Cloud computing acts as a computing paradigm that aims to provide huge amount of computing in a fully virtualized manner by aggregating resources and thus offering a single system view. Cloud Computing is also delivered as utility assuring customized and quality of service guaranteed computation environments for cloud users. While an enterprise organization is composed of different departments like finance, admin etc these departments are segregated as sub network zone which are thus interconnected via network. Securities are essential for authorization of storage and computing. In this paper we have proposed a privacy cheating discouragement and computation auditing approach that bridging secure storage and computation auditing in cloud. Privacy cheating discouragement is designated by verifier signature, batch verification and probabilistic sampling techniques.
On-demand services and reduced costs made cloud computing a popular mechanism to provide scalable resources according to the user’s expectations. This paradigm is an important role in business and academic organizations, supporting applications and services deployed based on virtual machines and containers, two different technologies for virtualization. Cloud environments can support workloads generated by several numbers of users, that request the cloud environment to execute transactions and its performance should be evaluated and estimated in order to achieve clients satisfactions when cloud services are offered. This work proposes a performance evaluation strategy composed of a performance model and a methodology for evaluating the performance of services configured in virtual machines and containers in cloud infrastructures. The performance model for the evaluation of virtual machines and containers in cloud infrastructures is based on stochastic Petri nets. A case study in a real public cloud is presented to illustrate the feasibility of the performance evaluation strategy. The case study experiments were performed with virtual machines and containers supporting workloads related to social networks transactions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.