Title: Reliability enhancement algorithm based on budget level in cloud-edge environments

Authors: Longxin Zhang; Dantong Liu; Minghui Ai; Runti Tan; Zhihao Zeng

Addresses: College of Computer Science, Hunan University of Technology, Zhuzhou, Hunan, China ' College of Computer Science, Hunan University of Technology, Zhuzhou, Hunan, China ' College of Computer Science, Hunan University of Technology, Zhuzhou, Hunan, China ' College of Computer Science, Hunan University of Technology, Zhuzhou, Hunan, China ' College of Computer Science, Hunan University of Technology, Zhuzhou, Hunan, China

Abstract: Low energy consumption and high reliability are two core performance metrics for task scheduling on heterogeneous computing systems. Dynamic voltage and frequency scaling is an efficient technique that reduces energy consumption by dynamically scaling the processor's supply voltage/frequency. However, frequent changes in processor frequency can lead to a dramatic increase in transient faults, which can affect system reliability. Hence, a novel budget level (BL) energy pre-allocation strategy is designed and a reliability maximisation algorithm based on BL (RMBL) is proposed in this study. The RMBL algorithm includes three stages, which are the establishment of a task priority queue, pre-allocation of task energy consumption constraints, and determination of the optimal virtual machine and frequency combination. Based on two real-world applications, namely, Laplace and Gaussian elimination, experimental results show that RMBL can achieve better reliability while satisfying energy consumption constraints.

Keywords: cloud-edge environment; CEE; dynamic voltage and frequency scaling; DVFS; energy consumption; parallel application; reliability.

DOI: 10.1504/IJES.2023.134106

International Journal of Embedded Systems, 2023 Vol.16 No.1, pp.9 - 22

Received: 31 Jul 2022
Received in revised form: 25 Nov 2022
Accepted: 23 Dec 2022
Published online: 11 Oct 2023 *

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