Abstract
The chapter presents a combinatorial optimization method for the low-power adaptive scheduling problem on variable speed processors and reconfigurable architectures. It deals with synchronous and flexible real-time OS tasks. A reconfiguration scenario is assumed to be a run-time software intervention which act on the system state to allow the addition-removal-update of OS tasks and consequently adapt the system to its environment under functional and extra-functional requirements. A reconfiguration can change the system behavior where temporal properties are violated or the energy consumption overcomes its limit and pushes the system to a non feasible state. A configuration scenario can be a result of the addition-removal-update of tasks in the system. The difficulty is how to recover the violated temporal parameters of the system’s tasks after any reconfiguration. We use a DVS processor which is with a variable speed to support run-time solutions to re-obtain the system’s feasibility. The challenge is to choose the suitable scaling factors for the processor speed to ensure the best compromise between the execution time and the energy consumption where all constraints are respected. We reformulate the problem and propose a combinatorial optimization method based on integer programming and heuristics to solve the problem. We compensate each approach by a mechanism which is based on the deadline adjustment of the tasks to satisfy the feasibility conditions when the available speeds of the processor do not filfull the needs. This mechanism make the system more reliable and flexible to respond appropriately to its environment.
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Chniter, H., Khalgui, M., Jarray, F. (2016). Combinatorial Optimization Approach for Feasible Low-Power and Real-Time Flexible OS Tasks. In: Filipe, J., Gusikhin, O., Madani, K., Sasiadek, J. (eds) Informatics in Control, Automation and Robotics. Lecture Notes in Electrical Engineering, vol 370. Springer, Cham. https://doi.org/10.1007/978-3-319-26453-0_4
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DOI: https://doi.org/10.1007/978-3-319-26453-0_4
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