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A survey on system level energy optimisation for MPSoCs in IoT and consumer electronics

Ali, Haider; Tariq, Umair Ullah; Hardy, James; Zhai, Xiaojun; Lu, Liu; Zheng, Yongjun; Bensaali, Faycal; Amira, Abbes; Fatema, Kaniz; Antonopoulos, Nikos

Authors

Haider Ali

Umair Ullah Tariq

James Hardy

Xiaojun Zhai

Liu Lu

Yongjun Zheng

Faycal Bensaali

Abbes Amira

Kaniz Fatema

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Prof Nick Antonopoulos N.Antonopoulos@napier.ac.uk
Deputy Vice Chancellor and Vice Principal of Research & Innovation



Abstract

Internet-of-Things (IoT) is an appealing service to revolutionise Smart City (SC) initiatives across the globe. IoT interconnects a plethora of digital devices known as Sensor Nodes (SNs) to the Internet. Due to their high performance and exceptional Quality-of-Service (QoS) Multiprocessor System-on-Chip (MPSoC) computing architectures are gaining increasing popularity for the computationally extensive workloads in both IoT and consumer electronics. In this survey, we have explored balance between the IoT paradigm and its applications in SC while introducing Wireless Sensor Network (WSN), including the structure of the SN. We considered MPSoCs systems in relation to characteristics such as architecture and the communication technology involved. This provides an insight into the benefits of coupling MPSoCs with IoT. This paper, also investigates prevalent software level energy optimisation techniques and extensively reviews workload mapping and scheduling approaches since 2001 until today for energy savings using (1) Dynamic Voltage and Frequency Scaling (DVFS) and/or Dynamic Power Management (DPM) (2) Inter-processor communication reduction (3) Coarse-grained software pipelining integrated with DVFS. This paper constructively summarises the findings of these approaches and algorithms identifying insightful directions to future research avenues.

Citation

Ali, H., Tariq, U. U., Hardy, J., Zhai, X., Lu, L., Zheng, Y., …Antonopoulos, N. (2021). A survey on system level energy optimisation for MPSoCs in IoT and consumer electronics. Computer Science Review, 41, https://doi.org/10.1016/j.cosrev.2021.100416

Journal Article Type Review
Acceptance Date Jun 16, 2021
Online Publication Date Jun 30, 2021
Publication Date 2021-08
Deposit Date Nov 8, 2021
Journal Computer Science Review
Print ISSN 1574-0137
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 41
Article Number 100416
DOI https://doi.org/10.1016/j.cosrev.2021.100416
Keywords Internet-of-Things, Smart City, WSN, SNs, Smart-phones, Bus, NoC, MPSoCs, Scheduling, DVFS, DPM, Re-timing, Energy-efficiency
Public URL http://researchrepository.napier.ac.uk/Output/2802685