Introduction to algorithms
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Dynamic Matching and Scheduling Algorithm for Heterogeneous Computing Systems
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
Some Economics of Market-Based Distributed Scheduling
ICDCS '98 Proceedings of the The 18th International Conference on Distributed Computing Systems
The Iso-level scheduling heuristic for heterogeneous processors
EUROMICRO-PDP'02 Proceedings of the 10th Euromicro conference on Parallel, distributed and network-based processing
Decomposing constraint systems: equivalences and computational properties
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
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Autonomous scheduling deals with the problem - how to enable agents to schedule a set of interdependent tasks in such a way that whatever schedule they choose for their tasks, the individual schedules always can be merged into a global feasible schedule? Unlike the traditional approaches to distributed scheduling we do not enforce a fixed schedule to every participating agent. Instead we guarantee flexibility by offering a set of schedules to choose from in such a way that every agent can choose its own schedule independently from the others. We show that in case of agents with unbounded concurrency, optimal make-span can be guaranteed. Whenever the agents have bounded concurrency optimality cannot be guaranteed, but we present an approximation algorithm that ensures a constant make-span ratio.