Adaptive probabilistic caching technique for caching networks with dynamic content popularity

摘要

This paper presents a new adaptive probabilistic cache algorithm (AProb) for modern caching networks. AProb is based on three main techniques: (1) dynamic probabilistic caching; (2) ghost list; and (3) adaptive probing and protection. It enables caching systems to quickly adjust their cached data to dynamic content popularity without intervention of network administrators and synchronization. The criteria of this adjustment are based on hit events occurring in AProb data structures. By using AProb, a caching system continuously adapts a caching probability and the ratio between probing and protection partitions of its cache. AProb has constant time complexity and its space overhead is minimal. Extensive computer simulations, which consider various network topologies and traffic traces, show that AProb offers improvement in terms of server-hit ratio, footprint distance, and caching time compared with those provided by several existing cache algorithms.