Quality of Service Improvement with Optimal Software-Defined Networking Controller and Control Plane Clustering

The controller is indispensable in software-defined networking(SDN).With several features,controllers monitor the network and respond promptly to dynamic changes.Their performance affects the quality-of-service(QoS)in SDN.Every controller supports a set of features.However,the support of the features may be more prominent in one controller.Moreover,a single controller leads to performance,single-point-of-failure(SPOF),and scalability problems.To overcome this,a controller with an optimum feature set must be available for SDN.Furthermore,a cluster of optimum feature set controllers will overcome an SPOF and improve the QoS in SDN.Herein,leveraging an analytical network process(ANP),we rank SDN controllers regarding their supporting features and create a hierarchical control plane based cluster(HCPC)of the highly ranked controller computed using the ANP,evaluating their performance for the OS3E topology.The results demonstrated in Mininet reveal that a HCPC environment with an optimum controller achieves an improved QoS.Moreover,the experimental results validated in Mininet show that our proposed approach surpasses the existing distributed controller clustering(DCC)schemes in terms of several performance metrics i.e.,delay,jitter,throughput,load balancing,scalability and CPU(central processing unit)utilization.

MST-BASED CLUSTERING TOPOLOGY CONTROL ALGORITHM FOR WIRELESS SENSOR NETWORKS

In this paper, we propose a novel clustering topology control algorithm named Minimum Spanning Tree (MST)-based Clustering Topology Control (MCTC) for Wireless Sensor Networks (WSNs), which uses a hybrid approach to adjust sensor nodes' transmission power in two-tiered hi- erarchical WSNs. MCTC algorithm employs a one-hop Maximum Energy & Minimum Distance (MEMD) clustering algorithm to decide clustering status. Each cluster exchanges information between its own Cluster Members (CMs) locally and then deliveries information to the Cluster Head (CH). Moreover, CHs exchange information between CH and CH and afterwards transmits aggregated in- formation to the base station finally. The intra-cluster topology control scheme uses MST to decide CMs' transmission radius, similarly, the inter-cluster topology control scheme applies MST to decide CHs' transmission radius. Since the intra-cluster topology control is a full distributed approach and the inter-cluster topology control is a pure centralized approach performed by the base station, therefore, MCTC algorithm belongs to one kind of hybrid clustering topology control algorithms and can obtain scalability topology and strong connectivity guarantees simultaneously. As a result, the network topology will be reduced by MCTC algorithm so that network energy efficiency will be improved. The simulation results verify that MCTC outperforms traditional topology control schemes such as LMST, DRNG and MEMD at the aspects of average node's degree, average node's power radius and network lifetime, respectively.

The Design of the Plasma Control System in KTX

KTX（Keda Torus for eXperiment）is a new reversed field pinch device.The KTX plasma control system（PCS）can provide real-time,stable,flexible plasma control which is designed by ASIPP（Institute of Plasma Physics,Chinese Academy of Sciences）,based on the Linux cluster system and EPICS（Experimental Physics and Industrial Control System）framework,and developed from DIII-D（Doublet III-D）PCS.The control of the equilibrium field in KTX uses a PID（Proportional-Integral-Derivative）feedback controller.The control of the gas injection is an open loop control.The plasma control simulation system is one part of the plasma control system,which is used to test the plasma control algorithm if it is revised and updated.The KTX PCS has been successfully tested using HT-7（Hefei Torus 7）experiment data in simulation mode.In the next phase,an error field feedback control and KTX simulator will be added to the KTX PCS,and the KTX PCS will be applied in experiments in the future.

Empirical Analysis of Forest Pest Control Efficiency from 2003 to 2014 in China

Three indexes including forest pest occurrence area,control area and input fund of 31 provinces from 2003 to 2014 were selected from Forestry Statistical Yearbook,to establish dynamic interaction index evaluation system with clustering robust regression model and Stata 13. 0 software. Total forest pest control efficiency in China was determined according to the computing result of entropy method. Suggestions such as improving forest pest control efficiency,increasing service efficiency and input amount of forest pest control input funds were put forward. It will provide empirical basis for target management evaluation of forest pest control work and accountability system.

