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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Liu, Haoyu Ding, Feiyan Wang, Yao Xiang, Qiao Shu, Jiwu Du, Haizhou Kong, Linghe Liu, Xue Xiamen University School of Informatics Xiamen China University of Electric Power of Shanghai School of Computer Science and Technology Shanghai China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China McGill University School of Computer Science Montreal Canada

ISBN: (纸本)9798350330717

All existing coflow scheduling algorithms compute dynamic-rate schedules that change the rates of flows during transmission. In this paper, we make a crucial finding: although dynamically adjusting the rates of flows could lead to a better coflow completion time (CCT) in theory, it would introduce additional pressures on the congestion control mechanism in the underlying network, which result in poor CCT in practice. This difference between theoretical CCT and practical CCT is further exacerbated in wide-area networks, where the topology does not provide any bisection guarantee as data center networks do. To this end, we designed a fixed-rate coflow scheduling policy called FSCO. Although in theory, the best fixed-rate schedule is usually suboptimal, it keeps the in-flight traffic relatively steady, reducing the risk of triggering congestion control. The core of FSCO is an efficient scheduling algorithm based on the classic network utilization maximization (NUM) framework. We implement a prototype of FSCO and evaluate its performance extensively using real-world topologies and coflow traces. Experimental results show that the total CCT reduces up to 30% compared to baselines while yielding up to 12× speedups compared to the solver. © 2023 IEEE.

关键词： Coflow Scheduling Dual decomposition Network Utility Maximization

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CloudRecoMan: Cloud adoption made easy: A platform for assisting small and medium enterprises to adopt cloud solutions 22

CloudRecoMan: Cloud adoption made easy: A platform for assis...

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Proceedings of the 2022 ACM Conference on Information technology for Social Good

作者： Christos Mettouris Evangelia Vanezi George Zampas Stylianos Argyrou Achilleas Achilleos Avgoustinos Constantinides George Angelos Papadopoulos Department of Computer Science University of Cyprus Cyprus Department of Electrical and Computer Engineering and Informatics Frederick University Cyprus IBSCY Ltd Cyprus

ISBN: (纸本)9781450392846

Although the adoption and use of cloud computing in large, medium and small enterprises is increasing every year, statistics show that medium and especially small enterprises have a much slower adoption than large enterprises. This suggests that various types of issues may affect Small to Medium Enterprises (SMEs) in making the choice to transit towards the public cloud. Based on experts and literature, SMEs’ adoption of cloud is impacted by lack of resources, concerns on security and data control and uncontrolled increasing cloud costs due to the lack of cloud experience. A platform is not yet available that would assist non-technical SME managers in specifying non-technical business requirements in order to receive assistance in the form of recommendations of cloud resources, cloud applications and deployment plans. The CloudRecoMan platform aims to enable this through the development of a web-based cloud recommender and deployment platform.

关键词： Cloud deployment platform Cloud computing Cloud Recommender System

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Private Computation of Boolean Functions Using Single Qubits 15th

Private Computation of Boolean Functions Using Single Qubit...

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15th International Conference on Parallel Processing and Applied Mathematics, PPAM 2024

作者： Rahmani, Zeinab Pinto, Armando N. Barbosa, Luis S. Department of Electronics Telecommunications and Informatics University of Aveiro Aveiro Portugal Instituto de Telecomunicações Aveiro Portugal International Iberian Nanotechnology Laboratory Braga Portugal Department of Computer Science University of Minho Braga Portugal Institute of Systems and Computer Engineering Technology and Science Braga Portugal

ISBN: (纸本)9783031856990

Secure Multiparty Computation (SMC) facilitates secure collaboration among multiple parties while safeguarding the privacy of their confidential data. This paper introduces a two-party quantum SMC protocol designed for evaluating binary Boolean functions using single qubits. Complexity analyses demonstrate a reduction of 66.7% in required quantum resources, achieved by utilizing single qubits instead of multi-particle entangled states. However, the quantum communication cost has increased by 40% due to the amplified exchange of qubits among participants. Furthermore, we bolster security by performing additional quantum operations along the y-axis of the Bloch sphere, effectively hiding the output from potential adversaries. We design the corresponding quantum circuit and implement the proposed protocol on the IBM Qiskit platform, yielding reliable outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Qubits

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Analysis and Performance Evaluation of OpenFlow Controller in SDN using N-Policy

Analysis and Performance Evaluation of OpenFlow Controller i...

