Energy-Efficient Fault-Tolerant Scheduling Algorithm for Real-Time Tasks in Cloud-Based 5G Networks

Pengze Guo, Ming Liu, Jun Wu, Zhi Xue, Xiangjian He

Research output: Journal PublicationArticlepeer-review

15 Citations (Scopus)

Abstract

Green computing has become a hot issue for both academia and industry. The fifth-generation (5G) mobile networks put forward a high request for energy efficiency and low latency. The cloud radio access network provides efficient resource use, high performance, and high availability for 5G systems. However, hardware and software faults of cloud systems may lead to failure in providing real-time services. Developing fault tolerance technique can efficiently enhance the reliability and availability of real-time cloud services. The core idea of fault-tolerant scheduling algorithm is introducing redundancy to ensure that the tasks can be finished in the case of permanent or transient system failure. Nevertheless, the redundancy incurs extra overhead for cloud systems, which results in considerable energy consumption. In this paper, we focus on the problem of how to reduce the energy consumption when providing fault tolerance. We first propose a novel primary-backup-based fault-tolerant scheduling architecture for real-time tasks in the cloud environment. Based on the architecture, we present an energy-efficient fault-tolerant scheduling algorithm for real-time tasks (EFTR). EFTR adopts a proactive strategy to increase the system processing capacity and employs a rearrangement mechanism to improve the resource utilization. Simulation experiments are conducted on the CloudSim platform to evaluate the feasibility and effectiveness of EFTR. Compared with the existing fault-tolerant scheduling algorithms, EFTR shows excellent performance in energy conservation and task schedulability.

Original languageEnglish
Article number8470927
Pages (from-to)53671-53683
Number of pages13
JournalIEEE Access
Volume6
DOIs
Publication statusPublished - 2018
Externally publishedYes

Keywords

  • 5G
  • Energy efficiency
  • cloud
  • fault tolerance
  • real-time
  • scheduling

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering

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