Distributed Scheduling of Tasks with Deadlines and Resource Requirements
IEEE Transactions on Computers
IEEE Transactions on Computers
Assignment and Scheduling Communicating Periodic Tasks in Distributed Real-Time Systems
IEEE Transactions on Software Engineering
Efficient Scheduling Algorithms for Real-Time Multiprocessor Systems
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
A Framework for Mapping with Resource Co-Allocation in Heterogeneous Computing Systems
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
On adaptive resource allocation for complex real-time applications
RTSS '97 Proceedings of the 18th IEEE Real-Time Systems Symposium
An Optimization Framework for Dynamic, Distributed Real-Time Systems
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Resource Reclaiming in Hard Real-Time Systems with Static and Dynamic Workloads
HICSS '97 Proceedings of the 30th Hawaii International Conference on System Sciences: Software Technology and Architecture - Volume 1
Multiprocessor Resource Allocation for Hard-Real-Time Streaming with a Dynamic Job-Mix
RTAS '05 Proceedings of the 11th IEEE Real Time on Embedded Technology and Applications Symposium
Toward a Theory for Scheduling Dags in Internet-Based Computing
IEEE Transactions on Computers
Software radios: unifying the reconfiguration process over heterogeneous platforms
EURASIP Journal on Applied Signal Processing
IEEE Transactions on Parallel and Distributed Systems
A Computing Resource Management Framework for Software-Defined Radios
IEEE Transactions on Computers
The software radio architecture
IEEE Communications Magazine
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This paper introduces an open computing resource managementframework for real-time computing systems. The framework is modular andconsists of a general computing resource modeling that facilitates a policy-based (open) computing resource management. The computing resource modelingcontains two resource model templates, which may be instantiated as oftenas necessary to capture a platform's computing resources and an application'scomputing requirements. The computing resource management approach featuresa parametric algorithm (tw-mapping with window size w) and a genericand parametric cost function, which implements the computing resource managementpolicy. We present simulations using a simple instance of this costfunction to demonstrate the suitability and versatility of the framework. Wecompute a metric that relates the computing resource management success to itscomplexity and conclude that adjusting the cost function's parameter is moreefficient than augmenting the tw-mapping's window size.