Authors:
Hamza Chniter
1
;
Mohamed Khalgui
2
and
Fethi Jarray
3
Affiliations:
1
University of Carthage, University of Elmanar and ISI Institute, Tunisia
;
2
University of Carthage and University of Elmanar, Tunisia
;
3
ISI Institute and Laboratoire CEDRIC, Tunisia
Keyword(s):
Flexible Embedded System, Reconfiguration, Real-time and Low-power Scheduling, Integer Programming, Heuristic.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Formal Methods
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Intelligent Fault Detection and Identification
;
Planning and Scheduling
;
Simulation and Modeling
;
Software Agents for Intelligent Control Systems
;
Symbolic Systems
Abstract:
The paper deals with low-power adaptive scheduling of synchronous and flexible real-time OS tasks. A software reconfiguration scenario is assumed to be any run-time operation allowing the addition-removal-update of OS tasks to adapt the system to its environment under well-defined conditions. The problem is that any reconfiguration can push the system to an unfeasible behavior where temporal properties are violated or the energy consumption is possibly high and unacceptable. A task in the system can change its characteristics at any time when a reconfiguration scenario is applied, it can also be stopped or replaced by another one. The difficulty is how to find the new temporal parameters of the systems tasks after any reconfiguration. We use a DVS processor which is with a variable speed to support run-time solutions that re-obtain the system’s feasibility. The challenge is how to compute the best combinations between available processor speeds for a good compromise between execution
time and energy consumption. We propose a combinatorial optimization method based on integer programming and heuristics. We propose also a solution when the available speeds do not allow the feasibility of the system. Both approaches include a mechanism to adjust the deadlines of tasks to satisfy the feasibility conditions and overcome the problem of rejected tasks. This mechanism makes the scheduling more flexible and able to react in accordance with its environment.
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