Problem
Research questions and friction points this paper is trying to address.
edge computing
resource efficiency
quality flexibility
overload management
PRICE: Pricing-based Resource Incentives for Quality-of-Result-aware Computing at the Edge
🤖 AI Summary
本文提出PRICE机制，通过结合利用率相关的定价信号与请求质量选择，解决边缘计算中资源紧张问题，提高请求吞吐量和CPU利用率。
📝 Abstract
Edge nodes are capacity-constrained by design, yet many edge workloads can trade result quality for resource efficiency at runtime. Existing edge pricing mechanisms largely treat requests as fixed-configuration submissions and rarely exploit per-request quality flexibility under overload. We present PRICE, an incentive mechanism that couples a utilization-dependent price signal to per-request quality selection. As utilization increases, rising acceptance prices make resource-intensive variants less likely to be selected, shifting accepted requests toward lighter execution and allowing the node to serve significantly more requests while operating near capacity. Evaluation on real hardware under sustained overload shows that PRICE outperforms both fixed-allocation and dynamic-pricing baselines in accepted throughput and CPU utilization. The results are robust across pricing function families, task-duration distributions, and client populations. Result-quality flexibility is a powerful but underused control dimension for overload management at the edge, and pricing is an effective mechanism to exploit it.
Innovation
Methods, ideas, or system contributions that make the work stand out.
utilization-dependent price signal
per-request quality selection
overload management
🔎 Similar Papers
No similar papers found.
