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Load balancing and auto-scaling issues in container microservice cloud-based system: a review on the current trend technologies

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International Journal of Web engineering and technology 2023年第4期18卷 294-318页

作者： Rabiu, Shamsuddeen Yong, Chan Huah Syed-Mohamad, Sharifah Mashita School of Computer Sciences Universiti Sains Malaysia Penang Minden11800 Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus21030 Malaysia

Load balancing and auto-scaling are essential to cloud features for cloud-based container microservices as they control the number of computing resources available. Many research works have proposed load balancing and auto-scaling approaches for microservices individually;however, they are less likely to propose the two approaches in solving their problems simultaneously. The paper aimed to critically analyse the current issues related to load balancing and auto-scaling in container microservices cloud-based systems. This will open room for researchers in the field to enhance performance for better QoS to the users. We present a comprehensive literature review of the existing techniques used for load balancing and auto-scaling in cloud-based containerised microservice applications. After the in-depth review, it is found that load balancing and auto-scaling contribute as a value-added feature to the microservice applications. This can optimise the issues of Servers overloaded, service failure, traffic spikes, et cetera, during the microservices communication phase. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Quality of service

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Collaborative learning-based inter-dependent task dispatching and co-location in an integrated edge computing system

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Digital Communications and Networks 2024年第6期10卷 1837-1850页

作者： Uchechukwu Awada Jiankang Zhang Sheng Chen Shuangzhi Li Shouyi Yang School of Software Henan Institute of Science and TechnologyXinxiang 453003China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China Department of Computing and Informatics Bournemouth UniversityPoole BH125BBUK School of Electronics and Computer Science University of SouthamptonSouthampton SO171BJUK Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266100China

Recently,several edge deployment types,such as on-premise edge clusters,Unmanned Aerial Vehicles(UAV)-attached edge devices,telecommunication base stations installed with edge clusters,etc.,are being deployed to enable faster response time for latency-sensitive *** fundamental problem is where and how to offload and schedule multi-dependent tasks so as to minimize their collective execution time and to achieve high resource *** approaches randomly dispatch tasks naively to available edge nodes without considering the resource demands of tasks,inter-dependencies of tasks and edge resource *** approaches can result in the longer waiting time for tasks due to insufficient resource availability or dependency support,as well as provider ***,we present Edge Colla,which is based on the integration of edge resources running across multi-edge *** Colla leverages learning techniques to intelligently dispatch multidependent tasks,and a variant bin-packing optimization method to co-locate these tasks firmly on available nodes to optimally utilize *** experiments on real-world datasets from Alibaba on task dependencies show that our approach can achieve optimal performance than the baseline schemes.

关键词： Edge computing Collaborative learning Resource utilization Execution time Edge federation Gang scheduling

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Layered niobium carbide enabling excellent kinetics and cycling stability of Li-Mg-B-H hydrogen storage material Layered niobium carbide enabling excellent kinetics

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Rare Metals 2024年第3期43卷 1153-1166页

作者： Li-Wen Lu Hui Luo Guang-Xu Li Yun Li Xin-Hua Wang Cun-Ke Huang Zhi-QiangLan Wen-Zheng Zhou Jin Guo Mohammad Ismail Hai-Zhen Liu Guangxi Novel Battery Materials Research Center of Engineering Technology Guangxi Colleges and Universities Key Laboratory of Blue Energy and Systems IntegrationSchool of Physical Science and TechnologyGuangxi UniversityNanning530004China State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures Nanning530004China School of Mechanical and Electrical Engineering Quzhou College of TechnologyQuzhou324000China Department of Materials Science and Engineering Zhejiang UniversityHangzhou310027China Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu21030Kuala NerusTerengganuMalaysia Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education) Nankai UniversityTianjin300071China

