IEEE Transactions on Computers
Assignment and Scheduling Communicating Periodic Tasks in Distributed Real-Time Systems
IEEE Transactions on Software Engineering
A case study in embedded system design: an engine control unit
DAC '98 Proceedings of the 35th annual Design Automation Conference
Heuristic Algorithms for Scheduling Independent Tasks on Nonidentical Processors
Journal of the ACM (JACM)
Scheduling Real-Time Systems with End-to-End Timing Constraints Using the Distributed Pinwheel Model
IEEE Transactions on Computers
Efficient Scheduling Algorithms for Real-Time Multiprocessor Systems
IEEE Transactions on Parallel and Distributed Systems
Static Processor Allocation in a Soft Real-Time Multiprocessor Environment
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Software Engineering
ICPP '97 Proceedings of the international Conference on Parallel Processing
An integer programming approach for static mapping onto heterogeneous real-time systems
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Task Execution Time Modeling for Heterogeneous Computing Systems
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
Specification and Modeling of Dynamic, Distributed Real-Time Systems
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
ISPAN '99 Proceedings of the 1999 International Symposium on Parallel Architectures, Algorithms and Networks
MIP formulation for robust resource allocation in dynamic real-time systems
Journal of Systems and Software - Special issue: Parallel and distributed real-time systems
Characterizing robustness in dynamic real-time systems
Journal of Systems and Software
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Dynamic real-time systems such as embedded systems operate in environments in which several parameters vary at run time. These systems must satisfy several performance requirements. Resource allocation on these systems becomes challenging because variations of run-time parameters may cause violations of the performance requirements. Performance violations result in the need for dynamic re-allocation, which is a costly operation. In this paper, a method for allocating resources such that the allocation can sustain the system in the light of a continuously changing environment is developed. We introduce a novel performance metric called MAIL (maximum allowable increase in load) to capture the effectiveness of a resource allocation. Given a resource allocation, MAIL quantifies the amount of additional load that can be sustained by the system without any performance violations. A Mixed-Integer-Programming-based approach (MIP) is developed to determine a resource allocation that has the highest MAIL value. Using simulations, several sets of experiments are conducted to evaluate our heuristics in various scenarios of machine and task heterogeneities. The performance of MIP is compared with three other heuristics: Integer-Programming based, Greedy, and classic Min-Min. Our results show that MIP performs significantly better when compared with the other heuristics.