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David Lindero

Publications and source records attributed to David Lindero.

4 recordsLinked to original sources

Automated Mobile Video Objective Testing System

Applying QoE analysis to optimize usage of cellular spectrum is of high interest to mobile network operators. A key challenge is to be able to perform QoE measurement across very different types of apps, from DASH VoD to interactive applications such as Video Conferencing and Cloud Gaming. This paper presents AMVOTS, a QoE measurement system developed by AT&T, which is flexible enough to support a large range of application types and network conditions. We also discuss using AMVOTS as part of a closed loop to prototype QoE-aware radio resource allocation.

cs.NI

Prototyping QoE-Aware Rate Adaptation in Cellular Networks with Commercial Applications

Prior work has shown that QoE-aware resource sharing for real-time interactive video can support up to three times more simultaneous sessions at acceptable quality compared to rate-fair allocation. However, the required capabilities (QoE-targeted encoding, runtime spatial complexity estimation, and rich application-network APIs) are not yet available in commercial deployments. In this paper, we take an evolutionary approach: we design a system that delivers QoE-aware resource allocation using only capabilities that can be assembled in a lab today. We extend the utility-based allocation framework to the radio resource domain by introducing composite spatial complexity, which combines a session's video spatial complexity with its time-variant spectral efficiency into a single resource demand function. To operate with commercial real-time video streaming applications that use rate-based congestion control and lack capability to measure QoE, we use external tooling for QoE measurements. We develop an incremental reallocation algorithm with per-interval limits that encode both the congestion control algorithm's speed constraint and that spatial complexity estimates are reliable only near the current rate. The resulting prototype combines external QoE measurements with congestion-signal-based rate steering and does not require modification to commercial applications. We chart an evolution path from this prototype toward full QoE-aware resource sharing, mapping emerging standards (IETF SCONE, CAMARA, Media over QUIC) to the progressive capabilities they enable.

cs.NI

Studying Mobile Spatial Collaboration across Video Calls and Augmented Reality

Mobile video calls are widely used to share information about real-world objects and environments with remote collaborators. While these calls provide valuable visual context in real time, the experience of interacting with people and moving around a space is significantly reduced when compared to co-located conversations. Recent work has demonstrated the potential of Mobile Augmented Reality applications to enable more spatial forms of collaboration across distance. To better understand the dynamics of mobile AR collaboration and how this medium compares against the status quo, we conducted a comparative structured observation study to analyze people's perception of space and interaction with remote collaborators across mobile video calls and AR-based calls. Fourteen pairs of participants completed a spatial collaboration task using each medium. Through a mixed-methods analysis of session videos, transcripts, motion logs, post-task exercises, and interviews, we highlight how the choice of medium influences the roles and responsibilities that collaborators take on and the construction of a shared language for coordination. We discuss the importance of spatial reasoning with one's body, how video calls help participants "be on the same page" more directly, and how AR calls enable both onsite and remote collaborators to engage with the space and each other in ways that resemble in-person interaction. Our study offers a nuanced view of the benefits and limitations of both mediums, and we conclude with a discussion of design implications for future systems that integrate mobile video and AR to better support spatial collaboration in its many forms.

cs.HC

Quantifying QoE-Aware Resource Sharing Potential Under Time-variant Spatial Complexity

The spatial complexity of real-time interactive video varies significantly within a single session, not only across different content types. This renders static resource allocation inadequate in our scenario: even with oracle knowledge of each session's average content complexity, static methods cannot guarantee acceptable picture quality. Using second-by-second oracle spatial complexity knowledge as a deliberate upper-bound methodology, we quantify the potential of dynamic QoE-aware resource sharing through a utility-based framework. In our scenario of 30 concurrent cloud gaming sessions sharing a bottleneck link, dynamic allocation guarantees acceptable quality (VMAF>=50) for all sessions at 35 Mbps, while no static method achieves this even at 100 Mbps. The framework makes allocation policy explicit and tunable, replacing rigid equalization that degrades all sessions when resources are scarce.

cs.NI