Measurement and modeling of computer reliability as affected by system activity
ACM Transactions on Computer Systems (TOCS)
Dynamic quorum adjustment for partitioned data
ACM Transactions on Database Systems (TODS)
Stochastic Petri Net Analysis of a Replicated File System
IEEE Transactions on Software Engineering
Performance Characterization of Quorum-Consensus Algorithms for Replicated Data
IEEE Transactions on Software Engineering
Increasing availability under mutual exclusion constraints with dynamic vote reassignment
ACM Transactions on Computer Systems (TOCS)
Dynamic voting algorithms for maintaining the consistency of a replicated database
ACM Transactions on Database Systems (TODS)
The generalized tree quorum protocol: an efficient approach for managing replicated data
ACM Transactions on Database Systems (TODS)
The UltraSAN modeling environment
Performance Evaluation - Special issue: performance modeling tools
A Majority consensus approach to concurrency control for multiple copy databases
ACM Transactions on Database Systems (TODS)
Optimizing Vote and Quorum Assignments for Reading and Writing Replicated Data
IEEE Transactions on Knowledge and Data Engineering
The Grid Protocol: A High Performance Scheme for Maintaining Replicated Data
Proceedings of the Sixth International Conference on Data Engineering
Stochastic Activity Networks: Structure, Behavior, and Application
International Workshop on Timed Petri Nets
Analyzing dynamic voting using Petri nets
SRDS '96 Proceedings of the 15th Symposium on Reliable Distributed Systems
Distributed and Parallel Databases
Proceedings of the 2004 ACM symposium on Applied computing
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Voting algorithms are a popular way to provide data consistency in replicated data systems. By maintaining multiple copies of data on distinct servers, they can increase the data's availability, as perceived by a user. Many models have been made to study the degree to which replication increases the availability of data, and some have been made to study the cost incurred in maintaining consistency. However, little work has been done to evaluate the time it takes to serve a request, accounting for server and network failures, or to determine the effect of workload on these measures. The effect of workload can be significant, since failures of system components are not important unless they are needed to deliver a service, and requests can force updates on data that would otherwise be outdated. In this paper, with the help of stochastic activity networks, we determine the availability and mean time to respond to write requests as a function of the number of replicated copies and workload offered to the system. The results illustrate that it is indeed possible to determine such measures analytically and that workload, as well as the number of copies, is an important determinant of availability and response time.