PETRI NET MODELLING OF CONCURRENCY CONTROL IN DISTRIBUTED DATABASE SYSTEM

The life time of transaction is divided into two stages: executing stage and committing stage. At the executing stage, transaction access data through a concurrency control, while at the committing stage, a commit protocol is executed to ensure failure atomicity. A transaction that requests a lock can be blocked by a committing transaction for a long time due to a long delay in completing the committing procedure. The potential long delay in transaction commitment makes concurrency control wait until transaction finish the committing stage. This study will modify concurrency control, the modified of concurrency control allows give the locks that are still on hold by another transaction in their completion of committing stage. In modeling the concurrency control, Petri Net is used. The simulation has show increase the commit throughput of transaction, but the issue of abort transaction has significant impact to modified concurrency control, the simulation has show increase the abort throughput of transaction

Asynchronous island model genetic algorithm for university course timetabling

University course timetabling problem (UCTP) is similar to general timetabling problems with some additional unique parts. UCTP involves assigning lecture events to timeslots and rooms subject to a variety of hard and soft constraints. Telkom University has almost similar problem with its course timetabling. The current solution with Informed Genetic Algorithm for Telkom University UCTP still has the time consuming problem. Island Model informed Genetic Algorithm was used in this research to solve this problem. The idea of this research is making distributed model exchanges an island’s local best Individu with another island. Island model GA could create university course timetabling in reasonable time. This distributed model could run faster rather than single machine model decreasing constraint violations to reach optimum fitness. It could have less constraint violations because it could escape from stagnant local optimum easier. Island model GA could even produce great accuracy for Telkom University dataset (99.74%) and acceptable accuracy at 96.80% for Purdue dataset for student level timetabling.</p