Name
Abstract | ||
|---|---|---|
Distributed shared logs are a powerful building block for distributed systems. By providing fault-tolerant persistence and strong ordering guarantees, applications can use a distributed shared log to reliably communicate a stream of events between processes. This can be used, for example, to replicate application state or to build a reliable publish/subscribe system. The log itself must also replicate data in order to provide availability and fault-tolerance. Key to the design of a distributed shared log is the choice of replication algorithm, which will determine many properties of the system.
We propose an algorithm for consistent replication of log data, quorum-replication with meta-data exchange (QMX), that is linearizable while allowing writes to be successful with only a single round-trip to a quorum of replicas and allowing reads to generally be serviced by any single replica, or read-one/write-quorum. This is achieved by coupling the reads with an asynchronous message exchange algorithm that continuously runs amongst the replicas. The message exchange algorithm allows replicas to infer the global state of writes across the cluster, in order to deduce which writes have been successfully quorum replicated and which have not. This metadata allows any single replica to directly answer reads in many cases, though in the worst case a read must wait for the message passing round to complete before being serviced which requires a majority quorum of servers to be responsive.
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Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3127479.3132695 | SoCC '17: ACM Symposium on Cloud Computing
Santa Clara
California
September, 2017 |
Field | DocType | ISBN |
Metadata,Asynchronous communication,Replica,Data analysis,Computer science,Server,Computer network,Real-time computing,Software-defined networking,Replicate,Message passing,Distributed computing | Conference | 978-1-4503-5028-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hua Fan | 1 | 14 | 6.04 |
| Jeffrey Pound | 2 | 356 | 22.21 |
| Peter Bumbulis | 3 | 59 | 5.78 |
| Nathan Auch | 4 | 13 | 1.33 |
| Scott MacLean | 5 | 13 | 1.33 |
| Eric Garber | 6 | 0 | 0.34 |
| Anil K. Goel | 7 | 98 | 57.69 |