Effect of household water treatment with chlorine on diarrhea among children under the age of five years in rural areas of Dire Dawa,eastern Ethiopia:a cluster randomized controlled trial

Background:Diarrheal disease is a leading cause of child mortality and morbidity worldwide.Household water treatment with chlorine significantly reduces morbidity due to waterborne diseases.However,the effect of point-ofuse(POU)water treatment in improving the quality of water in areas where POU is not provided free of charge and the effectiveness of home visits in inspiring household members to use POU regularly have not been studied.The objective of this study was to evaluate the effectiveness of drinking water disinfection by chlorination on diarrheal disease reduction among children under the age of 5 years in rural eastern Ethiopia.Methods:A cluster randomized controlled trial was carried out in rural Dire Dawa from October 2018 through January 2019.The 405 households were randomized to intervention and control arms and intervention materials were distributed after conducting a baseline survey.This trial evaluated the effectiveness of household drinking water disinfection by chlorination in reducing incidence of diarrhea among children under the age of 5 years.Intervention households received 1.2%sodium hypochlorite with demonstration of its proper use.Participants in the control households continued with their usual habits of water collection and water storage.Generalized estimation equations(GEE)with log link Poisson distribution family and exchangeable correlation matrix was used to compute crude incidence rate ratio(IRR),adjusted IRR and the corresponding 95%confidence intervals.Results:In the intervention households,in total,281 cases of diarrhea were documented(8.7 cases per 100 personweeks observation);in the control households,in total 446 cases of diarrhea were documented(13.8 cases per 100 person-weeks observation).A 36.0%(adjusted IRR=0.64,95%CI:0.57–0.73)reduction in incidence of diarrhea was observed in the intervention arm when compared with the control arm.The highest and the lowest reductions were obtained in children of age ranges 1 to 2 years and 3 to 4 years,42.7 and 30.4%,respectively.Adherence to the intervention was 81.3%as measured by free residual chlorine test.Conclusions:In rural areas where diarrhea is the second leading cause of morbidity,water chlorination at the household level using liquid bleach considerably reduced episodes of diarrhea among children under the age of 5 years.Therefore,chlorinating drinking water at the household level may be a valuable interim solution for reducing the incidence of diarrheal diseases until potable water is made accessible to the majority of the population in Dire Dawa Administration and other Ethiopian communities.

Gravid oviposition sticky trap and dengue non-structural 1 antigen test for early surveillance of dengue in multi-storey dwellings: study protocol of a cluster randomized controlled trial

Background:Dengue is a global disease,transmitted by the Aedes vectors.In 2018,there were 80615 dengue cases with 147 deaths in Malaysia.Currently,the nationwide surveillance programs are dependent on Aedes larval surveys and notifications of lab-confirmed human infections.The existing,reactive programs appear to lack sensitivity and proactivity.More efficient dengue vector surveillance/control methods are needed.Methods:A parallel,cluster,randomized controlled,interventional trial is being conducted for 18 months in Damansara Damai,Selangor,Malaysia,to determine the efficacy of using gravid oviposition sticky(GOS)trap and dengue non-structural 1(NS1)antigen test for early surveillance of dengue among Aedes mosquitoes to reduce dengue outbreaks.Eight residential apartments were randomly assigned into intervention and control arms.GOS traps are set at the apartments to collect Aedes weekly,following which dengue NS1 antigen is deteaed in these mosquitoes.When a dengue-positive mosquito is detected,the community will be advised to execute vector search-and-destroy and protective measures.The primary outcome concerns the the percentage change in the(i)number of dengue cases and(ii)durations of dengue outbreaks.Whereas other outcome measures include the change in density threshold of Aedes and changes in dengue-related knowledge,attitude and practice among cluster inhabitants.Discussion:This is a proactive and early dengue surveillance in the mosquito vector that does not rely on notification of dengue cases.Surveillance using the GOS traps should be able to efficiently provide sufficient coverage for multistorey dwellings where population per unit area is likely to be higher.Furthermore,trapping dengue-infected mosquitoes using the GOS trap,helps to halt the dengue transmission carried by the mosquito.It is envisaged that the results of this randomized controlled trial will provide a new proactive,cheap and targeted surveillance tool for the prevention and control of dengue outbreaks.Trial registration:This is a parallel-cluster,randomized controlled,interventional trial,registered at ClinicalTrials.gov(ID:NCT03799237),on 8th January 2019(retrospectively registered).

Lines cluster approaching mode control for air-breathing hypersonic vehicle under disturbances and uncertainties

This paper investigates the velocity and altitude tracking control problem for airbreathing hypersonic vehicle(AHV)in the presence of external disturbances and parameter uncertainties.A composite controller containing improved lines cluster approaching mode control(LCAMC)and nonlinear disturbance observer(NDO)is developed to guarantee the tracking errors converge to zero and enhance the robustness of control system.Meanwhile,considering the multiple uncertain parameters,a genetic algorithm(GA)based Pareto uncertainty estimation is employed to predict the parameter uncertainties of the AHV dynamics.Besides,the mathematical proofs of proposed method are analyzed by utilizing Lyapunov theory.Simulation results demonstrate the effective tracking performance,excellent disturbance estimation and uncertainty estimation ability of the composite method.

Automated extraction of attributes from natural language attribute-based access control(ABAC)Policies

The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.

Automated extraction of attributes from natural language attribute-based access control(ABAC)Policies

The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.