208 research outputs found

    Global Grids and Software Toolkits: A Study of Four Grid Middleware Technologies

    Full text link
    Grid is an infrastructure that involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by multiple organizations. Grid applications often involve large amounts of data and/or computing resources that require secure resource sharing across organizational boundaries. This makes Grid application management and deployment a complex undertaking. Grid middlewares provide users with seamless computing ability and uniform access to resources in the heterogeneous Grid environment. Several software toolkits and systems have been developed, most of which are results of academic research projects, all over the world. This chapter will focus on four of these middlewares--UNICORE, Globus, Legion and Gridbus. It also presents our implementation of a resource broker for UNICORE as this functionality was not supported in it. A comparison of these systems on the basis of the architecture, implementation model and several other features is included.Comment: 19 pages, 10 figure

    A Mean Field Approach for Optimization in Particles Systems and Applications

    Get PDF
    This paper investigates the limit behavior of Markov Decision Processes (MDPs) made of independent particles evolving in a common environment, when the number of particles goes to infinity. In the finite horizon case or with a discounted cost and an infinite horizon, we show that when the number of particles becomes large, the optimal cost of the system converges almost surely to the optimal cost of a discrete deterministic system (the ``optimal mean field''). Convergence also holds for optimal policies. We further provide insights on the speed of convergence by proving several central limits theorems for the cost and the state of the Markov decision process with explicit formulas for the variance of the limit Gaussian laws. Then, our framework is applied to a brokering problem in grid computing. The optimal policy for the limit deterministic system is computed explicitly. Several simulations with growing numbers of processors are reported. They compare the performance of the optimal policy of the limit system used in the finite case with classical policies (such as Join the Shortest Queue) by measuring its asymptotic gain as well as the threshold above which it starts outperforming classical policies

    A Pareto-based Genetic Algorithm for Optimized Assignment of VM Requests on a Cloud Brokering Environment

    Get PDF
    International audienceIn this paper, we deal with cloud brokering for the assignment optimization of VM requests in three-tier cloud infrastructures. We investigate the Pareto-based meta-heuristic approach to take into account multiple client and brokercentric optimization criteria. We propose a new multi-objective Genetic Algorithm ( MOGA-CB ) that can be integrated in a cloud broker. Two objectives are considered in the optimization process: minimizing both the response time and the cost of the selected VM instances to satisfy the clients and to maximize the profit of the broker. The approach has been experimented using realistic data of different types of Amazon EC2 instances and their pricing history. The reported results show that MOGA-CB provides efficiently effective Pareto sets of solutions

    SLA-Oriented Resource Provisioning for Cloud Computing: Challenges, Architecture, and Solutions

    Full text link
    Cloud computing systems promise to offer subscription-oriented, enterprise-quality computing services to users worldwide. With the increased demand for delivering services to a large number of users, they need to offer differentiated services to users and meet their quality expectations. Existing resource management systems in data centers are yet to support Service Level Agreement (SLA)-oriented resource allocation, and thus need to be enhanced to realize cloud computing and utility computing. In addition, no work has been done to collectively incorporate customer-driven service management, computational risk management, and autonomic resource management into a market-based resource management system to target the rapidly changing enterprise requirements of Cloud computing. This paper presents vision, challenges, and architectural elements of SLA-oriented resource management. The proposed architecture supports integration of marketbased provisioning policies and virtualisation technologies for flexible allocation of resources to applications. The performance results obtained from our working prototype system shows the feasibility and effectiveness of SLA-based resource provisioning in Clouds.Comment: 10 pages, 7 figures, Conference Keynote Paper: 2011 IEEE International Conference on Cloud and Service Computing (CSC 2011, IEEE Press, USA), Hong Kong, China, December 12-14, 201

    A Grid-Enabled Infrastructure for Resource Sharing, E-Learning, Searching and Distributed Repository Among Universities

    Get PDF
    In the recent years, service-based approaches for sharing of data among repositories and online learning are rising to prominence because of their potential to meet the requirements in the area of high performance computing. Developing education based grid services and assuring high availability reliability and scalability are demanding in web service architectures. On the other hand, grid computing provides flexibility towards aggregating distributed CPU, memory, storage, data and supports large number of distributed resource sharing to provide the full potential for education like applications to share the knowledge that can be attainable on any single system. However, the literature shows that the potential of grid resources for educational purposes is not being utilized yet. In this paper, an education based grid framework architecture that provides promising platform to support sharing of geographically dispersed learning content among universities is developed. It allows students, faculty and researchers to share and gain knowledge in their area of interest by using e-learning, searching and distributed repository services among universities from anywhere, anytime. Globus toolkit 5.2.5 (GTK) software is used as grid middleware that provides resource access, discovery and management, data movement, security, and so forth. Furthermore, this work uses the OGSA-DAI that provides database access and operations. The resulting infrastructure enables users to discover education services and interact with them using the grid portal

    A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

    Full text link
    Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
    • …
    corecore