We survey analytical methods and evaluation results for the performance assessment of caching strategies. Knapsack solutions are derived, which provide static caching bounds for independent requests and general bounds for dynamic caching under arbitrary request pattern. We summarize Markov- and time-to-live-based solutions, which assume specific stochastic processes for capturing web request streams and timing. We compare the performance of caching strategies with different knowledge about the properties of data objects regarding a broad set of caching demands. The efficiency of web caching must regard benefits for network wide traffic load, energy consumption and quality-of-service aspects in a tradeoff with costs for updating and storage overheads.

翻译：我们综述了用于缓存策略性能评估的分析方法与评估结果。推导出了背包解，该解为独立请求提供静态缓存界限，并为任意请求模式下的动态缓存提供通用界限。我们总结了基于马尔可夫和生存时间的解决方案，这些方案假设特定的随机过程来捕获网络请求流及其时序。我们比较了不同缓存策略在掌握数据对象属性知识程度不同的情况下的性能，涵盖了一系列广泛的需求场景。网络缓存的效率必须权衡对网络流量负载、能耗和服务质量方面的益处与更新和存储开销的成本。