| Title |
A survey on system level energy optimisation for MPSoCs in IoT and consumer electronics |
| ID_Doc |
42515 |
| Authors |
Ali, H; Tariq, UU; Hardy, J; Zhai, XJ; Lu, L; Zheng, YJ; Bensaali, F; Amira, A; Fatema, K; Antonopoulos, N |
| Title |
A survey on system level energy optimisation for MPSoCs in IoT and consumer electronics |
| Year |
2021 |
| Published |
|
| 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. (C) 2021 Elsevier Inc. All rights reserved. |
| PDF |
http://repository.essex.ac.uk/30859/1/Computer_Science_Review.pdf
|
