Managing QoS for Multimedia Applications in the Differentiated Services Environment
Journal of Network and Systems Management
SwarmLan: a language for host recommendation
IMSA'06 Proceedings of the 24th IASTED international conference on Internet and multimedia systems and applications
Autonomic QoS-Aware resource management in grid computing using online performance models
Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
Autonomic QoS control in enterprise Grid environments using online simulation
Journal of Systems and Software
Dynamic multi-resource advance reservation in grid environment
NPC'07 Proceedings of the 2007 IFIP international conference on Network and parallel computing
Mobile Networks and Applications
An adaptive reliable qos for resource errors running on ubiquitous computing environments
VSMM'06 Proceedings of the 12th international conference on Interactive Technologies and Sociotechnical Systems
An adaptive fault tolerance system for ubiquitous computing environments: AFTS
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part IV
Dynamic multi-resource advance reservation in grid environment
The Journal of Supercomputing
A reliable qos model for festival constraint running on MHAP in festival site
FGIT'12 Proceedings of the 4th international conference on Future Generation Information Technology
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We present a QoS and contention-aware multi-resource reservation algorithm to provide end-to-end QoS guarantees for distributed and component-based services. We study a reservation-enabled environment, where each type of resource can be reserved. However, the goals of: (1) achieving the best end-to-end QoS for each client, and (2) increasing the overall success rate of resource reservations for different service requests, are in conflict with each other. Our algorithm provides a solution to alleviate this conflict. For each service request, the algorithm computes an end-to-end multi-resource reservation plan which (1) achieves the highest level of end-to-end QoS under the constraint of current resource availability, and (2) tends to incur low bottleneck resource contention among all feasible reservation plans for this service request. Our initial simulation results show excellent performance of this algorithm.