Abstract
AbstractThis paper outlines the results that were collected from the implementation of the COPAR Service [5][6] in an Opnet Modeler simulation environment. The system carries out two (2) types of transaction processing techniques; Optimistic (Temporary) and Pessimistic (Permanent) Processing. The Opnet simulation environment was used to expand the projects capacity by increasing the number of servers and transactions that could be processed by the system. Results show the processing times for simulations that ran with nodes ranging from 20 to 100 nodes and transactions ranging from 200 to 1000.Results also showed statistics for the distribution of transactions amongst servers with different classifications. Classifications of server ranged from 1 to 6, 1 being the lowest and 6 being the highest. The number of transactions used for testing transaction distribution ranged from 1000 up to 4000, with each simulation run using 100 server nodes. These results can act as a guide to help implement systems that can provide optimal processing times in a real world environment.
Highlights
The COPAR service today is still running as a Java based system that runs off of 8 nodes located in the USA and the Caribbean (Trinidad)
Results for Optimistic and Pessimistic processing times are based on input parameters of 20 to 100 nodes with 200 to 1000 transactions
Optimistic processing results are divided into local optimistic processing only vs. local and remote optimistic processing
Summary
The COPAR service today is still running as a Java based system that runs off of 8 nodes located in the USA and the Caribbean (Trinidad). Developments and upgrades on the COPAR system have been ongoing for the last 16 years with versions written in C/C++ and Java Improvements on this project have been outlined in several papers [2] [3][4]. Recent enhancements to this project involved the implementation of COPAR using the OPNET modeler simulation environment. Simulations were run with varying number of transactions, server nodes and cost bound resource; these were three main inputs. Other input parameters include the transaction delay. Results for Optimistic and Pessimistic processing times are based on input parameters of 20 to 100 nodes with 200 to 1000 transactions. Transaction distribution results were collected for simulations running 100 nodes with 1000 to 4000 transactions
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