Half-day Tutorial: Too Hot to Handle? Thermal and Performance Bottlenecks in XR Wearables for the Metaverse

The tutorial will take place at Room Pedro Nunes (DMUC). Registration and lunch will take place at São Francisco Convent. A bus will depart from the Convent to DMUC at 13h45 and will return at 18h00 so you can enjoy the welcome reception.

• Olga Chukhno (University of Reggio Calabria)
• Francesco Malandrino (National Research Council of Italy - CNR-IEIIT)
• Alessandro Catania (University of Pisa)

A half-day hybrid (both lecture and hands-on part are included) tutorial

14:00 — 14:10	Introduction to XR and metaverse | O. Chukhno
14:10 — 14:25	Current state and technology trends | O. Chukhno
14:25 — 14:40	Experience and comfort | O. Chukhno
14:40 — 15:00	XR wearable requirements | O. Chukhno
15:00 — 15:45	Distributed approach in XR scenarios and related challenges | F. Malandrino
15:45 — 16:15	Afternoon coffee break
16:15 — 16:35	Overheating aspect | A. Catania
16:35 — 17:15	Hands-on thermal analysis with COMSOL | A. Catania
17:15 — 17:30	Safety issues and Integration technologies | A. Catania
17:30 — 17:45	Demonstrating heating, power, and battery characteristics of XR deployments | F. Malandrino
17:45 — 18:00	Discussion and wrap up | All

Extended reality (XR) services are swiftly gaining traction and poised to revolutionize various sectors, paving the way for the metaverse. At the heart of these experiences are small, lightweight wearable devices, whose compact design, limited processing power, and restricted battery life pose challenges in delivering a high-quality XR experience. To overcome these limitations, most wearable devices today often depend on external computing resources, such as those at the network edge, to manage computationally demanding tasks like rendering complex graphics and processing real-time data. However, this offloading approach also brings challenges, including network latency, bandwidth constraints, and blockages. Performing some operations locally on the wearables can help mitigate these issues; however, the benefits of on-device computing must be weighed against the wearables' tendency to heat up with use, causing discomfort for the user and potentially disrupting the XR experience itself. Therefore, XR necessitates both (i) a distributed processing approach, which involves splitting processing between edge servers and local devices, and a careful thermal/power/battery analysis incorporated into offloading decisions. This makes the extent of the split between local computation and edge offloading one of the most critical decisions in XR scenarios, and the convergence of telecommunications and electronics is essential for making such decisions.

The high-level objectives of this tutorial are as follows:

• Provide a foundational understanding of the key concepts and technologies involved in extended reality and the metaverse;
• Explore the challenges and opportunities in delivering XR services to wearable devices;
• Analyze the role of offloading in optimizing XR performance and reducing device strain;
• Discuss the importance of thermal management, battery optimization, and packaging/integration technologies for wearable devices;
• Examine the challenges and limitations faced in integrating telecommunications and electronics into wearable devices;
• Engage in a hands-on exploration of thermal analysis;
• Propose potential solutions and future directions for overcoming these challenges and realizing the full potential of wearable devices in XR traffic delivery.

This tutorial is particularly timely given the rapid advancements in wearable technology and the growing interest in XR services and the metaverse. It stands out by addressing the conflicting challenges faced by wearable devices, such as optimizing limited local processing capabilities while simultaneously managing thermal concerns and potential connectivity issues due to blockages. These challenges require opposing solutions; intuitively, thermal management is best addressed by reducing on-device processing, whereas blockage issues can be mitigated by increasing it. Part of the uniqueness and value of this tutorial lies in its unabashedly technical, practical approach. A grand total of zero minutes is devoted to high-flown praise and abstract discussions of the metaverse vision; the sole focus of the tutorial is to enabling the metaverse by allowing wearables to work as expected.

• Introduction to XR and metaverse (O. Chukhno, 10 mins)
• Current state and technology trends (O. Chukhno, 15 mins)
• Experience and comfort (O. Chukhno, 15 mins)
• XR wearable requirements including on-device capabilities, communication issues, battery life, heat dissipation (O. Chukhno, 20 mins)
• Distributed approach in XR scenarios and related challenges, including ML (F. Malandrino, 45 mins)
  • Edge offloading strategies and their limitations
  • The role of ML in XR
  • Challenges in deploying and managing ML models for XR
  • Tiny ML/ML compression for efficient on-device inference and training
• Overheating aspect (A. Catania, 20 mins)
• Hands-on thermal analysis with COMSOL (A. Catania, 40 mins)
• Safety issues and integration technologies (A. Catania, 15 mins)
• Demonstrating heating, power, and battery characteristics of XR deployments (F. Malandrino, 15 mins)
• Discussion and wrap up (all, 15 mins)

This tutorial is intended for researchers, engineers, and students in computer science, electrical engineering, telecommunications, and human-computer interaction. It will also benefit everyone interested in wearable technology, XR, network optimization, thermal management, or the convergence of these fields.

Regarding the requirements for the tutorial room, it is necessary to provide access to power outlets for the presenters' and participants' laptops and a projector for presentation. Additionally, attendees must bring laptops for the hands-on part of the tutorial. There is no restriction on the number of participants, provided they are comfortably seated.

Olga Chukhno (olga.chukhno@unirc.it) received her MSCA Innovative Training Network fellowship and obtained her double Ph.D. from Tampere University (Finland) and Mediterranea University of Reggio Calabria (Italy), where she is currently an Assistant Professor. Her main research interests include wireless communications, programmable heterogeneous networks with optimal traffic management and service composition, advanced algorithms for managing distributed services, and resource optimization with a particular focus on XR applications. She actively participates in research projects (currently—RESTART program funded by the European Union, previously—SNS JU ADROIT6G project and H2020 A-WEAR ITN/EJD). She is currently an Associate Editor for IEEE Communications Letters (recognized as Exemplary Editor in 2024) and Review Editor at Frontiers. She served as a TPC member in IEEE GLOBECOM, IEEE ISC2, WiMob, IEEE ISCC, IEEE MEDITCOM, ACM (GoodIT, ICDCN), IEEE PerCom, and IEEE VTC2025-Spring. Since 2024, she has been teaching courses on metaverse and mathematical modeling and simulation for programmable networks for Master's and Ph.D. students.

Francesco Malandrino (francesco.malandrino@cnr.it) earned his Ph.D. degree from Politecnico di Torino in 2012 and is now a senior researcher at the National Research Council of Italy (CNR-IEIIT). His research interests include distributed ML as well as wireless, cellular, and vehicular networks. He has been working on distributed machine learning and mobile network orchestration for over a decade, with over 15 published journal papers on these topics. He is the principal investigator of the SHIELDED national PRIN project on security and trustworthiness for federated learning, the leader of CNR's team in the CENTRIC Horizon Europe project on human-centric orchestration for mobile networks, and the MUSMET EIC Pathfinder project on distributed learning for the musical metaverse. He is a TPC member of the IEEE International Conference on Computer Communications (IEEE INFOCOM).

Alessandro Catania (alessandro.catania@unipi.it) obtained his PhD degree from the University of Pisa, Italy, in 2020, where he is currently an Assistant Professor. His research interests include mixed-signal microelectronic design for high-temperature environments and for wearable and implantable devices. He has responsibility and research roles in the Horizon2020 Autocapsule project. He is Guest Editor for the Special Issue “Advances on Electronics for Harsh Environments” of Electronics (MDPI). Since 2022, he has been teaching courses on microelectronic design for Master's students.

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