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Scheduling Algorithms for Heterogeneous Cloud Environment: Main Resource Load Balancing Algorithm and Time Balancing Algorithm

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Abstract

Cloud computing and Internet of Things (IoT) are two of the most important technologies that have significantly changed human’s life. However, with the growing prevalence of Cloud-IoT paradigm, the load imbalance and higher SLA lead to more resource wastage and energy consumption. Although there are many researches that study Cloud-IoT from the perspective of offloading side, few of them have focused on how the offloaded workload are dealt with in Cloud. This paper proposes two IoT-aware multi-resource task scheduling algorithms for heterogeneous cloud environment namely main resource load balancing and time balancing. The algorithms aim to obtain better result of load balance, Service-Level Agreement (SLA) and IoT task response time and meanwhile to reduce the energy consumption as much as possible. They both are devised to assign single task to a properly selected Virtual Machine (VM) each time. The task placed in a pre-processed queue is assigned sequentially each time. And the VM selection rule is carried out based on the newly inventive ideas called relative load or relative time cost. Besides, two customized parameters that influence the result of pre-process tasks are provided for users or administrators to flexibly control the behavior of the algorithms. According to the experiments, the main resource load balancing performs well in terms of SLA and load balance, while time balancing is good at saving time and energy. Besides, both of them perform well in IoT task response time.

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Acknowledgements

This work is supported by National Natural Science Foundation of China (Grant Nos. 61772205, 61872084), Guangdong Science and Technology Department (Grant No. 2017B010126002), Guangzhou Science and Technology Program key projects (Grant Nos. 201802010010, 201807010052, 201902010040 and 201907010001), Guangzhou Development Zone Science and Technology(Grant No. 2018GH17), Special Funds for the Development of Industry and Information of Guangdong Province (big data demonstrated applications) in 2017, and the Fundamental Research Funds for the Central Universities, SCUT(Grant No. 2019ZD26).

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Authors and Affiliations

  1. School of Computer Science and Engineering, South China University of Technology, Guangzhou, China

    Weiwei Lin, Gaofeng Peng & Siyao Xu

  2. Guangdong Luan Indusrty and Commerce Co.,Ltd., Guangzhou, China

    Weiwei Lin

  3. Shanghai Jiao Tong University, Shanghai, China

    Xinran Bian

  4. Institute of Software Application Technology, Guangzhou & Chinese Academy of Sciences, Guangzhou, China

    Yin Li

  5. School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, UK

    Victor Chang

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  1. Weiwei Lin
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Correspondence to Weiwei Lin.

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Lin, W., Peng, G., Bian, X. et al. Scheduling Algorithms for Heterogeneous Cloud Environment: Main Resource Load Balancing Algorithm and Time Balancing Algorithm. J Grid Computing 17, 699–726 (2019). https://doi.org/10.1007/s10723-019-09499-7

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