Speculative routing and update propagation: a kundali centric approach

Peer-to-peer networks have gained much attention due to their attractive features of self-organization, scalability and decentralized control. The key challenge in these networks is how to efficiently locate and retrieve the correct data. In this paper, we propose propagation and routing algorithms for a fully decentralized, self-organizing network. Our goal is to maximize the probability of finding the data, minimize peer access latencies and balance the workload among many peers. Central to our approach is the Kundali data structure that represents the set of data maintained by the peers and drives the smart routing of the search requests (queries). We have implemented our algorithms in the context of a fully decentralized Internet caching service in our internal network. Our mechanism is inexpensive, highly scalable, and resilient to node failures and with low administration cost. Experimental results validate or algorithms and show that they have good performance results.