Advances in Petri nets 1986, part II on Petri nets: applications and relationships to other models of concurrency
Sequential and concurrent behaviour in Petri net theory
Theoretical Computer Science
OPTICS: ordering points to identify the clustering structure
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Event detection from time series data
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
The Vision of Autonomic Computing
Computer
A unifying framework for detecting outliers and change points from non-stationary time series data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Service-Oriented Architecture: Concepts, Technology, and Design
Service-Oriented Architecture: Concepts, Technology, and Design
Detecting changes in large data sets of payment card data: a case study
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE Intelligent Systems
History-based joins: Semantics, soundness and implementation
Data & Knowledge Engineering
Business transformation to SOA: aspects of the migration and performance and QoS issues
Proceedings of the 2nd international workshop on Systems development in SOA environments
Proceedings of the VLDB Endowment
Workflow-based resource allocation to optimize overall performance of composite services
Future Generation Computer Systems
Resource Management in the Autonomic Service-Oriented Architecture
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
ICATPN'07 Proceedings of the 28th international conference on Applications and theory of Petri nets and other models of concurrency
SENECA – simulation of algorithms for the selection of web services for compositions
TES'05 Proceedings of the 6th international conference on Technologies for E-Services
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Service orientation is rapidly becoming the common practice in the IT world. A price one often has to pay for the advantages of service oriented architectures (SOA) is performance deterioration. SOA performance heavily depends on the allocation of computational resources to services. The needs of services in computational resources are however changing, depending e.g. on the environmental factors and changes in business processes (and hence service orchestrations). To ensure good performance results, the resource allocation should respond to the changes in the SOA environment. In this paper we focus on the detection of the changes in the environment and the prediction of the expected service requests rates. For this purpose we first discover a stochastic model of the service request rates. Then we monitor the system to detect changes in the environment behaviour and signal the necessity to reconsider the resource allocation, providing a prediction of the service request rates for the coming period. Moreover, we monitor whether the model is still a fair reflection of the behaviour, and when necessary, we adapt the model appropriately.