## 3 Results  
### Experimental Design  
The performance of the Holo-Cloud system has undergone assessment processes across various settings to ensure satisfactory functionality. Pioneering XR and cloud studies have employed various experimental settings due to heterogeneity in their XR applications. Therefore, replicating a similar experimental setting for our work is challenging. However, the evaluation metrics used in this study align with the latest methods in the literature. The objective of the experimental design in this study is to mimic a test environment and evaluate the performance of the Holo-Cloud to demonstrate its potential for further development [47]. These settings include the connection of a single client to the FI3D application hosted on the cloud and the connection of multiple clients to the FI3D. In each scenario, the FI3D server software is executed on the Holo-Cloud virtual machine that was hosted on AWS. The server software loads images and models of a cardiac MRI. This model is a 4D reconstruction of the left ventricle of the human heart from a multislice, multiframe CINE MRI set [32]. Subsequently, XR client software (installed on viewers' HMD and HHD, located in different physical locations) connect to the server software through a secure internet connection. Viewers choose the loaded study data, and the client software loads the 3D MRI holographic model.  
As the interaction with the system shown in Figure 3, for HMD viewers, the holographic model is loaded into their HMD's FOV, and they can roam around and view the model from different perspectives. For HHD viewers, the model is overlayed on their HHD screen's camera view. After viewing the model for a certain amount of time, the server software starts broadcasting the animated version of the study data to all currently connected clients. A scene control gesture menu was added to the system for HMD interfaces that enables users to modify study visuals by hand gesture. Similarly, HHD interfaces can interact with the study visuals using hand control commands (e.g., pinching and tapping) using the scene control touch menu. The overall network utilization, CPU utilization, and memory usage were measured during the study and later used to evaluate the performance of the Holo-Cloud platform.  
During this process, the FI3D server software sends two sets of data regarding the study to the client. The first set of data is the pixel intensities and triangular mesh for 3D models. This set of data is cached on the client's device. The second set of data, also known as metadata, is the visual properties of the of the model, such as the position, orientation, size, color, and slice index. The metadata, which is smaller than the first set of data, is not cached on the client device. The server continuously delivers models' metadata to the connected client because the visual properties of the models (e.g., position or orientation) can be changed at any time by the server or other clients [31].  
Spikes in resource utilization of the Holo-Cloud server are anticipated during each event in the experiments due to the increase in the number of received processing requests, TCP communication requests, and acknowledgments between the server software and clients. Moreover, uploading content data (models and collaborative CINE MRI sequence) to clients requires processing, memory, and network resources.