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I hereby declare that I am the sole author of this thesis. I authorize Ryerson University to lend this thesis to other institutions or individuals for the purpose of scholarly research. I further authorize Ryerson University to reproduce this thesis by photocopying or by other means, in total or in part, at the request of other institutions or individuals(More)
—Accurate availability and performance analysis are important requirements to guarantee quality of services (QoS) for cloud users. In this paper, we develop an analytical performance and availability model using interacting stochastic sub-models. Each sub-model captures a specific aspect of cloud centers. The key performance metrics such as task blocking(More)
Performance modeling of cloud computing centers is a challenging task due to complexity, shared resources and large scale of such systems. Introducing heterogeneous resources and workloads make the analysis even more complicated. In this paper, we propose a layered stochastic performance model applicable to cloud centers with wide range of heterogeneous(More)
This paper proposes and evaluates a novel analytical performance model to study the efficiency and scalability of software-defined infrastructure (SDI) to host adaptive applications. The SDI allows applications to communicate their adaptation requirements at run-time. Adaptation scenarios require computing and networking resources to be provided to(More)
Distributed Denial of Service (DDoS) attacks are one of the main concerns for online service providers because of their impact on cost/revenue and reputation. This paper presents Completely Automated DDoS Attack Mitigation Platform (CAAMP), a novel platform to mitigate DDoS attacks on public cloud applications using capabilities of software defined(More)
Microservice architecture has started a new trend for application development/deployment in cloud due to its flexibility, scalability, manageability and performance. Various microservice platforms have emerged to facilitate the whole software engineering cycle for cloud applications from design, development, test, deployment to maintenance. In this paper,(More)
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