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PopFlow:a novel flow management scheme for SDN switch of multiple flow tables based on flow popularity

Frontiers of Computer Science 2020年第6期14卷 111-122页

作者： Cheng WANG Kyung Tae KIM Hee Yong YOUN College of Electrical and Computer Engineering Sungkyunkwan UniversitySuwon 16419Korea College of Software Sungkyunkwan UniversitySuwon 16419Korea

pipeline processing is applied to mutiple flow tables(MFT)in the switch of software-defined network(SDN)to increase the throughput of the ***,the processing time of each flow increases as the size or number of flow tables gets *** this paper we propose a novel approach called PopFlow where a table keeping popular flow entries is located up front in the pipeline,and an express path is provided for the flow matching the table.A Markov model is employed for the selection of popular entries considering the match latency and match frequency,and Queuing theory is used to model the flow processing time of the existing MFT-based schemes and the proposed *** simulation reveals that the proposed scheme substantially reduces the flow processing time compared to the existing schemes,and the diference gets more significant as the flow arrival rate increases.

关键词： edge computing SDN pipeline processing PopFlow match frequency and latency markov model-based prediction

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Diffusion tensor imaging pipeline measures of cerebral white matter integrity: An overview of recent advances and prospects

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World Journal of Clinical Cases 2022年第24期10卷 8450-8462页

作者： Amanina Ahmad Safri Che Mohd Nasril Che Mohd Nassir Ismail Nurul Iman Nur Hartini Mohd Taib Anusha Achuthan Muzaimi Mustapha Department of Neurosciences School of Medical SciencesUniversiti Sains MalaysiaHealth CampusKubang Kerian 16150KelantanMalaysia Department of Radiology School of Medical SciencesUniversiti Sains MalaysiaHealth CampusKubang Kerian 16150KelantanMalaysia School of Computer Sciences Universiti Sains Malaysia11800 USMPenangMalaysia Department of Neurosciences Hospital Universiti Sains MalaysiaKubang Kerian 16150KelantanMalaysia

Cerebral small vessel disease(CSVD)is a leading cause of age-related microvascular cognitive decline,resulting in significant morbidity and decreased quality of *** a progress on its key pathophysiological bases and general acceptance of key terms from neuroimaging findings as observed on the magnetic resonance imaging(MRI),key questions on CSVD remain *** relationships and reliable lesion studies,such as white matter tractography using diffusion-based MRI(dMRI)are necessary in order to improve the assessment of white matter architecture and connectivity in *** tensor imaging(DTI)and tractography is an application of dMRI that provides data that can be used to non-invasively appraise the brain white matter connections via fiber tracking and enable visualization of individual patient-specific white matter fiber tracts to reflect the extent of CSVD-associated white matter ***,due to a lack of standardization on various sets of software or image pipeline processing utilized in this technique that driven mostly from research setting,interpreting the findings remain contentious,especially to inform an improved diagnosis and/or prognosis of CSVD for routine clinical *** this minireview,we highlight the advances in DTI pipeline processing and the prospect of this DTI metrics as potential imaging biomarker for CSVD,even for subclinical CSVD in at-risk individuals.

关键词： Diffusion tensor imaging White matter Cerebral small vessel disease pipeline processing Tractography

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