The Li-Mg-B-H composite(2LiBH_(4)+MgH_(2))has a high capacity of 11.4 wt%as a hydrogen storage ***,the slow kinetics and poor cycling stability severely restrict its practical *** this work,a layered Nb_(2)C MXene was first synthesized and then introduced to tailor the kinetics and cycling stability of the Li-Mg-B-H *** milled 2LiH+MgB_(2)composites were initially hydrogenated to obtain the 2LiBH_(4)+MgH_(2)*** 2LiBH_(4)+MgH_(2)+5wt%Nb_(2)C can release 9.0 wt%H_(2)in 30 min at 400℃,while it is only 2.7 wt%for the undoped 2LiBH_(4)+MgH_(2).The dehydrogenation activation energies of MgH_(2)and LiBH_(4)are 123 and 154 kJ·mol^(-1)respectively for the 5 wt%Nb_(2)C-doped composite,lower than the undoped composite(164 and 165 kJ·mol^(-1)).The 2LiBH_(4)+MgH_(2)+5 wt%Nb_(2)C possesses excellent cycling stability,with the reversible capacity only slightly reduced from 9.4 wt%for the 1st cycle to 9.3 wt%for the 20th ***_(2)C keeps stable in the composite and acts as an efficient catalyst for the Li-Mg-B-H *** is believed that both the layered structure and the active Nb element contribu te to the enhanced hydrogen storage performances of the Li-Mg-B-H *** work confirms that the Nb_(2)C MXene with layered stru cture has a significant enhancing impact on the Li-Mg-B-H hydrogen storage materials,which is different from the bulk NbC.

关键词： Hydrogen storage Lithium borohydride Magnesium hydride Nb_(2)C MXene

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Scouring Around Rigs-to-Reefs Jacket Platform with Different Sitting Configurations on Seabed 6th

Scouring Around Rigs-to-Reefs Jacket Platform with Different...

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6th International Conference on Mechanical engineering Research, ICMER 2021

作者： Rahman, Mohd Asamudin A. Mohd, Mohd Hairil Fitriadhy, Ahmad Nazri, Muhammad Nadzrin Kasiman, Erwan Hafizi Alias, Fatin Maritime Technology and Naval Architecture Programme Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus21030 Malaysia School of Civil Engineering Faculty of Engineering Universiti Teknologi Malaysia Johor Skudai81310 Malaysia

ISBN: (纸本)9789811915765

The decommissioning of offshore platforms is becoming more popular due to the lack of productive fields and the unpredictability of oil prices. The Rigs-to-Reef (RTR) program, which is part of the oil and gas company’s decommissioning method, involves turning jacket platforms into artificial reefs. This program creates shelter for marine life and subsequently increases marine production. However, the sediment scours around the jacket platform are one of the problems to be concerned about because it will result in RTR program failure. In this study, the seabed profile around the jacket platform was investigated using Computational Fluid Dynamic (CFD). The simulation of the seabed scour and the deposition around, were conducted using different arrangements of jacket platform. The results showed that the flow velocity decreased when the flow was obstructed in front of the jacket platform. A horseshoe vortex occurred, then developed in front of the cylinder. The flow accelerated on the opposite side of the jacket structure, causing significant scour around the structure as well as bed shear stress. Finally, the vertical jacket platforms showed a significantly lower scour and deposition than the horizontal position. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computational fluid dynamics

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Application of GNSS-PPP on Dynamic Deformation Monitoring of Offshore Platforms

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China ocean engineering 2024年第2期38卷 352-361页

作者： YU Li-na XIONG Kuan GAO Xi-feng LI Zhi FAN Li-long ZHANG Kai Institute of Ocean Energy and Intelligent Construction Tianjin University of TechnologyTianjin 300384China China Railway Construction Bridge Engineering Bureau Group Co.LTD Tianjin 300300China School of Civil Engineering Tianjin UniversityTianjin 300072China Department of Land Surveying and Geo-Informatics The Hong Kong Polytechnic UniversityHong KongChina State Key Laboratory of Precision Blasting Jianghan UniversityWuhan 430056China

