The two main approaches to find data in
(P2P) systems are
networks using flooding and
networks using a distributed index. A distributed index is usually built over
that are stored in the network whether they are queried or not. Indexing all keys is no longer feasible when indexing
, as the key space becomes very large. Here we need a query-adaptive approach that indexes only keys worth indexing, i.e. keys that are queried at least with a certain frequency. In this paper we study the cost of indexing and propose a query-adaptive
partial distributed hash table
(PDHT) that does not keep all keys in the index. We model and analyze a scenario to show that query-adaptive partial indexing outperforms pure flooding and “index-everything” strategies. Furthermore, our scheme is able to automatically adjust the index to changing query frequencies and distributions.