Metrics for Assessing Changes in Flow-based Networks

2025-08-13

AI Summary

Addressing the challenges of network performance evaluation under traffic fluctuations and the difficulty of quantifying individual flow impact, this paper proposes a flow-level influence assessment framework integrating percentile statistics, sample distribution analysis, and an improved Shapley value. We innovatively design a utilization scoring metric and leverage cooperative game theory to quantify the marginal contribution of each flow to network resource consumption. From an initial set of 11 candidate metrics, we identify three core indicators balancing interpretability, maintainability, and scalability. Extensive experiments across multiple traffic scenarios demonstrate that our method significantly improves detection sensitivity to abrupt network state transitions induced by anomalous flows. Results confirm that the framework enables efficient, robust performance attribution and optimization decision-making in dynamic networks, exhibiting strong potential for real-world deployment.

Technology Category

• Search and Optimization: Evaluation and Analysis
• Game Theory and Economic Paradigms: Cooperative Game Theory
• Machine Learning: Evaluation and Analysis

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

This paper addresses the challenges of evaluating network performance in the presence of fluctuating traffic patterns, with a particular focus on the impact of peak data rates on network resources. We introduce a set of metrics to quantify network load and measure the impact of individual flows on the overall network state. By analyzing link and flow data through percentile values and sample distributions, and introducing the Utilization Score metric, the research provides insights into resource utilization under varying network conditions. Furthermore, we employ a modified Shapley value-based approach to measure the influence of individual flows on the network, offering a better understanding of their contribution to network performance. The paper reviews and compares 11 metrics across various network scenarios, evaluating their practical relevance for research and development. Our evaluation demonstrates that these metrics effectively capture changes in network state induced by specific flows, with three of them offering a broad range of valuable insights while remaining relatively easy to maintain. Moreover, the methodology described in this paper serves as a framework for future research, with the potential to expand and refine the set of metrics used to evaluate flow impact on network performance.

Problem

• Evaluating network performance with fluctuating traffic patterns
• Quantifying network load and individual flow impacts
• Comparing metrics for practical relevance in network scenarios

Innovation

• Utilization Score metric for resource analysis
• Modified Shapley value for flow influence
• Percentile-based link and flow evaluation