Matching Items (6)
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- All Subjects: SaaS
- All Subjects: Modeling
- Creators: Sarjoughian, Hessam S.
Description
A new algebraic system, Test Algebra (TA), is proposed for identifying faults in combinatorial testing for SaaS (Software-as-a-Service) applications. In the context of cloud computing, SaaS is a new software delivery model, in which mission-critical applications are composed, deployed, and executed on cloud platforms. Testing SaaS applications is challenging because new applications need to be tested once they are composed, and prior to their deployment. A composition of components providing services yields a configuration providing a SaaS application. While individual components
in the configuration may have been thoroughly tested, faults still arise due to interactions among the components composed, making the configuration faulty. When there are k components, combinatorial testing algorithms can be used to identify faulty interactions for t or fewer components, for some threshold 2 <= t <= k on the size of interactions considered. In general these methods do not identify specific faults, but rather indicate the presence or absence of some fault. To identify specific faults, an adaptive testing regime repeatedly constructs and tests configurations in order to determine, for each interaction of interest, whether it is faulty or not. In order to perform such testing in a loosely coupled distributed environment such as
the cloud, it is imperative that testing results can be combined from many different servers. The TA defines rules to permit results to be combined, and to identify the faulty interactions. Using the TA, configurations can be tested concurrently on different servers and in any order. The results, using the TA, remain the same.
in the configuration may have been thoroughly tested, faults still arise due to interactions among the components composed, making the configuration faulty. When there are k components, combinatorial testing algorithms can be used to identify faulty interactions for t or fewer components, for some threshold 2 <= t <= k on the size of interactions considered. In general these methods do not identify specific faults, but rather indicate the presence or absence of some fault. To identify specific faults, an adaptive testing regime repeatedly constructs and tests configurations in order to determine, for each interaction of interest, whether it is faulty or not. In order to perform such testing in a loosely coupled distributed environment such as
the cloud, it is imperative that testing results can be combined from many different servers. The TA defines rules to permit results to be combined, and to identify the faulty interactions. Using the TA, configurations can be tested concurrently on different servers and in any order. The results, using the TA, remain the same.
ContributorsQi, Guanqiu (Author) / Tsai, Wei-Tek (Thesis advisor) / Davulcu, Hasan (Committee member) / Sarjoughian, Hessam S. (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2014
DescriptionThe thesis will study price optimization techniques, SaaS industry pricing structures, A/B testing, and then build a unique framework to optimize price and maximize revenue. The ultimate goal of the thesis research is to create a framework that identifies the best pricing structure and price points for a SaaS company.
ContributorsRyu, Kibaek (Author) / Clark, Joseph (Thesis director) / Granberry, Chase (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor)
Created2014-05
Description
Nowadays, Computing is so pervasive that it has become indeed the 5th utility (after water, electricity, gas, telephony) as Leonard Kleinrock once envisioned. Evolved from utility computing, cloud computing has emerged as a computing infrastructure that enables rapid delivery of computing resources as a utility in a dynamically scalable, virtualized manner. However, the current industrial cloud computing implementations promote segregation among different cloud providers, which leads to user lockdown because of prohibitive migration cost. On the other hand, Service-Orented Computing (SOC) including service-oriented architecture (SOA) and Web Services (WS) promote standardization and openness with its enabling standards and communication protocols. This thesis proposes a Service-Oriented Cloud Computing Architecture by combining the best attributes of the two paradigms to promote an open, interoperable environment for cloud computing development. Mutil-tenancy SaaS applicantions built on top of SOCCA have more flexibility and are not locked down by a certain platform. Tenants residing on a multi-tenant application appear to be the sole owner of the application and not aware of the existence of others. A multi-tenant SaaS application accommodates each tenant’s unique requirements by allowing tenant-level customization. A complex SaaS application that supports hundreds, even thousands of tenants could have hundreds of customization points with each of them providing multiple options, and this could result in a huge number of ways to customize the application. This dissertation also proposes innovative customization approaches, which studies similar tenants’ customization choices and each individual users behaviors, then provides guided semi-automated customization process for the future tenants. A semi-automated customization process could enable tenants to quickly implement the customization that best suits their business needs.
