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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Thai, Minh-TuanSubject: search.filters.subject.capacity optimization

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    Workload and Capacity Optimization for Cloud-Edge Computing Systems with Vertical and Horizontal Offloading
    (2020-03-01)
    Thai, Minh-Tuan
    ;
    Lin, Ying-Dar
    ;
    Lai, Yuan-Cheng
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    Chien, Hsu-Tung
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    交大名義發表
    A collaborative integration between cloud and edge computing is proposed to be able to exploit the advantages of both technologies. However, most of the existing studies have only considered two-tier cloud-edge computing systems which merely support vertical offloading between local edge nodes and remote cloud servers. This paper thus proposes a generic architecture of cloud-edge computing with the aim of providing both vertical and horizontal offloading between service nodes. To investigate the effectiveness of the design for different operational scenarios, we formulate it as a workload and capacity optimization problem with the objective of minimizing the system computation and communication costs. Because such a mixed-integer nonlinear programming (MINLP) problem is NP-hard, we further develop an approximation algorithm which applies a branch-and-bound method to obtain optimal solutions iteratively. Experimental results show that such a cloud-edge computing architecture can significantly reduce total system costs by about 34%, compared to traditional designs which only support vertical offloading. Our results also indicate that, to accommodate the same number of input workloads, a heterogeneous service allocation scenario requires about a 23% higher system costs than a homogeneous scenario.