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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Chien, Hsu-TungSubject: search.filters.subject.Computer architecture

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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.
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    End-to-End Slicing as a Service with Computing and Communication Resource Allocation for Multi-Tenant 5G Systems
    (2019-10-01)
    Chien, Hsu-Tung
    ;
    Lin, Ying-Dar
    ;
    Lai, Chia-Lin
    ;
    Wang, Chien-Ting
    ;
    交大名義發表
    5G services, such as Ultra-reliable and Low Latency Communications, Massive Machine Type Communications and Enhanced Mobile Broadband, support low (or ultra-low) latency, a huge number of connections, and high bandwidth. Typically, 5G platforms are shared by multiple tenants, where each tenant has different service deployment requirements and thus requires different amounts of resources from the lower tier (i.e., radio access network and mobile edge) and upper tier (i.e., transport network and central office) of the 5G architecture. Consequently, slicing is a key technology in 5G networks for providing scalability and flexibility in allocating the 5G resources with appropriate isolation. This study proposes an Endto- End Slicing as a Service framework for slicing both computing and communication resources across the full 2-tier multi-access edge computing architecture. The framework is implemented using open source tools. It is shown that the framework successfully isolates the 5G resources, which are computing and communication, between slices (slicing isolation effect ratio equals 1) and ensures that resources of the deployed slices are merely sufficient to meet the latency requirements of the tenants. Moreover, the experiments show that URLLC and mMTC services require more than 70 percent of the needed computing and communication resources be provided by the edge and RAN in order to satisfy their tighter latency requirements. Overall, the results suggest a central to edge resource allocation ratio of 9:1, 3:7, and 1:9 for the eMBB, URLLC, mMTC applications, respectively. Therefore,