Research Article
Distributed Job Scheduling based on Multiple Constraints Anycast Routing
@INPROCEEDINGS{10.1109/BROADNETS.2006.4374374, author={Tim Stevens and Marc De Leenheer and Filip De Turck and Bart Dhoedt and Piet Demeester}, title={Distributed Job Scheduling based on Multiple Constraints Anycast Routing}, proceedings={3rd International ICST Conference on Broadband Communications, Networks, and Systems}, publisher={IEEE}, proceedings_a={BROADNETS}, year={2006}, month={10}, keywords={}, doi={10.1109/BROADNETS.2006.4374374} }
- Tim Stevens
Marc De Leenheer
Filip De Turck
Bart Dhoedt
Piet Demeester
Year: 2006
Distributed Job Scheduling based on Multiple Constraints Anycast Routing
BROADNETS
IEEE
DOI: 10.1109/BROADNETS.2006.4374374
Abstract
As the popularity of resource-constrained devices such as hand-held computers increases, a new network service off loading complex processing tasks towards computational resources located in the access- or core network, sounds very promising. In a consumer-oriented environment, characterized by a large diversity in connected devices, a transparent network-based request processing strategy offers a clear flexibility advantage, as the installation and configuration of extra software components on all client devices can be avoided. In this work, this is achieved by linking computational resources to an any cast group, which allows intermediate router nodes to decide upon the target server. It is shown in the paper that the anycast routing problem can be reduced to unicast routing. Consequently, unicast multiple constraints routing algorithms can be applied to compute an optimal path based on several server selection criteria, including server load, path delay, path cost, etc. For this purpose, we envision the SAMCRA algorithm. A new evaluation ordering strategy for previously computed sub-paths is introduced, which guarantees optimality for the complete SAMCRA path between source and destination. Simulation results show that an effective distribution of the job scheduling requests over the available resources can be achieved by applying the described algorithm.