Design and Evaluation of a Decentralized System for Grid-wide Fairshare Scheduling
E-SCIENCE '05 Proceedings of the First International Conference on e-Science and Grid Computing
InterGrid: a case for internetworking islands of Grids
Concurrency and Computation: Practice & Experience
Scalable Grid-wide capacity allocation with the SweGrid Accounting System (SGAS)
Concurrency and Computation: Practice & Experience
A recursive architecture for hierarchical grid resource management
Future Generation Computer Systems
Accounting and Billing for Federated Cloud Infrastructures
GCC '09 Proceedings of the 2009 Eighth International Conference on Grid and Cooperative Computing
The reservoir model and architecture for open federated cloud computing
IBM Journal of Research and Development
An OGSA-based bank service for grid accounting systems
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
Self-management challenges for multi-cloud architectures
ServiceWave'11 Proceedings of the 4th European conference on Towards a service-based internet
Hi-index | 0.00 |
We present a non-intrusive solution to the increasingly important problem of shared logging for overlapping and federated Grid environments. The solution addresses three usage scenarios of hierarchical Grids, mutual cross-Grid resource utilization, and federated Cloud computing infrastructures. The approach is evaluated by extending the existing SweGrid Accounting System (SGAS) with a light-weight component that makes the system applicable to a wide range of usage scenarios. The proposed architecture is characterized by its simplicity, flexibility, and generality, and the new key component by its non-intrusiveness, flexibility, and ability to manage high load. We present requirements derived from three usage scenarios, and also include an in-depth description of the architecture and design, as well as the implementation and performance evaluation of a new component written for use with SGAS. We conclude from a performance evaluation that the sharing of usage data is not likely to be a limiting performance factor even in large-scale Grid scenarios.