Distributed snapshots: determining global states of distributed systems
ACM Transactions on Computer Systems (TOCS)
Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Discovering Workflow Performance Models from Timed Logs
EDCIS '02 Proceedings of the First International Conference on Engineering and Deployment of Cooperative Information Systems
Pinpoint: Problem Determination in Large, Dynamic Internet Services
DSN '02 Proceedings of the 2002 International Conference on Dependable Systems and Networks
Selected topics on assignment problems
Discrete Applied Mathematics
A decentralized model-based diagnostic tool for complex systems
ICTAI '01 Proceedings of the 13th IEEE International Conference on Tools with Artificial Intelligence
Performance debugging for distributed systems of black boxes
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
A polynomial-time approximation algorithm for the permanent of a matrix with nonnegative entries
Journal of the ACM (JACM)
Refereed Papers: Real-time Log File Analysis Using the Simple Event Correlator (SEC)
LISA '04 Proceedings of the 18th USENIX conference on System administration
Monitoring Large Systems Via Statistical Sampling
International Journal of High Performance Computing Applications
Mining logs files for data-driven system management
ACM SIGKDD Explorations Newsletter - Natural language processing and text mining
Path-based faliure and evolution management
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
Using magpie for request extraction and workload modelling
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Transaction monitoring in ENCOMPASS: reliable distributed transaction processing
VLDB '81 Proceedings of the seventh international conference on Very Large Data Bases - Volume 7
Efficient minimum cost matching using quadrangle inequality
SFCS '92 Proceedings of the 33rd Annual Symposium on Foundations of Computer Science
Tracking transaction footprints for non-intrusive end-to-end monitoring
Cluster Computing
Selectively retrofitting monitoring in distributed systems
ACM SIGMETRICS Performance Evaluation Review
A universal method for composing business transaction models using logs
IM'09 Proceedings of the 11th IFIP/IEEE international conference on Symposium on Integrated Network Management
USENIX'09 Proceedings of the 2009 conference on USENIX Annual technical conference
Rake: semantics assisted network-based tracing framework
Proceedings of the Nineteenth International Workshop on Quality of Service
Heavy-traffic analysis of cloud provisioning
Proceedings of the 24th International Teletraffic Congress
Performance troubleshooting in data centers: an annotated bibliography?
ACM SIGOPS Operating Systems Review
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The problem of tracking end-to-end service-level transactions in the absence of instrumentation support is considered. The transaction instances progress through a state-transition model and generate time-stamped footprints on entering each state in the model. The goal is to track individual transactions using these footprints even when the footprints may not contain any tokens uniquely identifying the transaction instances that generated them. Assuming a semi-Markov process model for state transitions, the transaction instances are tracked probabilistically by matching them to the available footprints according to the maximum likelihood (ML) criterion. Under the ML-rule, for a two-state system, it is shown that the probability that all the instances are matched correctly is minimized when the transition times are i.i.d. exponentially distributed. When the transition times are i.i.d. distributed, the ML-rule reduces to a minimum weight bipartite matching and reduces further to a first-in first-out match for a special class of distributions. For a multi-state model with an acyclic state transition digraph, a constructive proof shows that the ML-rule reduces to splicing the results of independent matching of many bipartite systems.