Topology aggregation for hierarchical routing in ATM networks
ACM SIGCOMM Computer Communication Review
Topology information condensation in hierarchical networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Future Generation Computer Systems - Special issue on metacomputing
Journal of Parallel and Distributed Computing
Directed diffusion for wireless sensor networking
IEEE/ACM Transactions on Networking (TON)
ACM Transactions on Computer Systems (TOCS)
Scheduling with Advanced Reservations
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
Comparison of Scheduling Heuristics for Grid Resource Broker
ENC '04 Proceedings of the Fifth Mexican International Conference in Computer Science
A taxonomy of grid monitoring systems
Future Generation Computer Systems
Monitoring Large Systems Via Statistical Sampling
International Journal of High Performance Computing Applications
Software—Practice & Experience
Topology aggregation for combined additive and restrictive metrics
Computer Networks: The International Journal of Computer and Telecommunications Networking
Joint Communication and Computation Task Scheduling in Grids
CCGRID '08 Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid
Quality-of-service routing for supporting multimedia applications
IEEE Journal on Selected Areas in Communications
Scheduling efficiency of resource information aggregation in grid networks
Future Generation Computer Systems
Towards an optimized abstracted topology design in cloud environment
Future Generation Computer Systems
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We propose information aggregation as a method for summarizing the resource-related information, used by the task scheduler. Through this method the information of a set of resources can be uniformly represented, reducing at the same time the amount of information transferred in a Grid network. A number of techniques are described for aggregating the information of the resources belonging to a hierarchical Grid domain. This information includes the cpu and storage capacities at a site, the number of tasks queued, and other resource-related parameters. The quality of the aggregation scheme affects the efficiency of the scheduler’s decisions. We use as a metric of aggregation efficiency the Stretch Factor (SF), defined as the ratio of the task delay when the task is scheduled using complete resource information over the task delay when an aggregation scheme is used. The simulation experiments performed show that the proposed aggregation schemes achieve large information reduction, while enabling good task scheduling decisions as indicated by the SF achieved.