Allocating hard real-time tasks: an NP-hard problem made easy
Real-Time Systems
IEEE Transactions on Computers
Design of Dynamically Reconfigurable Real-Time Software Using Port-Based Objects
IEEE Transactions on Software Engineering
An architecture for embedded software integration using reusable components
CASES '00 Proceedings of the 2000 international conference on Compilers, architecture, and synthesis for embedded systems
Designing Concurrent, Distributed, and Real-Time Applications with Uml
Designing Concurrent, Distributed, and Real-Time Applications with Uml
Knowledge-Based Automation of a Design Method for Concurrent Systems
IEEE Transactions on Software Engineering
Approximation Algorithms for Time Constrained Scheduling
IRREGULAR '95 Proceedings of the Second International Workshop on Parallel Algorithms for Irregularly Structured Problems
Allocation and scheduling of real-time periodic tasks with relative timing constraints
RTCSA '95 Proceedings of the 2nd International Workshop on Real-Time Computing Systems and Applications
Embedded System Design Framework for Minimizing Code Size and Guaranteeing Real-Time Requirements
RTSS '02 Proceedings of the 23rd IEEE Real-Time Systems Symposium
Minimizing Memory Utilization of Real-Time Task Sets in Single and Multi-Processor Systems-on-a-Chip
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
On a Constrained Bin-packing Problem
On a Constrained Bin-packing Problem
A Genetic Algorithm for Scheduling Tasks in a Real-Time Distributed System
EUROMICRO '98 Proceedings of the 24th Conference on EUROMICRO - Volume 2
Predicting Real-Time Properties of Component Assemblies: A Scenario-Simulation Approach
EUROMICRO '04 Proceedings of the 30th EUROMICRO Conference
Towards Predicting Real-Time Properties of a Component Assembly
EUROMICRO '04 Proceedings of the 30th EUROMICRO Conference
SaveCCM - A Component Model for Safety-Critical Real-Time Systems
EUROMICRO '04 Proceedings of the 30th EUROMICRO Conference
Transforming Structural Model to Runtime Model of Embedded Software with Real-Time Constraints
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe: Designers' Forum - Volume 2
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
Exploring performance trade-offs of a JPEG decoder using the deepcompass framework
WOSP '07 Proceedings of the 6th international workshop on Software and performance
Solving a real-time allocation problem with constraint programming
Journal of Systems and Software
Quality assessment of multiobjective optimisation algorithms in component deployment
Proceedings of the doctoral symposium for ESEC/FSE on Doctoral symposium
Developing platform specific model for MPSoC architecture from UML-based embedded software models
Journal of Systems and Software
Architecting dependable systems IV
Reliability-driven deployment optimization for embedded systems
Journal of Systems and Software
Component deployment optimisation with bayesian learning
Proceedings of the 14th international ACM Sigsoft symposium on Component based software engineering
A process for resolving performance trade-offs in component-based architectures
CBSE'06 Proceedings of the 9th international conference on Component-Based Software Engineering
Entropy-based adaptive range parameter control for evolutionary algorithms
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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The embedded systems domain represents a class of systems that have high requirements on cost efficiency as well as run-time properties such as timeliness and dependability. The research on component-based systems has produced component technologies for guaranteeing real-time properties. However, the issue of saving resources by allocating several components to real-time tasks has gained little focus. Trade-offs when allocating components to tasks are, e.g., CPU-overhead, footprint and integrity. In this paper we present a general approach for allocating components to real-time tasks, while utilizing existing real-time analysis to ensure a feasible allocation. We demonstrate that CPU-overhead and memory consumption can be reduced by as much as 48% and 32% respectively for industrially representative systems.