Trustworthiness Measurement Algorithm for TWfMS Based on Software Behaviour Entropy

As the virtual mirror of complex real-time business processes of organisations’ underlying information systems, the workflow management system (WfMS) has emerged in recent decades as a new self-autonomous paradigm in the open, dynamic, distributed computing environment. In order to construct a trustworthy workflow management system (TWfMS), the design of a software behaviour trustworthiness measurement algorithm is an urgent task for researchers. Accompanying the trustworthiness mechanism, the measurement algorithm, with uncertain software behaviour trustworthiness information of the WfMS, should be resolved as an infrastructure. Based on the framework presented in our research prior to this paper, we firstly introduce a formal model for the WfMS trustworthiness measurement, with the main property reasoning based on calculus operators. Secondly, this paper proposes a novel measurement algorithm from the software behaviour entropy of calculus operators through the principle of maximum entropy (POME) and the data mining method. Thirdly, the trustworthiness measurement algorithm for incomplete software behaviour tests and runtime information is discussed and compared by means of a detailed explanation. Finally, we provide conclusions and discuss certain future research areas of the TWfMS.

[1]  Jianmin Wang,et al.  A workflow net similarity measure based on transition adjacency relations , 2010, Comput. Ind..

[2]  Jianmin Wang,et al.  A label-free similarity measure between workflow nets , 2009, 2009 IEEE Asia-Pacific Services Computing Conference (APSCC).

[3]  Stefano A. Lollai,et al.  Quality Systems. A Thermodynamics-Related Interpretive Model , 2017, Entropy.

[4]  Michael Zur Muehlen,et al.  Workflow-based Process Controlling - Or: What You Can Measure You Can Control , 2001 .

[5]  Haiyan Zhao,et al.  A software architecture centric engineering approach for Internetware , 2006, Science in China Series F: Information Sciences.

[6]  Dawn-Marie Chin.  A definition and measure of workflow modularity , 2005 .

[7]  Han Qian.  Research on trustworthiness measurement approaches of component based BPRAS , 2014 .

[8]  Minglu Li,et al.  Workflow Similarity Measure for Process Clustering in Grid , 2007, Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007).

[9]  J. N. Kapur.  Maximum-entropy models in science and engineering , 1992 .

[10]  Rong Jiang,et al.  A Trustworthiness Evaluation Method for Software Architectures Based on the Principle of Maximum Entropy (POME) and the Grey Decision-Making Method (GDMM) , 2014, Entropy.

[11]  Azad M. Madni,et al.  Towards a Conceptual Framework for Resilience Engineering , 2009, IEEE Systems Journal.

[12]  Bo Terje Kalsaas,et al.  To Measure Workflow and Waste. A Concept for Continuous Improvement , 2014 .

[13]  Qiang Han,et al.  A Software Behavior Trustworthiness Measurement Method based on Data Mining , 2011 .

[14]  Eamonn J. Keogh,et al.  Clustering Workflow Requirements Using Compression Dissimilarity Measure , 2006, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06).

[15]  Therese M Jorwic,et al.  A new focus on process and measure. Raising data quality with a standard coding workflow and benchmarks. , 2008, Journal of AHIMA.

[16]  Jun Wei,et al.  Cost and accuracy aware scientific workflow retrieval based on distance measure , 2015, Inf. Sci..

[17]  Quan Long,et al.  Uncertainty Analysis in Software Reliability Modeling by Bayesian Analysis with Maximum-Entropy Principle , 2007, IEEE Transactions on Software Engineering.

[18]  Han Qiang,et al.  Data Mining Based Measurement Method for Software Trustworthiness , 2010, 2010 International Symposium on Intelligence Information Processing and Trusted Computing.