The real-time dynamic deformation monitoring of offshore platforms under environmental excitation is crucial to their safe *** Global Navigation Satellite System-Precise Point Positioning(GNSS-PPP)has been considered for this purpose,its monitoring accuracy is relatively ***,the influence of background noise on the dynamic monitoring accuracy of GNSS-PPP remains ***,it is imperative to further validate the feasibility of GNSS-PPP for deformation monitoring of offshore *** address these concerns,vibration table tests with different amplitudes and frequencies are *** results demonstrate that GNSS-PPP can effectively monitor horizontal vibration displacement as low as±30 mm,which is consistent with ***,the spectral characteristic of background noise in GNSS-PPP is similar to that of GNSS-RTK(Real Time Kinematic).Building on this observation,an improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)has been proposed to de-noise the data and enhance the dynamic monitoring accuracy of *** monitoring application research is also undertaken,successfully extracting and analyzing the dynamic deformation of an offshore platform structure under environmental excitation using GNSS-PPP monitoring in conjunction with improved CEEMDAN *** comparing the de-noised dynamic deformation trajectories of the offshore platform during different periods,it is observed that the platform exhibits reversible alternating vibration responses under environmental excitation,with more pronounced displacement deformation in the direction of load *** research results confirm the feasibility and potential of GNSS-PPP for dynamic deformation monitoring of offshore platforms.

关键词： GNSS-PPP offshore platform dynamic deformation monitoring improved CEEMDAN de-noising

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Ti_(3)AICN MAX for tailoring MgH_(2) hydrogen storage material:from performance to mechanism

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Rare Metals 2023年第6期42卷 1923-1934页

作者： Xing-Qing Duan Guang-Xu Li Wen-Hui Zhang Hui Luo Hai-Mei Tang Li Xu Peng Sheng Xin-Hua Wang Xian-Tun Huang Cun-Ke Huang Zhi-Qiang Lan Wen-Zheng Zhou Jin Guo Mohammd Bin Ismail Hai-Zhen Liu Guangxi Novel Battery Materials Research Center of Engineering Technology Guangxi Colleges and Universities Key Laboratory of Novel Energy Materials and Related TechnologySchool of Physical Science and TechnologyGuangxi UniversityNanning530004China State Key Laboratory of Advanced Power Transmission Technology State Grid Smart Grid Research Institute Co.Ltd.Beijing102209China Department of Materials Science and Engineering Zhejiang UniversityHangzhou310027China Department of Materials Science and Engineering Baise CollegeBaise533000China Energy Storage Research Group Faculty of Ocean Engineering Technology and InformaticsUniversiti Malaysia TerengganuKuala Nerus21030Malaysia

Many MXenes are efficient catalysts for MgH_(2)hydrogen storage ***,the synthesis of MXenes should consume a large amount of corrosive HF to etch out the Al layers from the transition metal aluminum carbides or nitrides(MAX) phases,which is environmentally *** this work,Ti_(3)AlCN MAX without HFetching was employed directly to observably enhance the kinetics and the cycling stability of MgH_(2).With addition of10 wt% Ti_(3)AlCN,the onset dehydrogenation temperature of MgH2 was dropped from 320 to 205℃,and the rehydrogenation of MgH2 under 6 MPa H2 began at as low as50℃.Furthermore,at 300℃,it could provide 6.2 wt% of hydrogen in 10 *** cycling,the composite underwent an activation process during the initial 40 cycles,with the reversible capacity increased from 4.7 wt% to 6.5 wt%.After that,the capacity showed almost no attenuation for up to 100 *** enhancing effect of Ti_(3)AICN on MgH_(2) was comparable to many *** was demonstrated that Ti_(3)AICN did not destabilize MgH_(2) but acted as an efficient catalyst for MgH_(2).Ti_(3)AICN was observed to be the active sites for the nucleation and growth of MgH_(2)and might also help in dissociation and recombination of hydrogen *** two factors are believed to contribute to the improvement of MgH_(2).This study not only provides a promising strategy for improving the hydrogen storage performances of MgH_(2) by using noncorrosive MAX materials,but also adds evidence of nucleation and growth of MgH_(2) on a catalyst.

