Caching contents close to end-users can improve the network performance, while causing the problem of guaranteeing consistency. Specifically, solutions are classified into validation and invalidation, the latter of which can provide strong cache consistency strictly required in some scenarios. To date, little work on the analysis of cache invalidation has been covered. In this work, by using conditional probability to characterize the interactive relationship between existence and validity, we develop an analytical model that evaluates the performance (hit probability and server load) of four different invalidation schemes with LRU replacement under arbitrary invalidation frequency distribution. The model allows us to theoretically identify some key parameters that affect our metrics of interest and gain some common insights on parameter settings to balance the performance of cache invalidation. Compared with other cache invalidation models, our model can achieve higher accuracy in predicting the cache hit probability. We also conduct extensive simulations that demonstrate the achievable performance of our model.

中文翻译：

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LRU替换下的缓存失效分析


缓存靠近最终用户的内容可以提高网络性能，但会带来保证一致性的问题。具体来说，解决方案分为验证和失效，后者可以提供某些场景严格要求的强缓存一致性。迄今为止，关于缓存失效分析的工作还很少。在这项工作中，通过使用条件概率来表征存在性和有效性之间的交互关系，我们开发了一个分析模型，用于评估任意失效频率分布下采用 LRU 替换的四种不同失效方案的性能（命中概率和服务器负载）。该模型使我们能够从理论上识别一些影响我们感兴趣的指标的关键参数，并获得一些关于参数设置的常见见解，以平衡缓存失效的性能。与其他缓存失效模型相比，我们的模型在预测缓存命中概率方面可以取得更高的准确性。我们还进行了广泛的模拟，以证明我们的模型可实现的性能。