Performance-oriented Cloud Provisioning: Taxonomy and Survey

Cloud computing is being viewed as the technology of today and the future. Through this paradigm, the customers gain access to shared computing resources located in remote data centers that are hosted by cloud providers (CP). This technology allows for provisioning of various resources such as virtual machines (VM), physical machines, processors, memory, network, storage and software as per the needs of customers. Application providers (AP), who are customers of the CP, deploy applications on the cloud infrastructure and then these applications are used by the end-users. To meet the fluctuating application workload demands, dynamic provisioning is essential and this article provides a detailed literature survey of dynamic provisioning within cloud systems with focus on application performance. The well-known types of provisioning and the associated problems are clearly and pictorially explained and the provisioning terminology is clarified. A very detailed and general cloud provisioning classification is presented, which views provisioning from different perspectives, aiding in understanding the process inside-out. Cloud dynamic provisioning is explained by considering resources, stakeholders, techniques, technologies, algorithms, problems, goals and more.Comment: 14 pages, 3 figures, 3 table

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

Component-wise application migration in bidimensional cross-cloud environments

We propose an algorithm for the migration of cloud applications' components between different providers, possibly changing their service level between IaaS and PaaS. Our solution relies on three of the key ingredients of the trans-cloud approach: a unified API, agnostic topology descriptions, and mechanisms for the independent specification of providers. We show how our approach allows us to overcome some of the current interoperability and portability issues of cloud environments to propose a solution for migration, present an implementation of our proposed solution, and illustrate it with a case study and experimental results.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Foundations of efficient virtual appliance based service deployments

The use of virtual appliances could provide a flexible solution to services deployment. However, these solutions suffer from several disadvantages: (i) the slow deployment time of services in virtual machines, and (ii) virtual appliances crafted by developers tend to be inefficient for deployment purposes. Researchers target problem (i) by advancing virtualization technologies or by introducing virtual appliance caches on the virtual machine monitor hosts. Others aim at problem (ii) by providing solutions for virtual appliance construction, however these solutions require deep knowledge about the service dependencies and its deployment process. This dissertation aids problem (i) with a virtual appliance distribution technique that first identifies appliance parts and their internal dependencies. Then based on service demand it efficiently distributes the identified parts to virtual appliance repositories. Problem (ii) is targeted with the Automated Virtual appliance creation Service (AVS) that can extract and publish an already deployed service by the developer. This recently acquired virtual appliance is optimized for service deployment time with the proposed virtual appliance optimization facility that utilizes active fault injection to remove the non-functional parts of the appliance. Finally, the investigation of appliance distribution and optimization techniques resulted the definition of the minimal manageable virtual appliance that is capable of updating and configuring its executor virtual machine. The deployment time reduction capabilities of the proposed techniques were measured with several services provided in virtual appliances on three cloud infrastructures. The appliance creation capabilities of the AVS are compared to the already available virtual appliances offered by the various online appliance repositories. The results reveal that the introduced techniques significantly decrease the deployment time of virtual appliance based deployment systems. As a result these techniques alleviated one of the major obstacles before virtual appliance based deployment systems