TY - JOUR
T1 - Improved multi-core real-time task scheduling of reconfigurable systems with energy constraints
AU - Chniter, Hamza
AU - Mosbahi, Olfa
AU - Khalgui, Mohamed
AU - Zhou, Mengchu
AU - Li, Zhiwu
N1 - Funding Information:
This work was supported in part by the National Key Research and Development Program of China under Grant 2018YFB1700104, in part by the National Natural Science Foundation of China under Grant 61873342 and Grant 61472295, in part by the Recruitment Program of Global Experts, in part by the Science Technology Development Fund, Macao Special Administrative Region (MSAR), under Grant 0012/2019/A1, and in part by the Deanship of Scientific Research (DSR) with King Abdulaziz University, Jeddah, under Grant RG-48-135-40.
Publisher Copyright:
© 2013 IEEE.
PY - 2020
Y1 - 2020
N2 - This paper deals with the scheduling of real-time periodic tasks executed on heterogeneous multicore platforms. Each processor is composed of a set of multi-speed cores with limited energy resources. A reconfigurable system is sensible to unpredictable reconfiguration events from related environment, such as the activation, removal or update of tasks. The problem is to handle feasible reconfiguration scenarios under energy constraints. Since any task can finish execution before achieving its worst-case execution time (WCET), the idea is to distribute this execution on different processor cores for meeting related deadlines and reducing energy consumption. The methodology consists in using lower processor speeds first to consume less energy. If the system is still non-feasible after reconfiguration, then we adjust the task periods as a flexible solution or migrate some of them to the least loaded processors. Accordingly, an integer linear program (ILP) is formulated to encode the execution model that assigns tasks to different cores with optimal energy consumption, thereby realizing energy-efficient computing/green computing. The potency and effectiveness of the proposed approach are rated through simulation studies. By measuring the energy consumption cost, our solution offers better than 11% of gain than recently published methods and improves by 85% the overall number of adjusted periods.
AB - This paper deals with the scheduling of real-time periodic tasks executed on heterogeneous multicore platforms. Each processor is composed of a set of multi-speed cores with limited energy resources. A reconfigurable system is sensible to unpredictable reconfiguration events from related environment, such as the activation, removal or update of tasks. The problem is to handle feasible reconfiguration scenarios under energy constraints. Since any task can finish execution before achieving its worst-case execution time (WCET), the idea is to distribute this execution on different processor cores for meeting related deadlines and reducing energy consumption. The methodology consists in using lower processor speeds first to consume less energy. If the system is still non-feasible after reconfiguration, then we adjust the task periods as a flexible solution or migrate some of them to the least loaded processors. Accordingly, an integer linear program (ILP) is formulated to encode the execution model that assigns tasks to different cores with optimal energy consumption, thereby realizing energy-efficient computing/green computing. The potency and effectiveness of the proposed approach are rated through simulation studies. By measuring the energy consumption cost, our solution offers better than 11% of gain than recently published methods and improves by 85% the overall number of adjusted periods.
KW - Green computing
KW - integer linear program
KW - low power consumption
KW - multi-core processor
KW - optimization real-time scheduling
KW - reconfigurable systems reconfiguration
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U2 - 10.1109/ACCESS.2020.2990973
DO - 10.1109/ACCESS.2020.2990973
M3 - Article
AN - SCOPUS:85086071140
SN - 2169-3536
VL - 8
SP - 95698
EP - 95713
JO - IEEE Access
JF - IEEE Access
M1 - 9079845
ER -