ContributorsSun, Xin (Author) / Tsai, Wei-Tek (Thesis advisor) / Xue, Guoliang (Committee member) / Davulcu, Hasan (Committee member) / Sarjoughian, Hessam S. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Software-as-a-Service (SaaS) has received significant attention in recent years as major computer companies such as Google, Microsoft, Amazon, and Salesforce are adopting this new approach to develop software and systems. Cloud computing is a computing infrastructure to enable rapid delivery of computing resources as a utility in a dynamic, scalable, and virtualized manner. Computer Simulations are widely utilized to analyze the behaviors of software and test them before fully implementations. Simulation can further benefit SaaS application in a cost-effective way taking the advantages of cloud such as customizability, configurability and multi-tendency.
This research introduces Modeling, Simulation and Analysis for Software-as-Service in Cloud. The researches cover the following topics: service modeling, policy specification, code generation, dynamic simulation, timing, event and log analysis. Moreover, the framework integrates current advantages of cloud: configurability, Multi-Tenancy, scalability and recoverability.
The following chapters are provided in the architecture:
Multi-Tenancy Simulation Software-as-a-Service.
Policy Specification for MTA simulation environment.
Model Driven PaaS Based SaaS modeling.
Dynamic analysis and dynamic calibration for timing analysis.
Event-driven Service-Oriented Simulation Framework.
LTBD: A Triage Solution for SaaS.
This research introduces Modeling, Simulation and Analysis for Software-as-Service in Cloud. The researches cover the following topics: service modeling, policy specification, code generation, dynamic simulation, timing, event and log analysis. Moreover, the framework integrates current advantages of cloud: configurability, Multi-Tenancy, scalability and recoverability.
The following chapters are provided in the architecture:
Multi-Tenancy Simulation Software-as-a-Service.
Policy Specification for MTA simulation environment.
Model Driven PaaS Based SaaS modeling.
Dynamic analysis and dynamic calibration for timing analysis.
Event-driven Service-Oriented Simulation Framework.
LTBD: A Triage Solution for SaaS.
ContributorsLi, Wu (Author) / Tsai, Wei-Tek (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Ye, Jieping (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2015
Description
Computational models for relatively complex systems are subject to many difficulties, among which is the ability for the models to be discretely understandable and applicable to specific problem types and their solutions. This demands the specification of a dynamic system as a collection of models, including metamodels. In this context, new modeling approaches and tools can help provide a richer understanding and, therefore, the development of sophisticated behavior in system dynamics. From this vantage point, an activity specification is proposed as a modeling approach based on a time-based discrete event system abstraction. Such models are founded upon set-theoretic principles and methods for modeling and simulation with the intent of making them subject to specific and profound questions for user-defined experiments.
Because developing models is becoming more time-consuming and expensive, some research has focused on the acquisition of concrete means targeted at the early stages of component-based system analysis and design. The model-driven architecture (MDA) framework provides some means for the behavioral modeling of discrete systems. The development of models can benefit from simplifications and elaborations enabled by the MDA meta-layers, which is essential for managing model complexity. Although metamodels pose difficulties, especially for developing complex behavior, as opposed to structure, they are advantageous and complementary to formal models and concrete implementations in programming languages.
The developed approach is focused on action and control concepts across the MDA meta-layers and is proposed for the parallel Discrete Event System Specification (P-DEVS) formalism. The Unified Modeling Language (UML) activity meta-models are used with syntax and semantics that conform to the DEVS formalism and its execution protocol. The notions of the DEVS component and state are used together according to their underlying system-theoretic foundation. A prototype tool supporting activity modeling was developed to demonstrate the degree to which action-based behavior can be modeled using the MDA and DEVS. The parallel DEVS, as a formal approach, supports identifying the semantics of the UML activities. Another prototype was developed to create activity models and support their execution with the DEVS-Suite simulator, and a set of prototypical multiprocessor architecture model specifications were designed, simulated, and analyzed.
