Browsing by Author "Mireslami, Seyedehmehrnaz"

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    Cost and Performance Optimization for Cloud-Based Web Applications Deployment
    (2018-08-21) Mireslami, Seyedehmehrnaz; Far, Behrouz H.; Wang, Mea; Rakai, Logan M.; Moussavi, Mahmood
    Cloud computing offers a pool of various cloud resources, including scalable computing instances, database instances, storage, network bandwidth, etc. which are delivered to customers in an on-demand or reserved manner. In recent years, cloud computing has become a major enablement for businesses and researchers to reduce the deployment costs by externalizing their resources in the cloud environment. Achieving an optimal set of cloud resources for web application deployment among different public cloud providers is a challenge that becomes more difficult when cloud customers tend to optimize both deployment costs and Quality of Service (QoS). Furthermore, due to lack of understanding of the pricing model and the cloud IaaS, a customer may pay more than necessary or may not fully utilize the purchased resources. In this thesis, to tackle these challenges, first, a QoS-aware cost optimization algorithm is proposed that finds the most cost-effective cloud resources for web application deployment. The proposed algorithm maps the minimum required resources for the web application to minimize the deployment costs according to the price model set by the cloud providers. In the next stage, a multi-cloud datacenters cost optimization algorithm is proposed to distribute the cloud resources in different cloud datacenters to improve the web application availability and maintain QoS for geographically distributed user demands. To solve the cloud-based deployment problem from the cloud customer’s point of view, it is vital to balance the two conflicting objectives of deployment costs and QoS performance. Therefore, in this research, a multi-objective optimization algorithm is proposed that minimizes cost and maximizes QoS performance simultaneously by providing a balanced trade-off. Finally, a hybrid method to allocate resources according to the dynamic user demands is developed which includes the reservation and dynamic provision phases. The total deployment cost of each phase is formulated as the optimization objective and a stochastic optimization approach is developed to model the uncertainties in the user demands as random variables.
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    Verification of Multi-Agent Systems Using AUML Methodology
    (2013-09-13) Mireslami, Seyedehmehrnaz; Far, Behrouz H.
    Verification of Multi-Agent Systems (MAS) is vital since it results in reducing design costs. Agent UML (AUML) is a methodology for MAS design that is an extension of Unified Modeling Language (UML). Although UML is used for object-oriented designs, AUML can handle the interactions among agents to deal with agent-based designs. In this thesis, AUML is employed for designing MASs and a set of conversion rules is proposed to convert AUML notations into UML diagrams to be used for MAS verification. Emergent behaviour is a critical problem in MASs that leads to unexpected behaviours due to the assumptions of behaviour model synthesis, i.e. overgeneralization. The main contributions of this thesis are: 1) Designing multi-agent systems using AUML methodology and preparing scenarios for verification. 2) Developing a component-level approach for verifying multi-agent systems preventing overgeneralization. 3) Proposing a system-level algorithm to obtain comprehensive system behaviour analysis.