TY - GEN
T1 - Combining memory allocation and processor volatage scaling for energy-efficient IoT task scheduling
AU - Nam, Sunhwa A.
AU - Cho, Kyungwoon
AU - Bahn, Hyokyung
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported by the Basic Science Research program through the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2016R1A2B4015750) and (MOE) (2016R1A6A3A11930295). Hyokyung Bahn is the corresponding author of this paper.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/27
Y1 - 2017/6/27
N2 - As IoT (Internet-of-things) technologies grow rapidly for emerging applications such as smart living and health care, reducing power consumption in battery-based IoT devices becomes an important issue. An IoT device is a kind of real-time systems, of which power-savings have been widely studied in terms of processor's dynamic voltage/frequency scaling. However, recent research has shown that memory subsystems are getting reached to a significant portion of power consumption in such systems. In this paper, we show that power consumption of real-time systems can be further reduced by combining voltage/frequency scaling with task allocation in hybrid memory. If a task set is schedulable in a low voltage mode of a processor, we can expect that the task set will still be schedulable even with slow memory. By considering this, we adopt non-volatile memory technologies that consume less power than DRAM but provide relatively slow access latency. Our aim is to allocate tasks in non-volatile memory if it does not violate the deadline constraint of real-time tasks, thereby reducing the power consumption of the system further. To do so, we incorporate the memory allocation problem into the problem model of processor's voltage scaling, and evaluate the effectiveness of the combined approach.
AB - As IoT (Internet-of-things) technologies grow rapidly for emerging applications such as smart living and health care, reducing power consumption in battery-based IoT devices becomes an important issue. An IoT device is a kind of real-time systems, of which power-savings have been widely studied in terms of processor's dynamic voltage/frequency scaling. However, recent research has shown that memory subsystems are getting reached to a significant portion of power consumption in such systems. In this paper, we show that power consumption of real-time systems can be further reduced by combining voltage/frequency scaling with task allocation in hybrid memory. If a task set is schedulable in a low voltage mode of a processor, we can expect that the task set will still be schedulable even with slow memory. By considering this, we adopt non-volatile memory technologies that consume less power than DRAM but provide relatively slow access latency. Our aim is to allocate tasks in non-volatile memory if it does not violate the deadline constraint of real-time tasks, thereby reducing the power consumption of the system further. To do so, we incorporate the memory allocation problem into the problem model of processor's voltage scaling, and evaluate the effectiveness of the combined approach.
KW - Dynamic voltage scaling
KW - Hybrid memory
KW - Internet-of-things (IoT)
KW - Non-volatile memory
KW - Real-time task scheduling
UR - http://www.scopus.com/inward/record.url?scp=85030641065&partnerID=8YFLogxK
U2 - 10.1109/ICIS.2017.7960033
DO - 10.1109/ICIS.2017.7960033
M3 - Conference contribution
AN - SCOPUS:85030641065
T3 - Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017
SP - 441
EP - 446
BT - Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017
A2 - Cui, Xiaohui
A2 - Yao, Shaowen
A2 - Xu, Simon
A2 - Zhu, Guobin
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 May 2017 through 26 May 2017
ER -