in terms of cost and admission rate compared to modeling the whole application traffic with one VNF-FG having the most stringent requirements.
AB - Remote robotic surgery is one of the most interesting Tactile Internet (TI) applications. It has a huge potential to deliver healthcare services to remote locations. Moreover, it provides better precision and accuracy to diagnose and operate on patients. Remote robotic surgery requires ultra-low latency and ultra-high reliability. The aforementioned stringent requirements do not apply for all the multimodal data traffic (i.e., audio, video, and haptic) triggered during a surgery session. Hence, customizing resource allocation policies according to the different quality-of-service (QoS) requirements is crucial in order to achieve a cost-effective deployment of such system. In this paper, we focus on resource allocation in a softwarized 5G-enabled TI remote robotic surgery system through the use of Network Functions Virtualization (NFV). Specifically, this work is devoted to the joint placement and scheduling of application components in an NFV-based remote robotic surgery system, while considering haptic and video data. The problem is formulated as an integer linear program (ILP). Due to its complexity, we propose a greedy algorithm to solve the developed ILP in a computationally efficient manner. The simulation results show that our proposed algorithm is close to optimal and outperforms the benchmark solutions in terms of cost and admission rate. Furthermore, our results demonstrate that splitting application traffic to multiple VNF-forwarding graphs (VNF-FGs) with different QoS requirements achieves a significant gain in terms of cost and admission rate compared to modeling the whole application traffic with one VNF-FG having the most stringent requirements.
KW - Joint Placement and Scheduling
KW - Latency
KW - Network Function Virtualization
KW - Remote Robotic Surgery
KW - Tactile Internet
KW - Virtual Network Function
KW - VNF Forwarding Graph
UR - http://www.scopus.com/inward/record.url?scp=85143903589&partnerID=8YFLogxK
U2 - 10.23919/CNSM55787.2022.9964591
DO - 10.23919/CNSM55787.2022.9964591
M3 - Conference contribution
AN - SCOPUS:85143903589
T3 - Proceedings of the 2022 18th International Conference of Network and Service Management: Intelligent Management of Disruptive Network Technologies and Services, CNSM 2022
SP - 205
EP - 211
BT - Proceedings of the 2022 18th International Conference of Network and Service Management
A2 - Charalambides, Marinos
A2 - Papadimitriou, Panagiotis
A2 - Cerroni, Walter
A2 - Kanhere, Salil
A2 - Mamatas, Lefteris
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 31 October 2022 through 4 November 2022
ER -