Collaborative Mixed Reality (CollabMR) enables multiple users to interact with both the physical and virtual worlds in real time. One of the major challenges CollabMR faces is the timely synchronization of shared virtual content, yet how network Quality of Service (QoS) maps to user Quality of Experience (QoE) remains poorly understood. To address this gap, we present an exploratory, multi-layer framework linking QoS inputs (latency, bandwidth) to system responsiveness and perceptual, cognitive, and behavioral QoE. We evaluate this framework through a controlled within-subject human study with 60 participants (30 pairs) using HoloLens 2 headsets and a collaborative 3D puzzle task under four network conditions. To validate, we analyze network-level measurements, interaction logs, task performance metrics, and post-task subjective questionnaires to examine how variations in system responsiveness manifest across our conceptual model.

In the aftermath of the pandemic, governments and organizations worldwide are proactively preparing for future challenges. The importance of communication and connection has been underscored in recent years, especially through applications like Skype, Discord, and Zoom, as they play a pivotal role in collaboration and innovation across the world. Virtual platforms have become integral for societies to connect and collaborate, emphasizing the need for the evolution of communication methods to ensure a resilient global future. This paper provides an implementation for an Extended Reality (XR) conferencing application. This required implementing an XR-capable application for the HoloLens 2 as well as creating a server application that acts as a hub for all connected users, with a focus on simplicity and modality to allow for future modification and experimentation. Once these applications were created, further testing was performed to evaluate network metrics, and user quality of experience through a user study. The user study evaluates the effects of latency on object movement and creates a starting point for further improvement on the created messaging system. The development and deployment of a basic conferencing application for the HoloLens 2 is an important step in building a more connected and resilient future.

In recent years, streamed 360° videos have gained popularity within Virtual Reality (VR) and Augmented Reality (AR) applications. However, they are of much higher resolutions than 2D videos, causing greater bandwidth consumption when streamed. This increased bandwidth utilization puts tremendous strain on the network capacity of the cloud providers streaming these videos. In this paper, we introduce L3BOU, a novel, three-tier distributed software framework that reduces cloud-edge bandwidth in the backhaul network and lowers average end-to-end latency for 360° video streaming applications. The L3BOU framework achieves low bandwidth and low latency by leveraging edge-based, optimized upscaling techniques. L3BOU accomplishes this by utilizing down-scaled MPEG-DASH-encoded 360° video data, known as Ultra Low Resolution (ULR) data, that the L3BOU edge applies distributed super-resolution (SR) techniques on, providing a high quality video to the client. L3BOU is able to reduce the cloud-edge backhaul bandwidth by up to a factor of 24, and the optimized super-resolution multi-processing of ULR data provides a 10-fold latency decrease in super resolution upscaling at the edge.

We demonstrate a video 360 navigation and streaming system for Mobile HMD devices. The Navigation Graph (NG) concept is used to predict future views that use a graph model that captures both temporal and spatial viewing behavior of prior viewers. Visualization of video 360 content navigation and view prediction algorithms is used for assessment of Quality of Experience (QoE) and evaluation of the accuracy of the NG-based view prediction algorithm.