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Abstract. Infrastructure cloud systems offer basic functionalities only for managing complex virtual infrastructures. These functionalities demand low-level understanding of applications and their infrastructural needs. Recent research has identified several techniques aimed at enabling the semi-automated management and use of those applications that span across multiple virtual machines. Even with these efforts however, a truly flexible and end-user oriented approach is missing. This paper presents the One Click Cloud Orchestrator that not only allows higher level of automation than it was possible before, but it also allows end-users to focus on their problems instead of the complex cloud infrastructures needed for them. To accomplish these goals the paper reveals the novel building blocks of our new orchestrator from the components closely related to infrastructure cloud to the ways virtual infrastructures are modeled. Finally, we show our initial evaluation and study on how the orchestrator fulfills the high level requirements of end-users.

Abstract. Infrastructure-as-a-Service (IaaS) clouds are widely used today, however there are no standardized or commonly used performance evaluation methods and metrics that can be used to compare the services of the different providers. Performance evaluation tools and benchmarks are able to grasp some aspects or details of performance but for various reasons are not capable to characterize cloud performance. Our aim is to collect these elementary or primitive facets of performance and derive high-level aggregated and qualitative performance characterization semantically far above the output of tools and benchmarks. We designed and implemented a framework that collects low-level raw performance data (in terms of CPU, disk, memory and network) of cloud providers based on standard benchmark tools and these data are aggregated and evaluated using a hierarchical fuzzy system. In this process performance characteristics are associated with symbolic values and fuzzy inference is applied to produce the normalized qualitative comparable and readable performance metrics. In this paper, we discuss the issues of cloud performance analysis, present the concept and implementation of our method, illustrate the proposed solution by comparing -in terms of performancethe general purpose medium instance type of the Amazon EC2 cloud (in Ireland) and the standard instance type of the OpenNebula installation at MTA SZTAKI.

Cloud computing is the dominating paradigm in distributed computing. The most popular open source cloud solutions support different type of storage subsystems, because of the different needs of the deployed services (in terms of performance, flexibility, cost-effectiveness). In this paper, we investigate the supported standard and open source storage types and create a classification. We point out that the Internet Small Computer System Interface (iSCSI) based block level storage can be used for I/O intensive services currently. However, the ATA-over-Ethernet (AoE) protocol uses fewer layers and operates on lower level which makes it more lightweight and faster than iSCSI. Therefore, we proposed an architecture for AoE based storage support in OpenNebula cloud. The novel storage solution was implemented and the performance evaluation shows that the I/O throughput of the AoE based storage is better (32.5-61.5%) compared to the prior iSCSI based storage and the new storage solution needs less CPU time (41.37%) to provide the same services.