Abstract
Mobile Augmented Reality (MAR) applications face performance challenges due to their high computational demands and need for low-latency responses. Traditional approaches like on-device storage or reactive data fetching from the cloud often result in limited augmented reality (AR) experiences. Edge caching, which caches AR objects closer to the user, provides a promising solution. However, existing edge caching approaches do not consider AR-specific features such as AR object sizes, user interactions, user's field of view and physical location in a coherent manner. This paper investigates how to further optimize edge caching by employing AR-Aware prefetching techniques. We present ASTRA, a prefetching framework tailored for mobile augmented reality edge caches. It integrates object associations derived from user interaction patterns with spatial awareness based on the user's physical location and field of view. This approach employs an association factor per object that considers the recency of object co-Access; and a lazy fetching strategy that prioritizes prefetching only when the user is in close proximity to the virtual objects. Furthermore, ASTRA incorporates an adaptive tuning algorithm for minimum support in association rule generation to minimize the computation overhead, making it a distinct and effective solution for enhancing user experience in AR applications by ensuring timely virtual object availability.Through extensive evaluation using both synthetic and real-world workloads, we demonstrate that ASTRA significantly improves cache hit rates compared to current prefetching algorithms, achieving gains in hit rate of upto 35% and end-To-end latency by upto 14%. Further, we demonstrate that the adaptive tuning algorithm that automatically tunes minimum support further improves the hit rate of ASTRA by 10%. Our findings demonstrate the potential of ASTRA to substantially enhance the user experience in MAR applications by ensuring the timely availability of virtual objects.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings - 2025 IEEE International Conference on Cloud Engineering, IC2E 2025 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 170-179 |
| Number of pages | 10 |
| ISBN (Electronic) | 9798331534653 |
| DOIs | |
| State | Published - 2025 |
| Event | 13th IEEE International Conference on Cloud Engineering, IC2E 2025 - Rennes, France Duration: Sep 23 2025 → Sep 26 2025 |
Publication series
| Name | Proceedings - 2025 IEEE International Conference on Cloud Engineering, IC2E 2025 |
|---|
Conference
| Conference | 13th IEEE International Conference on Cloud Engineering, IC2E 2025 |
|---|---|
| Country/Territory | France |
| City | Rennes |
| Period | 9/23/25 → 9/26/25 |
Bibliographical note
Publisher Copyright:© 2025 IEEE.
Keywords
- Augmented reality
- association
- caching
- confidence
- edge computing
- prefetching
- proximity
- support
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