Proactive information caching for efficient resource discovery in a self-structured grid
BADS '09 Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems
MaGate Simulator: A Simulation Environment for a Decentralized Grid Scheduler
APPT '09 Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies
Enabling efficient information discovery in a self-structured grid
Future Generation Computer Systems
CASP: a community-aware scheduling protocol
International Journal of Grid and Utility Computing
MaGate: An Interoperable, Decentralized and Modular High-Level Grid Scheduler
International Journal of Distributed Systems and Technologies
Meta-scheduling algorithms for managing inter-cloud interoperability
International Journal of High Performance Computing and Networking
| Hi-index | 0.00 |
Resource management and scheduling has proven to be one of the key topics for grid computing. Nowadays, the resource management field is subdivided into low-level and high-level approaches. While low-level resource management systems normally concern the scheduling activities within a single virtual organization, high-level schedulers focus on the large scale resources utilization with unstable resource availability, low reliability networks, multi-policies, multi-administrative domains, etc. In this paper, we propose a decentralized framework named SmartGRID to tackle high-level grid resource management and scheduling. Within the SmartGRID framework, swarm intelligence algorithms are used for resource discovery and monitoring, standard protocols and schemes are adopted for scheduler interoperability, and an embedded plugin mechanism is provided to utilize multi-type external scheduling strategies. With a clearly decoupled layered architecture, SmartGRID has been designed to be a generic and modular environment to support intelligent and interoperable grid resource management upon a volatile, dynamics, and heterogeneous grid computing infrastructure.