Behavioral modeling and formal verification of a resource discovery approach in Grid computing

•Presenting a resource discovery approach to address multi-attribute and range queries.•Modeling the behaviors of proposed approach.•Analyzing the soundness, completeness, and consistency as a model checking problem.•Translating the design model into a verifiable formal model.•Implementing the behav...

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Vydáno v:	Expert systems with applications Ročník 41; číslo 8; s. 3831 - 3849
Hlavní autoři:	Souri, Alireza, Jafari Navimipour, Nima
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier Ltd 15.06.2014 Elsevier
Témata:	Applied sciences Behavioral modeling Checkers Completeness Computational grids Computer science; control theory; systems Computer systems and distributed systems. User interface Computer systems performance. Reliability Consistency Exact sciences and technology Expert systems Formal verification Grid computing Information systems. Data bases Mathematical models Memory organisation. Data processing Model checking NuSMV Queries Resource discovery Software Software engineering Behavioral modeling Model checking Grid computing NuSMV Resource discovery Formal verification Resource allocation Grid Web service State space Distributed computing Modeling Behavioral analysis Completeness Static analysis Defect Localization High performance Branching temporal logic CTL Resource sharing State space method Behavior model Program verification Range query Soundness Problem solving Internet Resource management
ISSN:	0957-4174, 1873-6793
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Abstract	•Presenting a resource discovery approach to address multi-attribute and range queries.•Modeling the behaviors of proposed approach.•Analyzing the soundness, completeness, and consistency as a model checking problem.•Translating the design model into a verifiable formal model.•Implementing the behavior models by ArgoUML tool and the NuSMV model checker. Grid computing is the federation of resources from multiple locations to facilitate resource sharing and problem solving over the Internet. The challenge of finding services or resources in Grid environments has recently been the subject of many papers and researches. These researches and papers evaluate their approaches only by simulation and experiments. Therefore, it is possible that some part of the state space of the problem is not analyzed and checked well. To overcome this defect, model checking as an automatic technique for the verification of the systems is a suitable solution. In this paper, an adopted type of resource discovery approach to address multi-attribute and range queries has been presented. Unlike the papers in this scope, this paper decouple resource discovery behavior model to data gathering, discovery and control behavior. Also it facilitates the mapping process between three behaviors by means of the formal verification approach based on Binary Decision Diagram (BDD). The formal approach extracts the expected properties of resource discovery approach from control behavior in the form of CTL and LTL temporal logic formulas, and verifies the properties in data gathering and discovery behaviors comprehensively. Moreover, analyzing and evaluating the logical problems such as soundness, completeness, and consistency of the considered resource discovery approach is provided. To implement the behavior models of resource discovery approach the ArgoUML tool and the NuSMV model checker are employed. The results show that the adopted resource discovery approach can discovers multi-attribute and range queries very fast and detects logical problems such as soundness, completeness, and consistency.
AbstractList	Grid computing is the federation of resources from multiple locations to facilitate resource sharing and problem solving over the Internet. The challenge of finding services or resources in Grid environments has recently been the subject of many papers and researches. These researches and papers evaluate their approaches only by simulation and experiments. Therefore, it is possible that some part of the state space of the problem is not analyzed and checked well. To overcome this defect, model checking as an automatic technique for the verification of the systems is a suitable solution. In this paper, an adopted type of resource discovery approach to address multi-attribute and range queries has been presented. Unlike the papers in this scope, this paper decouple resource discovery behavior model to data gathering, discovery and control behavior. Also it facilitates the mapping process between three behaviors by means of the formal verification approach based on Binary Decision Diagram (BDD). The formal approach extracts the expected properties of resource discovery approach from control behavior in the form of CIL and LTL temporal logic formulas, and verifies the properties in data gathering and discovery behaviors comprehensively. Moreover, analyzing and evaluating the logical problems such as soundness, completeness, and consistency of the considered resource discovery approach is provided. To implement the behavior models of resource discovery approach the ArgoUML tool and the NuSMV model checker are employed. The results show that the adopted resource discovery approach can discovers multi-attribute and range queries very fast and detects logical problems such as soundness, completeness, and consistency. •Presenting a resource discovery approach to address multi-attribute and range queries.