A framework using cluster-based hybrid network architecture for collaborative virtual surgery

Area of Science:

• Computer Science
• Medical Simulation
• Virtual Reality

Background:

• Collaborative virtual environments (CVEs) offer potential for simulating cooperative surgical operations.
• Implementing high-performance collaborative surgical simulation is challenging due to state consistency and network latency issues, especially with complex models and haptics.

Purpose of the Study:

• To propose an integrated framework using a cluster-based hybrid network architecture for collaborative virtual surgery.
• To address challenges in state consistency and network latency in surgical simulations.

Main Methods:

• Utilized multicast transmission for reduced network latencies.
• Implemented reliable multicast with distributed message acknowledgment and a sliding window technique.
• Ensured system consistency via an administrative server and robustness through a failure detection chain.

Main Results:

• Successfully extended an existing orthopedic surgery trainer into a collaborative simulation system.
• Experimental results demonstrated the framework's capability to support collaborative surgical simulation.
• The framework effectively reduced communication overhead through management approaches.

Conclusions:

• The proposed framework provides a feasible and robust solution for high-performance collaborative surgical simulations.
• The system effectively manages network latency and maintains state consistency.
• This research advances the field of virtual reality in surgical training and cooperation.