Business Process Workflow Monitoring Using Distributed CBR with GPU Computing

Workflow monitoring and diagnosis can be a complex process
involving sophisticated computational intensive operations.
The ever-growing data generation and its utilisation
have increased the complexity of workflow domains leading
to an increased interest in distributed approaches for efficient
workflow monitoring. Existing work has proposed a
CBR enhancement to tackle deficiencies in areas where data
volumes increase significantly. In such areas, the notion of a
“data volume” component was proposed in an enhanced
CBR architecture. This work proceeds further by evaluating
a proposed distributed CBR lifecycle based on GPU programming
to abstract further and evaluate the hypothesis
that: increased data volumes can be tackled efficiently using
distributed case bases and processing on demand. Our proposed
approach is evaluated against previous work and it
shows promising speedup gains. This paper signposts future
research areas in distributed CBR paradigms,