z-logo
Premium
The M / G /∞ Queueing Model for Optimistic Concurrency Control
Author(s) -
Sassen S. A. E.,
Van Der Wal J.
Publication year - 2000
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/1467-9574.00136
Subject(s) - computer science , server , distributed transaction , transaction processing , concurrency control , database transaction , serializability , optimistic concurrency control , online transaction processing , concurrency , distributed computing , queue , queueing theory , transaction processing system , database , service (business) , operating system , computer network , distributed concurrency control , economy , economics
The M / G /∞ queue with Optimistic Concurrency Control (OCC) is a model for a special form of parallel transaction processing in a real‐time database. Transactions arrive according to a Poisson process and require some generally distributed execution time. One of the differences with ordinary multi‐ and infinite‐server queueing models is that under OCC the successful completion of one transaction may immediately cause the failure of one or more of the other transactions. This happens if the completing transaction has overwritten a data‐item that is in use by another transaction in progress. As soon as this failure is detected the failed transaction is restarted. So the total service time of a transaction consists of its final successful run and the time spent on unsuccessful runs. In this study we develop an approximation for the distribution of the total service time, and test the approximation against simulation. Although in practice the number of servers is never unlimited, this study provides valuable insight in the asymptotics with respect to the number of servers. The approximation clearly demonstrates the very limited performance gain from an increase of the number of servers.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here