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Main Authors: Hossain, Abrar, Ahmed, Kishwar
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2606.00490
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author Hossain, Abrar
Ahmed, Kishwar
author_facet Hossain, Abrar
Ahmed, Kishwar
contents Modern High Performance Computing (HPC) centers face growing challenges in ingesting large and diverse data streams. These issues often create bottlenecks that limit bandwidth utilization and delay scientific progress. Traditional static allocation and simple queuing methods are often insufficient. This paper presents a dynamic, value-based approach to bandwidth allocation. We formalize the problem by incorporating both network and processing constraints. To address it, we introduce two auction-based mechanisms: the Greedy Value Density Auction, which is computationally efficient, and the Vickrey--Clarke--Groves (VCG) Knapsack Auction, which provides strong theoretical guarantees. Both mechanisms rely on user bids that specify data requirements and scientific value. The objective is to maximize the total value of successful transfers, commonly referred to as social welfare. Simulation results demonstrate that the proposed mechanisms significantly outperform First Come First Served (FCFS) baselines. Under high-load conditions, they reduce average and tail completion delays by more than 80%. Predictability also improves, with the coefficient of variation of delay decreasing by 75--85%. Network stability increases as well, with load volatility, measured by the peak-to-average ratio, decreasing by 60--70%. These results indicate that value-driven, adaptive bandwidth allocation can reduce congestion, improve resource utilization, and provide fairer access based on scientific importance.
format Preprint
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publishDate 2026
record_format arxiv
spellingShingle XOR Bidding and Knapsack Formulations for HPC Network Resource Allocation
Hossain, Abrar
Ahmed, Kishwar
Networking and Internet Architecture
Modern High Performance Computing (HPC) centers face growing challenges in ingesting large and diverse data streams. These issues often create bottlenecks that limit bandwidth utilization and delay scientific progress. Traditional static allocation and simple queuing methods are often insufficient. This paper presents a dynamic, value-based approach to bandwidth allocation. We formalize the problem by incorporating both network and processing constraints. To address it, we introduce two auction-based mechanisms: the Greedy Value Density Auction, which is computationally efficient, and the Vickrey--Clarke--Groves (VCG) Knapsack Auction, which provides strong theoretical guarantees. Both mechanisms rely on user bids that specify data requirements and scientific value. The objective is to maximize the total value of successful transfers, commonly referred to as social welfare. Simulation results demonstrate that the proposed mechanisms significantly outperform First Come First Served (FCFS) baselines. Under high-load conditions, they reduce average and tail completion delays by more than 80%. Predictability also improves, with the coefficient of variation of delay decreasing by 75--85%. Network stability increases as well, with load volatility, measured by the peak-to-average ratio, decreasing by 60--70%. These results indicate that value-driven, adaptive bandwidth allocation can reduce congestion, improve resource utilization, and provide fairer access based on scientific importance.
title XOR Bidding and Knapsack Formulations for HPC Network Resource Allocation
topic Networking and Internet Architecture
url https://arxiv.org/abs/2606.00490