A case for redundant arrays of inexpensive disks (RAID)
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
A physicist's guide to Mathematica
A physicist's guide to Mathematica
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Storage management and caching in PAST, a large-scale, persistent peer-to-peer storage utility
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Wide-area cooperative storage with CFS
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Kademlia: A Peer-to-Peer Information System Based on the XOR Metric
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
OpenDHT: a public DHT service and its uses
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Opendht: a public dht service
A distributed hash table
High availability, scalable storage, dynamic peer networks: pick two
HOTOS'03 Proceedings of the 9th conference on Hot Topics in Operating Systems - Volume 9
Efficient replica maintenance for distributed storage systems
NSDI'06 Proceedings of the 3rd conference on Networked Systems Design & Implementation - Volume 3
High availability in DHTs: erasure coding vs. replication
IPTPS'05 Proceedings of the 4th international conference on Peer-to-Peer Systems
Tapestry: a resilient global-scale overlay for service deployment
IEEE Journal on Selected Areas in Communications
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Recent work has shown that the durability of large-scale storage systems such as DHTs can be predicted using a Markov chain model. However, accurate predictions are only possible if the model parameters are also estimated accurately. We show that the Markov chain rates proposed by other authors do not consider several aspects of the system's behavior, and produce unrealistic predictions. We present a new analytical expression for the chain rates that is condiderably more fine-grain that previous estimations. Our experiments show that the loss rate predicted by our model is much more accurate than previous estimations.