•Modeling the behaviors of proposed approach.•Analyzing the soundness, completeness, and consistency as a model checking problem.•Translating the design model into a verifiable formal model.•Implementing the behavior models by ArgoUML tool and the NuSMV model checker. Grid computing is the federation of resources from multiple locations to facilitate resource sharing and problem solving over the Internet. The challenge of finding services or resources in Grid environments has recently been the subject of many papers and researches. These researches and papers evaluate their approaches only by simulation and experiments. Therefore, it is possible that some part of the state space of the problem is not analyzed and checked well. To overcome this defect, model checking as an automatic technique for the verification of the systems is a suitable solution. In this paper, an adopted type of resource discovery approach to address multi-attribute and range queries has been presented. Unlike the papers in this scope, this paper decouple resource discovery behavior model to data gathering, discovery and control behavior. Also it facilitates the mapping process between three behaviors by means of the formal verification approach based on Binary Decision Diagram (BDD). The formal approach extracts the expected properties of resource discovery approach from control behavior in the form of CTL and LTL temporal logic formulas, and verifies the properties in data gathering and discovery behaviors comprehensively. Moreover, analyzing and evaluating the logical problems such as soundness, completeness, and consistency of the considered resource discovery approach is provided. To implement the behavior models of resource discovery approach the ArgoUML tool and the NuSMV model checker are employed. The results show that the adopted resource discovery approach can discovers multi-attribute and range queries very fast and detects logical problems such as soundness, completeness, and consistency. Grid computing is the federation of resources from multiple locations to facilitate resource sharing and problem solving over the Internet. The challenge of finding services or resources in Grid environments has recently been the subject of many papers and researches. These researches and papers evaluate their approaches only by simulation and experiments. Therefore, it is possible that some part of the state space of the problem is not analyzed and checked well. To overcome this defect, model checking as an automatic technique for the verification of the systems is a suitable solution. In this paper, an adopted type of resource discovery approach to address multi-attribute and range queries has been presented. Unlike the papers in this scope, this paper decouple resource discovery behavior model to data gathering, discovery and control behavior. Also it facilitates the mapping process between three behaviors by means of the formal verification approach based on Binary Decision Diagram (BDD). The formal approach extracts the expected properties of resource discovery approach from control behavior in the form of CTL and LTL temporal logic formulas, and verifies the properties in data gathering and discovery behaviors comprehensively. Moreover, analyzing and evaluating the logical problems such as soundness, completeness, and consistency of the considered resource discovery approach is provided. To implement the behavior models of resource discovery approach the ArgoUML tool and the NuSMV model checker are employed. The results show that the adopted resource discovery approach can discovers multi-attribute and range queries very fast and detects logical problems such as soundness, completeness, and consistency.
Author	Jafari Navimipour, Nima Souri, Alireza
Author_xml	– sequence: 1 givenname: Alireza surname: Souri fullname: Souri, Alireza email: alireza.souri@iauasrb.ac.ir – sequence: 2 givenname: Nima surname: Jafari Navimipour fullname: Jafari Navimipour, Nima email: jafari@iauasrb.ac.ir
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Keywords	Behavioral modeling Model checking Grid computing NuSMV Resource discovery Formal verification Resource allocation Grid Web service State space Distributed computing Modeling Behavioral analysis Completeness Static analysis Defect Localization High performance Branching temporal logic CTL Resource sharing State space method Behavior model Program verification Range query Soundness Problem solving Internet Resource management
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Snippet	•Presenting a resource discovery approach to address multi-attribute and range queries.•Modeling the behaviors of proposed approach.•Analyzing the soundness,... Grid computing is the federation of resources from multiple locations to facilitate resource sharing and problem solving over the Internet. The challenge of...
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SubjectTerms	Applied sciences Behavioral modeling Checkers Completeness Computational grids Computer science; control theory; systems Computer systems and distributed systems. User interface Computer systems performance. Reliability Consistency Exact sciences and technology Expert systems Formal verification Grid computing Information systems. Data bases Mathematical models Memory organisation. Data processing Model checking NuSMV Queries Resource discovery Software Software engineering
Title	Behavioral modeling and formal verification of a resource discovery approach in Grid computing
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