Traffic congestion in interconnected complex networks

Traffic congestion in isolated complex networks has been investigated extensively over the last decade. Coupled network models have recently been developed to facilitate further understanding of real complex systems. Analysis of traffic congestion in coupled complex networks, however, is still relatively unexplored. In this paper, we try to explore the effect of interconnections on traffic congestion in interconnected BA scale-free networks. We find that assortative coupling can alleviate traffic congestion more readily than disassortative and random coupling when the node processing capacity is allocated based on node usage probability. Furthermore, the optimal coupling probability can be found for assortative coupling. However, three types of coupling preferences achieve similar traffic performance if all nodes share the same processing capacity. We analyze interconnected Internet AS-level graphs of South Korea and Japan and obtain similar results. Some practical suggestions are presented to optimize such real-world interconnected networks accordingly.Comment: 8 page

Overseas Chinese Environmental Engineers and Scientists Association (OCEESA) Report, Regular Issue, February 2020

This OCEESA report, which is regular issue of OCEESA Journal (Overseas Chinese Environmental Engineers and Scientists Association Journal). This report is OCEESA report number: OCEESA/JL-2020/3701, February 2020, ISSN 1072 -7248. This report is also OCEESA Journal, Volume 37, Number 1, February 2020. Yung-Tse Hung, Permanent Executive Director, OCEESA, is editor of this report. This issue includes: (A) 10 OCEESA Best Papers (B) 6 OCEESA Papers; 21.Zhang-Zhi Charlie Huang 黄长志 , Implementing Compensation System for Environmental Damages: Challenges and Solutions, 22. Hanlu Yan, Kaimin Shih施凱閔 , Quantitative X-Ray Diffraction for Characterizing P Recovery Products from Wastewater, 23. Kaimin Shih 施凱閔 , Material Mineralogical Technology for Pollution Prevention and Resource Recovery材料礦物學技術於污染防治與資源回收的應用, 24. Kuo-Kunag Hsu 許國光 , Cleanup of MSW-Gasified Synthesis Gas, 25. Pao-Chiang Yuan 袁保強 , End of Useful Life Computer Recycling Program at Jackson State University, Jackson, Mississippi, USA, 26. Qin Qian钱琴, Bo Sun, Xianchang Li, Frank Sun, Che-Jen Lin, Water quality modeling with data collected by wireless sensor networks (WSNs) in an experimental pond: A case study; (C) 3 technical papers; 28. Abdulkarim Alorayfij, Yung-Tse Hung, Anaerobic digestion of agricultural waste, 29. Abdullah Alshati, Yung-Tse Hung, Methane Gas Production from Animal Waste, 30. Abdulmajeed Alshatti, Yung-Tse Hung, Treatment of Timber Industry Wastes, 31. OCEESA Constitutions By-Laws (5 November 2000 edition), 32. OCEESA Constitutions By-Laws (14 February 2006 edition), 33. OCEESA Constitutions By-Laws (27 October 2013 edition), 34. Lawrence Kong-Pu Wang letter of support Yung-Tse Hung Permanent Executive Director OCEESA 12-30-20, 35. Wen-Chi Ku letter of support Yung-Tse Hung Permanent Executive Director OCEESA 12-03-20, 36. OCEESA Member Application Form and Information, 37. Mailing Address Pag

Overseas Chinese Environmental Engineers and Scientists Association (OCEESA) Report, Dec 2016.

This Overseas Chinese Environmental Engineers and Scientists Association (OCEESA) report is 2016 Directory of Overseas Chinese Environmental Engineers and Scientists Association (OCEESA), Report number: OCEESA/JL-2016/33D1, December 2016, ISSN 1072 -7248. This report was prepared by Yung-Tse Hung, Permanent Executive Director, OCEESA. This report includes OCEESA contact information, list of OCEESA Directors, list of OCEESA past presidents, OCEESA membership data, constitutions and by laws of OCEESA (5 November 2000 edition), constitutions and by laws of OCEESA (14 February 2006 edition), constitutions and by laws of OCEESA (27 October 2013 edition), membership application form, letter from Wen-Chi Ku to confirm Yung-Tse Hung OCEESA permanent executive director, letter from Lawrence Kong-Pu Wang to confirm Yung-Tse Hung OCEESA permanent executive director

A Stable Matching-based Virtual Machine Allocation Mechanism for Cloud Data Centers

Abstract-Virtualization is the enabling technology that makes resource provisioning in Cloud computing feasible. With virtualization, virtual machines (VMs) can be migrated across physical hosts to achieve better utilization of resource with a minimum impact on service quality. The VM allocation problem can be formulated as a stable matching problem. In this paper, we propose a VM allocation mechanism based on stable matching. A deferred acceptance procedure is adopted to handle conflicts among preferences of VMs and physical hosts. Unlike ordinary stable matching problems, both involving party groups in our matching process are having a mutual objective, that is to reduce the overall energy consumption of a Cloud data center while maintaining a high level of Quality of Service. The proposed mechanism is evaluated using CloudSim with real-world workload data. Simulation results show that Cloud data centers with the proposed mechanism can reduce energy consumption and avoid violations of ServiceLevel Agreement

Analysis of telephone network traffic based on a complex user network

The traffic in telephone networks is analyzed in this paper. Unlike the classical traffic analysis where call blockings are due to the limited channel capacity, we consider here a more realistic cause for call blockings which is due to the way in which users are networked in a real-life human society. Furthermore, two kinds of user network, namely, the fully-connected user network and the scale-free network, are employed to model the way in which telephone users are connected. We show that the blocking probability is generally higher in the case of the scale-free user network, and that the carried traffic intensity is practically limited not only by the network capacity but also by the property of the user network.Comment: 17 pages, 9 figures, accepted for Physica

Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning

Introduction Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and variability of HbA1c and lipids for adverse outcomes. Methods This retrospective cohort study consists of type 1 and type 2 diabetic patients who were prescribed insulin at outpatient clinics of Hong Kong public hospitals, from 1st January to 31st December 2009. Standard deviation (SD) and coefficient of variation were used to measure the variability of HbA1c, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglyceride. The primary outcome is all-cause mortality. Secondary outcomes were diabetes-related complications. Result The study consists of 25,186 patients (mean age = 63.0, interquartile range [IQR] of age = 15.1 years, male = 50%). HbA1c and lipid value and variability were significant predictors of all-cause mortality. Higher HbA1c and lipid variability measures were associated with increased risks of neurological, ophthalmological and renal complications, as well as incident dementia, osteoporosis, peripheral vascular disease, ischemic heart disease, atrial fibrillation and heart failure (p <  0.05). Significant association was found between hypoglycemic frequency (p <  0.0001), HbA1c (p <  0.0001) and lipid variability against baseline neutrophil-lymphocyte ratio (NLR). Conclusion Raised variability in HbA1c and lipid parameters are associated with an elevated risk in both diabetic complications and all-cause mortality. The association between hypoglycemic frequency, baseline NLR, and both HbA1c and lipid variability implicate a role for inflammation in mediating adverse outcomes in diabetes, but this should be explored further in future studies