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After a successful first run at the LHC, and during the Long Shutdown (LS1) of the accelerator, the workload and data management sectors of the CMS Computing Model are entering into an operational review phase in order to concretely assess area of possible improvements and paths to exploit new promising technology trends. In particular, since the preparation activities for the LHC start, the networks...
An e-Infrastructure allows end-user's applications to easily and securely access heterogeneous grid resources (e.g., computing and storage elements). Since e-Science applications are often characterized by huge data transfers and high computational loads, the selection and allocation of grid resources dramatically affect their performance. This paper proposes a distributed resource allocation algorithm,...
This paper considers an InfiniBand connection between two bwGRiD clusters over a distance of 28 km in day-to-day production use. We discuss the hardware setup of InfiniBand messages converted and transported over a fiber optic connection. The two clusters can be operated as single system image, the batch system will enforce that all nodes for a job are allocated on one side of the cluster. This is...
Data grid, which provides the capability to store the mass data, has become one of the hottest topics in distributed storage research domains. However, the limited capacity of local storage devices and the high latency of network have become the bottlenecks for efficiently accessing the files in the data grids. These problems can be solved through introducing a replication strategy by which the overall...
BES is a large internationally collaborative experiment, which produces more than 1PB of data every year. To meet the requirements of data storage and analysis, the BESGrid project has been launched. Data management is a very important part of BESGrid, and we designed and developed a large scale data management system. The system is responsible for storing a large amount of data, providing high-performance...
The use of grid computing is becoming increasingly important in the areas requiring large quantity of data and calculation. To provide better access time and fault tolerance in such systems, the replication is one of the main issues for this purpose. The effectiveness of a replication model depends on several factors, including the replicas placement strategy. In this paper, we propose an a priori...
We propose a novel deadline-based strategy in scheduling and rescheduling workflow applications on a heterogeneous Grid system. Instead of minimizing the makespan of a job by a greedy algorithm, our approach schedules tasks so that the overall job meets its deadline. The key innovation is how we allow some tasks to be rescheduled, in light of later job requests, to a different time slot or another...
The data grid technology, which uses the scale of the Internet to provide storage capability for the mass data, has become one of the hot research topics. The high latency of the network is the bottleneck in accessing the files in data grid systems. The replication strategy can shorten the time of fetching the files by creating many replicas stored in appropriate locations. Due to the limited storage...
Cloud computing has been endorsed by the IT community as the new paradigm shift in the industry that charts the way forward. Unfortunately, the field is still on its path to rigor and robustness. This is epitomized by the numerous fuzzy articulations of “what is cloud computing”. This paper makes a first attempt at remedying this conundrum by providing a core technical specification of the model for...
With all the potential flexibility of software-defined radios, the flexibility of SDR terminals is currently limited to design time flexibility. The capacity of the platform in terms of processing resources and internal bandwidths is dimensioned for the range of supported functionalities. In a platform-independent design scenario, resource managers play the role of matching waveform demands with platform...
We propose a model for large-scale smartphone based sensor networks, with sensor information processed by clouds and grids, with a mediation layer for processing, filtering and other mashups done via a brokering network. Final aggregate results are assumed to be sent to users through traditional cloud interfaces such as browsers. We conjecture that such a network configuration will have significant...
Task scheduling has been one of the hot and difficult problems in grid computing, it is a big challenge to design an efficient scheduling algorithm. This paper discusses the problem of independent tasks scheduling on tree-based grid computing platforms, a small heap tree (virtual resource tree) model was proposed and on the model we propose a tasks scheduling heuristic algorithm based-on linear programming...
Data-intensive applications are becoming increasingly common in Grid environments. These applications require enormous volume of data for the computation. Most conventional meta-scheduling approaches are aimed at computation intensive application and they do not take data requirement of the applications into account, thus leading to poor performance. Efficient scheduling of data-intensive applications...
The coming decade is going to see a push towards exascale computing. Assuming gigahertz cores, this means exascale systems will have between 100 million and 1 billion of them to achieve this level of performance. At this scale, some important questions need to be answered on the applications end. What applications are feasible at this scale? What needs to be done to make them scalable? How does the...
Grid computing is emerging as a key enabling infrastructure for a wide range of disciplines in Science and Engineering. Data grids provide distributed resources for dealing with large scale applications that generate huge volume of data sets. Data replication, a technique much discussed by data grid researchers in past years creates multiple copies of file and stores them in conventional locations...
A grid system connects a huge number of computers in the Internet. It integrates the distributed computational resources and data resources. A complex grid system needs to have a characteristic of self-managing. Autonomic computing aims to overcome the rapidly growing complexity of computing system management. It can be implemented to manage complex computing resources in grid systems. We present...
In order to solve the problem of collaboration and resource sharing of spatial database, this paper combines with the collaboration and resource sharing idea of grid computing, through analyzing the characteristics of grid and spatial database, the author establishes the spatial database model initially in grid environment , studies the spatial data processing operations performance in grid environment...
We presented the SimGrid simulation framework whose goal is to provide a generic evaluation tool for large-scale distributed computing. Its main components are: two APIs for researchers who study algorithm and need to prototype simulations quickly, and two for developers who can develop applications in the comfort of the simulated world before deploying them seamlessly in the real world. SimGrid employs...
Grid scheduling is one of the most crucial issue in a grid environment because it strongly affects the performance of the whole system. Taking into account that the issue of allocating jobs on resources is a combinatorial optimization problem, a NP-complete problem, several heuristics have been proposed to provide good performance. In this paper, the proposed approach considers a stochastic optimization...
In the last years, grid computing has emerged as a valuable service to solve complex computational problems in many scientific and industrial domains. Quality of Service (QoS) provision for these applications is therefore a key challenge for high speed Next Generation Networks and cross-layer mechanisms, enabling the development of network-aware grids, should be introduced. This paper takes into account,...
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