Efficient computation of optimal assignments for distributed tasks
Journal of Parallel and Distributed Computing
Scheduling hard real-time tasks with tolerance of multiple processor failures
Microprocessing and Microprogramming - Parallel processing in embedded real-time systems
The Deferrable Server Algorithm for Enhanced Aperiodic Responsiveness in Hard Real-Time Environments
IEEE Transactions on Computers
Allocation and Scheduling of Precedence-Related Periodic Tasks
IEEE Transactions on Parallel and Distributed Systems
Allocating fixed-priority periodic tasks on multiprocessor systems
Real-Time Systems
New Strategies for Assigning Real-Time Tasks to Multiprocessor Systems
IEEE Transactions on Computers
A Framework for Mapping Periodic Real-Time Applications on Multicomputers
IEEE Transactions on Parallel and Distributed Systems
A proper model for the partitioning of electrical circuits
DAC '72 Proceedings of the 9th Design Automation Workshop
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
Optimal graph clustering problems with applications to information system design (partitioning, database)
Evaluation of Search Heuristics for Embedded System Scheduling Problems
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Real-Time Support for Mobile Robotics
RTAS '03 Proceedings of the The 9th IEEE Real-Time and Embedded Technology and Applications Symposium
A Model-Based Approach to System-Level Dependency and Real-Time Analysis of Embedded Software
RTAS '03 Proceedings of the The 9th IEEE Real-Time and Embedded Technology and Applications Symposium
RTAS '03 Proceedings of the The 9th IEEE Real-Time and Embedded Technology and Applications Symposium
Algorithmic aspects of hardware/software partitioning
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Efficient allocation of distributed object-oriented tasks to a pre-defined scheduled system
International Journal of Computers and Applications
Resource management for real-time tasks in mobile robotics
Journal of Systems and Software
Finding optimal hardware/software partitions
Formal Methods in System Design
Solving a real-time allocation problem with constraint programming
Journal of Systems and Software
Evaluating the Kernighan-Lin Heuristic for Hardware/Software Partitioning
International Journal of Applied Mathematics and Computer Science
Expert Systems with Applications: An International Journal
Journal of Systems Architecture: the EUROMICRO Journal
Hi-index | 14.98 |
We propose a new approach to the problem of workload partitioning and assignment for very large distributed real-time systems, in which software components are typically organized hierarchically, and hardware components potentially span several shared and/or dedicated links. Existing approaches for load partitioning and assignment are based on either schedulability or communication. The first category attempts to construct a feasible schedule for various assignments and chooses the one that minimizes task lateness (or other similar criteria), while the second category partitions the workload heuristically in accordance with the amount of intertask communication. We propose, and argue for, a (new) third category based on task periods, which, among others, combines the ability of handling heterogeneity with excellent scalability. Our algorithm is a recursive invocation of two stages: clustering and assignment. The clustering stage partitions tasks and processors into clusters. The assignment stage maps task clusters to processor clusters. A later scheduling stage will compute a feasible schedule, if any, when the size of processor clusters reduces to one at the bottom of the recursion tree. We introduce a new clustering heuristic and evaluate elements of the period-based approach using simulations to verify its suitability for large real-time applications. Also presented is an example application drawn from the field of command and control that has the potential to benefit significantly from the proposed approach.