2,831 research outputs found
QoS Provisioning by Meta-Scheduling in Advance within SLA-Based Grid Environments
The establishment of agreements between users and the entities which manage the Grid resources is still a challenging task. On the one hand, an entity in charge of dealing with the communication with the users is needed, with the aim of signing resource usage contracts and also implementing some renegotiation techniques, among others. On the other hand, some mechanisms should be implemented which decide if the QoS requested could be achieved and, in such case, ensuring that the QoS agreement is provided. One way of increasing the probability of achieving the agreed QoS is by performing meta-scheduling of jobs in advance, that is, jobs are scheduled some time before they are actually executed. In this way, it becomes more likely that the appropriate resources are available to run the jobs when needed. So, this paper presents a framework built on top of Globus and the GridWay meta-scheduler to provide QoS by means of performing meta-scheduling in advance. Thanks to this, QoS requirements of jobs are met (i.e. jobs are finished within a deadline). Apart from that, the mechanisms needed to manage the communication between the users and the system are presented and implemented through SLA contracts based on the WS-Agreement specification
Modelling of user requirements and behaviors in computational grids
In traditional distributed computing systems a few user types are found having ratherPeer ReviewedPostprint (published version
Network-aware heuristics for inter-domain meta-scheduling in Grids
AbstractGrid computing generally involves the aggregation of geographically distributed resources in the context of a particular application. As such resources can exist within different administrative domains, requirements on the communication network must also be taken into account when performing meta-scheduling, migration or monitoring of jobs. Similarly, coordinating efficient interaction between different domains should also be considered when performing such meta-scheduling of jobs. A strategy to perform peer-to-peer-inspired meta-scheduling in Grids is presented. This strategy has three main goals: (1) it takes the network characteristics into account when performing meta-scheduling; (2) communication and query referral between domains is considered, so that efficient meta-scheduling can be performed; and (3) the strategy demonstrates scalability, making it suitable for many scientific applications that require resources on a large scale. Simulation results are presented that demonstrate the usefulness of this approach, and it is compared with other proposals from literature
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
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
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