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XtreemOS aims to build and promote a Linux based operating system to provide native Virtual Organization (VO) support in the next generation Grids. XtreemOS takes a different approach from many existing Grid middleware by: first, recognizing the fundamental role of VO in Grid computing and hence taking VO support into account from the very beginning of our design; and, second, getting around the overheads brought by layers of existing Grid middleware by enabling native VO support in the Linux operating system. This paper presents our vision of VOs in a Grid operating system and describes various aspects of VO management in our system architecture, ranging from lifecycle management, application execution management, security, to node-level enforcement mechanisms in operating system. [ABSTRACT FROM AUTHOR]

Grid computing is becoming a common platform for solving large scale computing tasks. However, a number of major technical issues, including the lack of adequate performance evaluation approaches, hinder the grid computing's further development. The requirements herefore are manifold; adequate approaches must combine appropriate performance metrics, realistic workload models, and flexible tools for workload generation, submission, and analysis. In this paper we present an approach to tackle this complex problem. First, we introduce a set of grid performance objectives based on traditional and grid-specific performance metrics. Second, we synthesize the requirements for realistic grid workload modeling, e.g. co-allocation, data and network management, and failure modeling. Third, we show how GrenchMark, an existing framework for generating, running, and analyzing grid workloads, can be extended to implement the proposed modeling techniques. Our approach aims to be an initial and necessary step towards a common performance evaluation framework for grid environments. [ABSTRACT FROM AUTHOR]

In this paper, we present a methodology for automatically generating online scheduling strategies for a complex scheduling objective with the help of real life workload data. The scheduling problem includes independent parallel jobs and multiple identical machines. The objective is defined by the machine provider and considers different priorities of user groups. In order to allow a wide range of objective functions, we use a rule based scheduling strategy. There, a rule system classifies all possible scheduling states and assigns an appropriate scheduling strategy based on the actual state. The rule bases are developed with the help of a Genetic Fuzzy System that uses workload data obtained from real system installations. We evaluate our new scheduling strategies again on real workload data in comparison to a probability based scheduling strategy and the EASY standard scheduling algorithm. To this end, we select an exemplary objective function that prioritizes some user groups over others. [ABSTRACT FROM AUTHOR]

This paper addresses necessary modification and extensions to existing Grid Computing approaches in order to meet modern business demand. Grid Computing has been traditionally used to solve large scientific problems, focussing more on accumulative use of computing power and processing large input and output files, typical for many scientific problems. Nowadays businesses have increasing computational demands, such that Grid technologies are of interest. However, the existing business requirements introduce new constraints on the design, configuration and operation of the underlying systems, including availability of resources, performance, monitoring aspects, security and isolation issues. This paper addresses the existing Grid Computing capabilities, discussing the additional demands in detail. This results in a suggestion of problem areas that must be investigated and corresponding technologies that should be used within future Business Grid systems. [ABSTRACT FROM AUTHOR]