The Globus Data Grid architecture provides a scalable infrastructure for the management of storage resources and data that are distributed across Grid environments. These services are designed to support a variety of scientific applications, ranging from high-energy physics to computational genomics, that require access to large amounts of data (terabytes or even petabytes) with varied quality of service requirements. By layering on a set of core services, such as data transport, security, and replica cataloging, one can construct various higher-level services. In this paper, we discuss the design and implementation of a high-level replica selection service that uses information regarding replica location and user preferences to guide selection from among storage replica alternatives. We first present a basic replica selection service design, then show how dynamic information collected using Globus information service capabilities concerning storage system properties can help improve and optimize the selection process. We demonstrate the use of Condor's ClassAds resource description and matchmaking mechanism as an efficient tool for representing and matching storage resource capabilities and policies against application requirements.
In this paper, we present the ADMIRE architecture; a new framework for developing novel and innovative data mining techniques to deal with very large and distributed heterogeneous datasets in both commercial and academic applications. The main ADMIRE components are detailed as well as its interfaces allowing the user to efficiently develop and implement their data mining applications techniques on a Grid platform such as Globus ToolKit, DGET, etc.
Data grid replication is an effective method to achieve efficient and fault tolerant data access while reducing access latency and bandwidth consumption in grids. Since we have storage limitation, a replica should be created in the best site. Through evaluation of previously suggested algorithms, we understand that by blind creation of replications on different sites after each demand, we may be able to improve algorithm regarding response time. In practice, however, most of the created replications will never be used and existing resources in Grid will be wasted through the creation of unused…
The LHCb collaboration is one of the four major experiments at the Large Hadron Collider at CERN. Many petabytes of data are produced by the detectors and Monte-Carlo simulations. The LHCb Grid interware LHCbDIRAC is used to make data available to all collaboration members around the world. The data is replicated to the Grid sites in different locations. However the Grid disk storage is limited and does not allow keeping replicas of each file at all sites. Thus it is essential to optimize number of replicas to achieve a better Grid performance. In this study, we present a new approach of data …
Grid computing is a collection of computer resources that are gathered together from various areas to give computational resources such as storage, data or application services. This is to permit clients to access this huge measure of processing resources without the need to know where these might be found and what technology such as, hardware equipment and operating system was used. Dependability and performance are among the key difficulties faced in a grid computing environment. Various systems have been proposed in the literature to handle recouping from resource failure in Grid computing …
Edge computing moves the computation closer to the data and the data closer to the user to overcome the high latency communication of cloud computing. Storage at the edge allows data access with high speeds that enable latency-sensitive applications in areas such as autonomous driving and smart grid. However, several distributed services are typically designed for the cloud and building an efficient edge-enabled storage system is challenging because of the distributed and heterogeneous nature of the edge and its limited resources. In this paper, we propose EdgeKV, a decentralized storage syste…
In 2016, LIGO and Virgo announced the first observation of gravitational waves from a binary black hole merger, known as GW150914. To establish the confidence of this detection, large-scale scientific workflows were used to measure the event's statistical significance. They used code written by the LIGO/Virgo and were executed on the LIGO Data Grid. The codes are publicly available, but there has not yet been an attempt to directly reproduce the results, although several analyses have replicated the analysis, confirming the detection. We attempt to reproduce the result presented in the GW15091…
