No abstract

Decentralized and unstructured peer-to-peer networks such as Gnutella are attractive for certain applications because they require no centralized directories and no precise control over network topology or data placement. However, the flooding-based query algorithm used in Gnutella does not scale; each individual query generates a large amount of traffic and large systems quickly become overwhelmed by the query-induced load. This paper explores various alternatives to Gnutella's query algorithm and data replication strategy. We propose a query algorithm based on multiple random walks that resolves queries almost as quickly as Gnutella's flooding method while reducing the network traffic by two orders of magnitude in many cases. We also present a distributed replication strategy that yields closeto-optimal performance.

As disk performance continues to lag behind that of memory systems and processors, virtual memory management becomes increasingly important for overall system performance. In this paper we study the page reference behavior of a collection of memory-intensive applications, and propose a new virtual memory page replacement algorithm, SEQ. SEQ detects long sequences of page faults and applies most-recently-used replacement to those sequences. Simulations show that for a large class of applications, SEQ performs close to the optimal replacement algorithm, and significantly better than Least-Recently-Used (LRU). In addition, SEQ performs similarly to LRU for applications that do not exhibit sequential faulting.