SMT-Based Modeling and Verification of Cloud Applications

Cloud applications have been rapidly evolving and gained more and more attention in the past decade. Formal modeling and verification of cloud services are necessarily needed to guarantee their correctness and reliability of complex cloud applications. In this paper, we present a formal framework for modeling and verification of cloud applications based on the SMT solver Z3. Simple cloud services are specified as the basis for the modeling of composition and more complex cloud services. Three different classes Service, Composition and Cloud indicating simple cloud services, composition patterns and composed cloud services are defined, which facilitates the further development of attributes and methods. We also propose an approach to check the refinement and equivalence relations between cloud services, in which counter examples can be automatically generated when the relation is not valid.

[1]  Meng Sun,et al.  A Formal Design Model for Cloud Services , 2017, SEKE.

[2]  Xiao Ma,et al.  Monitoring-Based Task Scheduling in Large-Scale SaaS Cloud , 2016, ICSOC.

[3]  Faiza Belala,et al.  Towards a Formal Model for Cloud Computing , 2013, ICSOC Workshops.

[4]  Yunxiang Liu,et al.  Modeling and analyzing cost-aware fault tolerant strategy for cloud application , 2016, SEKE.

[5]  Nikolaj Bjørner,et al.  Z3: An Efficient SMT Solver , 2008, TACAS.

[6]  Meng Sun,et al.  Using PVS for Modeling and Verifying Cloud Services and Their Composition , 2018, 2018 Sixth International Conference on Advanced Cloud and Big Data (CBD).

[7]  Jifeng He,et al.  rCOS: A refinement calculus of object systems , 2006, Theor. Comput. Sci..

[8]  Kwang Mong Sim,et al.  Agent-Based Cloud Computing , 2012, IEEE Transactions on Services Computing.

[9]  Jun Sun,et al.  Towards Formal Modeling and Verification of Cloud Architectures: A Case Study on Hadoop , 2013, 2013 IEEE Ninth World Congress on Services.

[10]  Ivan Porres,et al.  Integrating Event-B Modelling and Discrete-Event Simulation to Analyse Resilience of Data Stores in the Cloud , 2014, IFM.

[11]  Paul Watson,et al.  Formalising Workflows Partitioning over Federated Clouds: Multi-level Security and Costs , 2012, 2012 IEEE Eighth World Congress on Services.

[12]  Kim G. Larsen,et al.  A Cost/Reward Method for Optimal Infinite Scheduling in Mobile Cloud Computing , 2015, FACS.

[13]  Farhad Arbab,et al.  Connectors as designs: Modeling, refinement and test case generation , 2012, Sci. Comput. Program..

[14]  Amel Mammar,et al.  Towards Correct Cloud Resource Allocation in Business Processes , 2017, IEEE Transactions on Services Computing.

[15]  Haiping Xu,et al.  A RAID-Based Secure and Fault-Tolerant Model for Cloud Information Storage , 2013, Int. J. Softw. Eng. Knowl. Eng..

[16]  Hana Chockler,et al.  HiFrog: SMT-based Function Summarization for Software Verification , 2017, TACAS.