Implementation of a Tapestry Node: The main components: The core router, utilizes the routing and object reference tables to handle messages, The node membership component, responsible for handling the integration of new nodes as well as graceful (or voluntary) exit of nodes The mesh repair, is responsible for adapting the Tapestry mesh as the Network environment changes The patchwork monitoring loss rates and latency information for established communication channels

The central role of the Core Routing Component

The critical path of routing Two kinds of lookup’s for the Router: The object-references: Timecomplexity O(1), if all references fit in memory The tablelookup for nodes: Timecomplexity O(Log B N) Toward a Higher Performance Implementation

The Bloomfilter Which comes in handy, because: In a large global-scale deployment of Tapestry the pointers will not fit into main-memory In Tapestry most routing hops receive negative lookup results Two links: From the article: “A Bloom filter is a lossy representation of a set that can detect the absence of a member quite quickly” Definition: “A probalistic algorithm to quickly test membership in a large set using multiple hash functions into a single array of bits”

Using the Bloomfilter

Testing the Performance of Routing

Optimizing the Performance of Routing

Testing Scalability

Testing the Performance Against Massiv Fall-outs and Joins

Testing the Performance Against continous Fall-outs and Joins

Conclusion Tapestry provides a stable interface under a variety of network conditions Tapestry supports efficient routing of messages It scales well Simple optimizations can be achieved by replicating data across multiple servers