Hybrid Rate-Limiting Algorithms for Payment Systems: A Comparative Analysis under High Traffic Spikes

Nitya sri Nellore

doi:10.5281/zenodo.14802748

Hybrid Rate-Limiting Algorithms for Payment Systems: A Comparative Analysis under High Traffic Spikes

Author(s)	Nitya sri Nellore
Country	United States
Abstract	Payment systems experience unpredictable traffic spikes, particularly during sales events, promotional campaigns, or seasonal shopping periods. These spikes pose a significant challenge to maintaining service quality and ensuring that legitimate users are not affected by resource contention or system overload. Traditional rate-limiting algorithms like token bucket and leaky bucket often fail to handle these high-demand scenarios effectively, resulting in degraded user experience, increased latency, and potential revenue loss. Furthermore, such static approaches lack the flexibility to adapt to rapidly changing traffic patterns, making them unsuitable for modern distributed systems. This paper introduces hybrid rate-limiting algorithms tailored for payment systems, combining static rate limits with adaptive mechanisms powered by predictive analytics and feedback loops. We propose a framework that integrates token bucket for baseline limits with adaptive modules to dynamically adjust thresholds based on real-time traffic metrics. By simulating real-world payment system traffic patterns—including steady transactions, bursty demand surges, and mixed scenarios—we provide a comprehensive comparison of static, adaptive, and hybrid algorithms. Our findings reveal that the hybrid approach consistently outperforms traditional methods, achieving superior throughput, fairness, and latency reduction. Beyond payment systems, the principles of hybrid rate limiting are broadly applicable to any high-throughput environment, such as content delivery networks, API gateways, and gaming platforms. By enabling scalable and reliable traffic management, hybrid rate-limiting algorithms offer a robust solution to challenges faced across diverse domains, ensuring better resource utilization and enhanced user experiences. Payment systems often face high traffic spikes during key periods like holiday shopping, flash sales, or promotions, where transaction volumes can surge by up to 200-300% in a matter of minutes. This creates significant stress on backend systems, potentially leading to degraded performance or complete outages. Approximately 60-70% of payment systems report experiencing such spikes during major retail events or high-demand periods. Traditional rate-limiting algorithms fail to scale effectively in these scenarios, as they lack the ability to adapt dynamically to the changing load, leading to high latencies, dropped transactions, and user dissatisfaction. Hybrid rate-limiting algorithms solve this problem by integrating static mechanisms for baseline protection with adaptive modules that respond to real-time traffic fluctuations. By dynamically adjusting thresholds, these algorithms can ensure that resources are optimally utilized while maintaining fairness across users. For instance, during a flash sale, a hybrid system can prioritize critical transactions, such as high-value purchases, while managing lower-priority requests efficiently. This not only improves user experience but also ensures system stability under extreme loads. Our experiments simulate real-world payment system traffic patterns, including steady transactions, bursty demand surges, and mixed scenarios. Comparative analysis demonstrates that the hybrid approach consistently outperforms static and adaptive algorithms, achieving superior throughput, fairness, and latency reduction. Additionally, the findings highlight how hybrid rate-limiting algorithms can be extended to other applications, such as content delivery networks, gaming platforms, and API gateways, which also experience similar high-demand scenarios. This work provides actionable insights and implementation strategies for enhancing the reliability and scalability of payment systems.
Keywords	-
Field	Engineering
Published In	Volume 14, Issue 4, October-December 2023
Published On	2023-10-07
Cite This	Hybrid Rate-Limiting Algorithms for Payment Systems: A Comparative Analysis under High Traffic Spikes - Nitya sri Nellore - IJSAT Volume 14, Issue 4, October-December 2023. DOI 10.5281/zenodo.14802748
DOI	https://doi.org/10.5281/zenodo.14802748
Short DOI	https://doi.org/g83xkn

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Hybrid Rate-Limiting Algorithms for Payment Systems: A Comparative Analysis under High Traffic Spikes

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