Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Database Management Systems
The cougar approach to in-network query processing in sensor networks
ACM SIGMOD Record
Scalable Fault-Tolerant Aggregation in Large Process Groups
DSN '01 Proceedings of the 2001 International Conference on Dependable Systems and Networks (formerly: FTCS)
ACM Transactions on Computer Systems (TOCS)
Epidemic-Style Proactive Aggregation in Large Overlay Networks
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
A scalable distributed information management system
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Aggregating Information in Peer-to-Peer Systems for Improved Join and Leave
P2P '04 Proceedings of the Fourth International Conference on Peer-to-Peer Computing
Definitive MPLS Network Designs
Definitive MPLS Network Designs
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Gossip-based aggregation in large dynamic networks
ACM Transactions on Computer Systems (TOCS)
Cooperative bug isolation
S3: a scalable sensing service for monitoring large networked systems
Proceedings of the 2006 SIGCOMM workshop on Internet network management
Delay aware querying with seaweed
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Interpreting the data: Parallel analysis with Sawzall
Scientific Programming - Dynamic Grids and Worldwide Computing
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Querying the internet with PIER
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Willow: DHT, aggregation, and publish/subscribe in one protocol
IPTPS'04 Proceedings of the Third international conference on Peer-to-Peer Systems
Concast: design and implementation of an active network service
IEEE Journal on Selected Areas in Communications
Scribe: a large-scale and decentralized application-level multicast infrastructure
IEEE Journal on Selected Areas in Communications
Tapestry: a resilient global-scale overlay for service deployment
IEEE Journal on Selected Areas in Communications
Network imprecision: a new consistency metric for scalable monitoring
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
A flexible architecture integrating monitoring and analytics for managing large-scale data centers
Proceedings of the 8th ACM international conference on Autonomic computing
Benchmarking decentralized monitoring mechanisms in peer-to-peer systems
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
Performance troubleshooting in data centers: an annotated bibliography?
ACM SIGOPS Operating Systems Review
Decentralized monitoring in peer-to-peer systems
Benchmarking Peer-to-Peer Systems
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San Fermín is a system for aggregating large amounts of data from the nodes of large-scale distributed systems. Each San Fermín node individually computes the aggregated result by swapping data with other nodes to dynamically create its own binomial tree. Nodes that fall behind abort their trees, thereby reducing overhead. Having each node create its own binomial tree makes San Fermín highly resilient to failures and ensures that the internal nodes of the tree have high capacity, thereby reducing completion time. Compared to existing solutions, San Fermín handles large aggregations better, has higher completeness when nodes fail, computes the result faster, and has better scalability. We analyze the completion time, completeness, and overhead of San Fermín versus existing solutions using analytical models, simulation, and experimentation with a prototype built on peer-to-peer system deployed on PlanetLab. Our evaluation shows that San Fermín is scalable both in the number of nodes and in the aggregated data size. San Fermín aggregates large amounts of data significantly faster than existing solutions: compared to SDIMS, an existing aggregation system, San Fermín computes a 1MB result from 100 PlanetLab nodes in 61-76% of the time and from 2-6 times as many nodes. Even if 10% of the nodes fail during aggregation, San Fermín still includes the data from 97% of the nodes in the result and does so faster than the underlying peer-to-peer system recovers from failures.