Because developing models is becoming more time-consuming and expensive, some research has focused on the acquisition of concrete means targeted at the early stages of component-based system analysis and design. The model-driven architecture (MDA) framework provides some means for the behavioral modeling of discrete systems. The development of models can benefit from simplifications and elaborations enabled by the MDA meta-layers, which is essential for managing model complexity. Although metamodels pose difficulties, especially for developing complex behavior, as opposed to structure, they are advantageous and complementary to formal models and concrete implementations in programming languages.
The developed approach is focused on action and control concepts across the MDA meta-layers and is proposed for the parallel Discrete Event System Specification (P-DEVS) formalism. The Unified Modeling Language (UML) activity meta-models are used with syntax and semantics that conform to the DEVS formalism and its execution protocol. The notions of the DEVS component and state are used together according to their underlying system-theoretic foundation. A prototype tool supporting activity modeling was developed to demonstrate the degree to which action-based behavior can be modeled using the MDA and DEVS. The parallel DEVS, as a formal approach, supports identifying the semantics of the UML activities. Another prototype was developed to create activity models and support their execution with the DEVS-Suite simulator, and a set of prototypical multiprocessor architecture model specifications were designed, simulated, and analyzed.
ContributorsAlshareef, Abdurrahman (Author) / Sarjoughian, Hessam S. (Thesis advisor) / Fainekos, Georgios (Committee member) / Lee, Joohyung (Committee member) / Zhao, Ming (Committee member) / Arizona State University (Publisher)
Created2019
Description
Component simulation models, such as agent-based models, may depend on spatial data associated with geographic locations. Composition of such models can be achieved using a Geographic Knowledge Interchange Broker (GeoKIB) enabled with spatial-temporal data transformation functions, each of which is responsible for a set of interactions between two independent models. The use of autonomous interaction models allows model composition without alteration of the composed component models. An interaction model must handle differences in the spatial resolutions between models, in addition to differences in their temporal input/output data types and resolutions.
A generalized GeoKIB was designed that regulates unidirectional spatially-based interactions between composed models. Different input and output data types are used for the interaction model, depending on whether data transfer should be passive or active. Synchronization of time-tagged input/output values is made possible with the use of dependency on a discrete simulation clock. An algorithm supporting spatial conversion is developed to transform any two-dimensional geographic data map between different region specifications. Maps belonging to the composed models can have different regions, map cell sizes, or boundaries. The GeoKIB can be extended based on the model specifications to be composed and the target application domain.
Two separate, simplistic models were created to demonstrate model composition via the GeoKIB. An interaction model was created for each of the two directions the composed models interact. This exemplar is developed to demonstrate composition and simulation of geographic-based component models.
A generalized GeoKIB was designed that regulates unidirectional spatially-based interactions between composed models. Different input and output data types are used for the interaction model, depending on whether data transfer should be passive or active. Synchronization of time-tagged input/output values is made possible with the use of dependency on a discrete simulation clock. An algorithm supporting spatial conversion is developed to transform any two-dimensional geographic data map between different region specifications. Maps belonging to the composed models can have different regions, map cell sizes, or boundaries. The GeoKIB can be extended based on the model specifications to be composed and the target application domain.
Two separate, simplistic models were created to demonstrate model composition via the GeoKIB. An interaction model was created for each of the two directions the composed models interact. This exemplar is developed to demonstrate composition and simulation of geographic-based component models.
ContributorsBoyd, William Angelo (Author) / Sarjoughian, Hessam S. (Thesis advisor) / Maciejewski, Ross (Committee member) / Sarwat, Mohamed (Committee member) / Arizona State University (Publisher)
Created2019