pacific 发表于 2025-3-23 10:27:35
Cache-Enabled Super-Peer Overlays for Multiple Job Submission on Gridsnd low cost mechanism for acquiring the necessary compute power is the "publicresource computing" paradigm, which exploits the computational power of private computers. Recently decentralized peer-to-peer and super-peer technologies have been proposed for adaptation in these systems. A super-peer prCOST 发表于 2025-3-23 16:29:30
http://reply.papertrans.cn/39/3888/388740/388740_12.pngconstruct 发表于 2025-3-23 20:55:06
Analysis of Grid Storage Element Architectures: High-end Fiber-Channel vs. Emerging Cluster-based Neporting an increasing number of data-intensive applications and services. This paper studies two approaches for building scalable networked storage elements: enterpriselevel, Fibre-Channel-based Storage (FCS) and commodity, Cluster-based Networked Storage (CNS). First we review the characteristics oOCTO 发表于 2025-3-23 22:50:20
http://reply.papertrans.cn/39/3888/388740/388740_14.pngCANON 发表于 2025-3-24 04:18:25
Peer-to-Peer Metadata Management for Knowledge Discovery Applications in Grids applications running on such platforms need to efficiently and reliably access the various and heterogeneous distributed resources they offer. This can be achieved by using metadata information describing all available resources. It is therefore crucial to provide efficient metadata management archRetrieval 发表于 2025-3-24 10:19:20
http://reply.papertrans.cn/39/3888/388740/388740_16.pngPandemic 发表于 2025-3-24 12:22:25
Real-World Workflow Support in the ASKALON Grid Environmentnvironment. We describe techniques for performance prediction, scheduling, advance reservation, and scalability analysis and illustrate a variety of experimental results that validate each of our technique.MODE 发表于 2025-3-24 18:00:47
http://reply.papertrans.cn/39/3888/388740/388740_18.png额外的事 发表于 2025-3-24 21:06:51
http://reply.papertrans.cn/39/3888/388740/388740_19.pngNausea 发表于 2025-3-25 00:15:33
Patterns for Flexible Object Programming earlier work , we have already shown that time-shared execution of jobs, which splits the CPUs or cores per node between two jobs but shares the network, may provide a performance benefit vs. space sharing, which splits the nodes among the jobs. In this paper, we make a step towards p