Hermes: Clustering Users in Large-Scale E-mail Services - Christos Gkantsidis - Microsoft Research Cambridge, UK
Abstract: Hermes is an optimization engine for large-scale enterprise e-mail services. Such services could be hosted by a virtualized e-mail service provider, or by dedicated enterprise data centers. In both cases we observe that the pattern of e-mails between employees of an enterprise forms an implicit social graph. Hermes tracks this implicit social graph, periodically identifies clusters of strongly connected users within the graph, and co-locates such users on the same server. Co-locating the users reduces storage requirements: senders and recipients who reside on the same server can share a single copy of an e-mail. Co-location also reduces inter-server bandwidth usage. We evaluate Hermes using a trace of all e-mails within a major corporation over a five month period. The e-mail service supports over 120,000 users on 68 servers. Our evaluation shows that using Hermes results in storage savings of 37% and bandwidth savings of 50% compared to current approaches. The overheads are low: a single commodity server can run the optimization for the entire system.
Bio: Christos is a researcher in the Systems and Networking Group in Microsoft Research, Cambridge, UK. He holds a Ph.D. from Georgia Institute of Technology, Atlanta, GA, USA, and bachelors from University of Patras, Greece, both in computer science. He is interested in content distribution networks, peer-to-peer technologies, analysis and modelling of complex communication networks, and wireless mesh networking. Christos is a member of IEEE and ACM.