关键词： Hydrogen storage Magnesium hydride MAX MXene Titanium aluminum carbonitride

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Ingredient-Guided RGB-D Fusion Network for Nutritional Assessment

IEEE Transactions on AgriFood Electronics

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IEEE Transactions on AgriFood Electronics 2025年第1期3卷 156-166页

作者： Feng, Zhihui Xiong, Hao Min, Weiqing Hou, Sujuan Duan, Huichuan Liu, Zhonghua Jiang, Shuqiang Shandong Normal University School of Information Science and Enginering Jinan250358 China Macquarie University Centre for Health Informatics Macquarie ParkNSW2109 Australia Chinese Academy of Sciences Key Laboratory of Intelligent Information Processing Institute of Computing Technology Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Zhejiang Ocean University School of Information Engineering Zhoushan316022 China

The nutritional value of agricultural products is an important indicator for evaluating their quality, which directly affects people's dietary choices and overall well-being. Nutritional assessment studies provide a scientific basis for the production, processing, and marketing of food by analyzing the nutrients they contain. Traditional methods often struggle with suboptimal accuracy and can be time consuming, as well as a shortage of professionals. The progress in artificial intelligence has revolutionized dietary health by offering more accessible methods for food nutritional assessment using vision-based approaches. However, existing vision-based methods using RGB images often face challenges due to varying lighting conditions, impacting the accuracy of nutritional assessment. An alternative is the RGB-D fusion method, which combines RGB images and depth maps. Yet, these methods typically rely on simple fusion techniques that do not ensure precise assessment. Additionally, current vision-based methods struggle to detect small components like oils and sugars on food surfaces, crucial for determining ingredient information and ensuring accurate nutritional assessment. In this pursuit, we propose a novel ingredient-guided RGB-D fusion network that integrates RGB images with depth maps and enables more reliable nutritional assessment guided by ingredient information. Specifically, the multifrequency bimodality fusion module is designed to leverage the correlation between the RGB image and the depth map within the frequency domain. Furthermore, the progressive-fusion module and ingredient-guided module leverage ingredient information to explore the potential correlation between ingredients and nutrients, thereby enhancing the guidance for nutritional assessment learning. We evaluate our approach on a variety of ablation settings on Nutrition5k, where it consistently outperforms state-of-the-art methods. © 2023 IEEE.

关键词： Medicinal chemistry

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Detection of oil spill based on CBF-CNN using HY-1C CZI multispectral images

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Acta oceanologica Sinica 2022年第7期41卷 166-179页

作者： Kai Du Yi Ma Zongchen Jiang Xiaoqing Lu Junfang Yang College of Geodesy and Geomatics Shandong University of Science and TechnologyQingdao266590China First Institute of Oceanology Ministry of Natural ResourcesQingdao266061China School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin150001China National Satellite Ocean Application Service Beijing100081China College of Oceanography and Space Informatics China University of Petroleum(East China)Qingdao266580China Technology Innovation Center for Ocean Telemetry Ministry of Natural ResourcesQingdao266061China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710072China

Accurate detection of an oil spill is of great significance for rapid response to oil spill *** images have the advantages of high spatial resolution,short revisit period,and wide imaging width,which is suitable for large-scale oil spill ***,in wide remote sensing images,the number of oil spill samples is generally far less than that of seawater ***,the sea surface state tends to be heterogeneous over a large area,which makes the identification of oil spills more difficult because of various sea conditions and *** address this problem,we used the F-Score as a measure of the distance between forecast value and true value,proposed the Class-Balanced F loss function(CBF loss function)that comprehensively considers the precision and recall,and rebalances the loss according to the actual sample numbers of various *** the CBF loss function,we constructed convolution neural networks(CBF-CNN)for oil spill *** on the image acquired by the Coastal Zone Imager(CZI)of the Haiyang-1C(HY-1C)satellite in the Andaman Sea(study area 1),we carried out parameter adjustment *** contrast to experiments of different loss functions,the F1-Score of the detection result of oil emulsions is 0.87,which is 0.03–0.07 higher than cross-entropy,hinge,and focal loss functions,and the F1-Score of the detection result of oil slicks is 0.94,which is 0.01–0.09 higher than those three loss *** comparison with the experiment of different methods,the F1-Score of CBF-CNN for the detection result of oil emulsions is 0.05–0.12 higher than that of the deep neural networks,supports vector machine and random forests models,and the F1-Score of the detection result of oil slicks is 0.15–0.22 higher than that of the three *** verify the applicability of the CBF-CNN model in different observation scenes,we used the image obtained by HY-1C CZI in the Karimata Strait to carry out experiments,which include two stu

