  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.
