RegaDB: Community-driven data management and analysis for infectious diseases

Summary: RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB pr

Stiller: Grids in a Mobile World: Akogrimo’s Network and Business Views; IFI

Abstract — The use of wireless networking technologies has emerged over recent years in many application domains. The area of grids determines a potentially huge application domain, since the typical centralized computing centers require access from anywhere, e.g., from field engineers who are situated in a wireless network domain. Thus, the integration of suitable business views on mobile grids, of grid views on available technologies, and network views in a fully IP-based network domain determines the key challenge. The Akogrimo project’s architecture developed, is outlined and discussed in this paper and provides the major details required to offer a fully integrated and interoperable solution for those three views of concern

Data collection framework: project deliverable D4.1, revision 2

This deliverable will detail the requirements of the data collection framework to be deployed for the project. The requirements include the performance and energy indicators that the data collection framework is expected to log and analyse, the agreed data formats and the architecture of the data collection tool. The deliverable also discusses the available datasets from Flexiant and the University of ULM

The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation

Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing