Evolutionary design of en-route caching strategies

Nowadays, large distributed databases are commonplace. Client applications increasingly rely on accessing objects from multiple remote hosts. The Internet itself is a huge network of computers, sending documents point-to-point by routing packetized data over multiple intermediate relays. As hubs in the network become overutilized, slowdowns and timeouts can disrupt the process. It is thus worth to think about ways to minimize these effects. Caching, i.e. storing replicas of previously-seen objects for later reuse, has the potential for generating large bandwidth savings and in turn a significant decrease in response time. En-route caching is the concept that all nodes in a network are equipped with a cache, and may opt to keep copies of some documents for future reuse [X. Tang, S.T. Chanson, Coordinated en-route web caching, IEEE Transact. Comput. 51 6 (2002) 595–607]. The rules used for such decisions are called “caching strategies”. Designing such strategies is a challenging task, because the different nodes interact, resulting in a complex, dynamic system. In this paper, we use genetic programming to evolve good caching strategies, both for specific networks and network classes. An important result is a new innovative caching strategy that outperforms current state-of-the-art methods.