Abstract
Resource discovery is the process of locating shared resources on a computer network. Previously studied examples include efficiently finding files with a given title on a file sharing system. New developments in the application of networked computers raise the issue of dynamic resource discovery, the process of locating shared resources that are always changing. An example application is peer-to-peer computing, where a user wishes to locate idle CPU time anywhere on the network. Peer-to-peer computing is an exciting new computing paradigm. There are vast amounts of idle CPU resources scattered through the globe. We envision a peer-to-peer system to harness those resources, where every member of the network can both share their own CPU and utilize others' CPUs. In a network of hundreds of thousands of computers, resource discovery will play an important role. To avoid debilitating amounts of excess network traffic it is imperative that an efficient resource discovery algorithm be chosen. This paper's contribution to this topic is the use of gossip to reduce network traffic without sacrificing effectiveness. This project has investigated piggybacking gossip messages on other communications to increase the intelligence of searching protocols. The overhead of piggybacking the small amount of data needed is very small, and a case study by simulation shows that it can reduce network traffic by 71-84 percent