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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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Communication and Computing Cost Optimization of Meshed Hierarchical NFV Datacenters
(2020-01-01)
Kar, Binayak
;
Wu, Eric Hsiao-Kuang
;
Lin, Ying-Dar
;
資訊工程學系
;
Department of Computer Science
Telecommunication carriers of 5G-MEC are re-architecting their central offices and mobile base stations as datacenters with network function virtualization (NFV) technology. These datacenters (DCs) are known as edge datacenters that help network operators speed deployment and reduce costs. Previously, the use of NFV was limited to within a datacenter (DC) known as intra-DC. Recently, many studies have been conducted into the use of NFV across DCs, i.e., inter-DC. However, these NFV inter-DC architectures have limited communication between DCs with either horizontal or vertical connectivity. In this paper, we propose a generic architecture of such edge NFV datacenters with both horizontal and vertical connectivity, and demonstrate the consequences of both vertical and horizontal connectivity between DCs in terms of communication and computing costs. We formulate a cost optimization problem with latency and capacity as constraints by estimating the traffic dispatch rate between DCs. We propose a vertical-horizontal communication (VHC) heuristic solution to the NP-hard problem. Compared to horizontal connectivity, our results show that vertical connectivity helps to reduce computing costs by 10-30 & x0025;. However, both vertical and horizontal communications together can help to reduce such costs by 20-30 & x0025; compared to only vertical communication.
Smoothed Graphic User Interaction on Smartphones With Motion Prediction
(2020-04-01)
Lin, Ying-Dar
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Chu, Edward T-H
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Chang, Evan
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Lai, Yuan-Cheng
;
資訊工程學系
The smoothness of human-smartphone interaction directly influences users experience and affects their purchase decisions. A commonly used method to improve user interaction of smartphones is to optimize the CPU scheduler. However, optimizing the CPU scheduler requires a modification of operating system. In addition, the improvement of the smoothness of human-smartphone interaction may be limited because the display subsystem is not optimized. Therefore, in this paper, we design a motion prediction queuing system, named MPQS, to improve the smoothness of human-smartphone interaction. For this, we use the information of vector, speed, movement, provided by the queuing mechanism of Android, to predict the movement of user-smartphone interaction. Based on the prediction, we then utilize available execution time between frames to perform image processing. We conducted a set of experiments on beagleboard-xM to evaluate the performance of MPQS. Our experiment results show that the proposed method can reduce the number of jank by up to 21.75%.
Workload and Capacity Optimization for Cloud-Edge Computing Systems with Vertical and Horizontal Offloading
(2020-03-01)
Thai, Minh-Tuan
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Lin, Ying-Dar
;
Lai, Yuan-Cheng
;
Chien, Hsu-Tung
;
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.
End-to-End Slicing as a Service with Computing and Communication Resource Allocation for Multi-Tenant 5G Systems
(2019-10-01)
Chien, Hsu-Tung
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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,

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🏛️國立陽明交通大學機構典藏

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