Although grid systems have evolved in such a way that they are largely used both in industry and academy, techniques to test and evaluate them, such as simulation and emulation, have limitations on both their applicability and their reliability. We are investigating the utilization of paravirtualization techniques merged with systems management tools to build an automated emulation framework for grid experiments. This framework accesses standard network resources to manage communication among virtual nodes, allowing virtual machines to behave like a real grid environment. The development of this framework involves the mapping of virtual machines to physical hosts, automatic deployment and management of virtual machines, automatic configuration of virtual network and experiment control. In this paper, we address these issues and present results demonstrating the feasibility and advantages of our approach. * This work was developed in collaboration with HP Brazil R&D.

Xen is becoming a de facto solution for virtualization with low performance overhead. Virtualization features include optimization in resources utilization, server consolidation, improved security and fault tolerance. Server consolidation is currently one of the main attractions of virtualization for enterprises. It enhances the scalability of a regular IT infrastructure, enabling the utilization of an amount of servers larger than the available physical machines. However, deploying and managing virtual machines in such environment can be a complex task. It is first necessary to install the virtualization layer, represented by the VMM (Virtual Machine Monitor), on each physical machine. After that, the virtual machines can be deployed. Due to the possibility of having several virtual machines inside a single physical machine, an efficient management of the environment in order to enhance overall system performance and resources utilization is required. Considering these issues, we present in this paper the Xen Site Manager (XSM), a tool to facilitate the deployment and management of virtual sites based on Xen. It interacts with standard services and tools, such as SystemImager, DHCP, PXE and Ganglia, in order to provide high flexibility. We provide a detailed description of XSM architecture and present a performance evaluation of its deployment feature. This work was developed in collaboration with HP Brazil R&D.

Power-aware management strategies are a trend towards achieving energy-efficient computing environments. One of the approaches behind those strategies is dynamic frequency and voltage scaling (DVFS). Since frequency adjustments may have a negative impact on system performance, users often have to experiment with these policies to find the optimal configuration for their application and energy reduction goals. While the performance impact can be easily measured by the total execution time of an application, power consumption measurements require additional logging and frequently external equipment. The following paper presents a mathematical model to help users estimate the power consumption of their application when using different DVFS policies. A preliminary evaluation shows that the model has 94% accuracy when compared against real-time measurements.

Nowadays, data security is a demand for companies when adopting storage services on public clouds. From long term persistence services, such as Amazon Glacier 1 , to online block storage systems for virtual machines disks, security principles can be part of the cloud context, especially for customer's sensitive data. The confidentiality of storage services considers aspects such as data life-cycle, location, and size, besides that, this principle is often provided by a cryptography mechanism applied in one of the persistence layers, such as in the File-System (FS). However, to add cryptography for data security demands extra CPU cycles for ciphering the data during its persistence. Although these extra CPU cycles are not considered on current cloud costs estimations, it should be part of the total application execution's costs. This paper presents the architectures for Cryptography File Systems (CFS) adoption for data storing in cloud computing. Furthermore, a mathematical model is presented and discussed as an estimation tool of cryptography overhead when using CFSs in the cloud storage stack. The model is verified in a real scenario for estimating the total cost when adding security for storage in a cloud environment. As main result, the model could estimate the overhead within 90% to 92% of accuracy for the AES algorithm, according to real cases traces, considering available memory, I/O throughput and workload size.