关键词： oil spills CNN classification loss function sunglint detection

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Driving Data Analysis for the Development of Kuala Terengganu Driving Cycle 6th

Driving Data Analysis for the Development of Kuala Terenggan...

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6th International Conference on Mechanical engineering Research, ICMER 2021

作者： Anida, I.N. Norbakyah, J.S. Yussof, W.N.J.H.W. Walker, P. Salisa, A.R. Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus21030 Malaysia Universiti Malaysia Terengganu Terengganu Kuala Nerus21030 Malaysia Universiti Malaysia Terengganu Terengganu Kuala Nerus21030 Malaysia School of Mechanical and Mechatronic Engineering Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia

ISBN: (纸本)9789811915765

Driving cycle plays a vital role in the production and evaluating the performance of the vehicle. Driving cycle is a speed-time data set and as an important input for vehicle emission models. A problem coming with the second-by-second speed driving data is to analyze the big driving data. To analyze this big data, it is necessary to choose best big data analysis methods, which give opportunity to store, preprocess, detect outlier and apply classification or clustering algorithms. In this study, a set of driving data is stored, managed and analyzed using Tall Arrays (TA) and k-means clustering algorithms in MATLAB for the development of Kuala Terengganu Driving Cycle (KTDC). The objectives of this paper are;to store and manage driving data using TA in MATLAB, to develop a KTDC by using k-means clustering, and lastly to analyze the energy consumption and emissions of KTDC. Firstly, the driving data is collected in five different routes in Kuala Terengganu city at go-to-work times. Then the data is stored and analyzed in the MATLAB. The development of KTDC is by using k-means clustering approach. Finally, the energy consumption and emissions of KTDC is analyzed by using AUTONOMIE software. KTDC is successfully developed with 35.15 km/h in average speed and 12 micro-trips. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： MATLAB

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Assessing and solving multicollinearity in sediment transport prediction models using principal component analysis

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ISH Journal of Hydraulic engineering 2021年第S1期27卷 343-353页

作者： Sulaiman, Mohd Sofiyan Abood, Manal Mohsen Sinnakaudan, Shanker Kumar Shukor, Mohd Rizal You, Goh Qiu Chung, Xiang Zhi School of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Terengganu Malaysia Faculty of Engineering and Technology Infrastructure Infrastructure University Kuala Lumpur Kajang Malaysia Faculty of Civil Engineering Universiti Teknologi MARA Permatang Pauh Malaysia

Predicting sediment transport in a river system is necessary when attempting to monitor river changes due to incoming particle deposition from upstream reaches. Previous studies have used various techniques such as probabilistic, regression, and equal mobility approaches to make predictions. However, issues associated with multicollinearity occur when using the regression approach. Significant correlations between the explanatory variables in a regression equation can increase the coefficient variance estimates, which make these estimates very sensitive to minor changes. Thus, we propose the use of principal component analysis as a solution to these issues. We observed that the variance inflation factor is less than 10, which indicates the nonexistence of issues associated with multicollinearity. Fitting components to the regression equation create a new prediction model for sediment transport, which improves upon previous equations using the same technique. © 2019 Indian Society for Hydraulics.

关键词： Regression analysis

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