User-Assisted Collaborative Distributed Inference for Efficient QoS-Aware Autoscaling
Growing demand for artificial intelligence (AI) inference services requires scalable infrastructure, yet centralized serving costs rise with demand. We propose a collaborative distributed inference system combining dedicated infrastructure with resources contributed by service users. Dedicated resources provide baseline capacity for maintaining quality of service (QoS), while volunteered resources absorb increasing demand without proportional growth in centralized infrastructure. To capture stochastic and dynamic interactions among users, resources, tasks, and policies, we develop a high-dimensional generative Markov model with structured temporal factorization. The model supports simulat...
| Authors | Alfreds Lapkovskis, Ali Beikmohammadi, Sindri Magnússon et al. |
|---|---|
| Primary category | cs.DC |
| Published | 12 August 2026 |
| Last updated at source | 12 August 2026 |
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