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2023 International Conference on Recent Advances in Science and engineering technology, ICRASET 2023

作者： Al Ahmad, Mahmoud Diab, Maisa Patra, Sudhansu Shekhar University of Kalamoon College of Engineering It Department Damascus Suburb Syria Arab Private University for Science and Technology College of Informatics Engineering It Department Hama Syria Kiit Deemed to Be University School of Computer Applications Bhubaneswar India

ISBN: (纸本)9798350306927

The OpenFlow protocol facilitates the communication between the control and forwarding planes within a software-defined networking (SDN) framework. In SDN, the control plane is housed in a distinct entity known as the OpenFlow controller, which assumes the responsibility of making high-level determinations regarding the forwarding of network traffic. With the OpenFlow controller, network administrators can centrally program and manage network behavior, incorporating functionalities like traffic engineering, load balancing, QoS enforcement, security policies, and more. By segregating the control plane from the data plane, SDN utilizing OpenFlow empowers flexible network management, automation, and programmability. Through the utilization of the OpenFlow protocol, the OpenFlow controller interacts with the forwarding plane, typically implemented in network switches or routers. This approach offers a centralized perspective of the network and grants dynamic control over the behavior of network devices by installing flow entries into their forwarding tables. In this research, we use a single-controller N-policy finite buffer waiting queue model to investigate the system performance metrics. Numerical examples and different indices are presented to illustrate the proposed model. © 2023 IEEE.

关键词： Controllers

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GCAT: graph calibration attention transformer for robust object tracking

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Neural Computing and Applications 2024年第23期36卷 14151-14172页

作者： Chen, Si Hu, Xinxin Wang, Da-Han Yan, Yan Zhu, Shunzhi Fujian Key Laboratory of Pattern Recognition and Image Understanding School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China State Key Laboratory of Integrated Services Networks Xidian University Xi’an710071 China Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen University Xiamen361005 China

Recent Siamese trackers have taken advantage of transformers to achieve impressive advancements. However, existing transformer trackers ignore considering the positional and structural information between tokens, and traditional template update strategies easily introduce noises to the dynamic templates during tracking. In order to alleviate this issue, this paper develops a novel end-to-end graph calibration attention transformer network (GCAT) to enhance tracking robustness and accuracy. A graph calibration attention mechanism is first designed to calibrate and aggregate template information, for effectively updating dynamic templates during the tracking process. Specifically, each token is considered as a node in the graph, and then, we calculate the weight relationships between each node and their adjacent nodes. Thus, this mechanism can aggregate the global context information of the template and search nodes and activate feature channels based on weights and biases to obtain more discriminative feature information. Moreover, we leverage a multi-level dropout mechanism to perform the data dropout, the layer dropout, and the feature dropout on the data, network, and attention levels, respectively, to avoid overfitting of local-specific information and improve the generalization ability. Extensive experiments show the proposed method achieves superior performance on seven challenging benchmark datasets, i.e., OTB100, OTB2013, UAV123, LaSOT, GOT10K, VOT2020, and TrackingNet. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Aggregates

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Fusion of Infrared and Visible Images Using Fuzzy Based Siamese Convolutional Network

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computers, Materials & Continua 2022年第3期70卷 5503-5518页

作者： Kanika Bhalla Deepika Koundal Surbhi Bhatia Mohammad Khalid Imam Rahmani Muhammad Tahir Department of Electrical Engineering National Taipei University of TechnologyTaipei10608Taiwan Department Virtualization School of Computer ScienceUniversity of Petroleum&Energy StudiesDehradunIndia College of Computer Science and Information technology King Faisal University36362Saudi Arabia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia

Traditional techniques based on image fusion are arduous in integrating complementary or heterogeneous infrared(IR)/visible(VS)*** in various kind of features in these images are vital to preserve in the single fused ***,simultaneous preservation of both the aspects at the same time is a challenging ***,most of the existing methods utilize the manual extraction of features;and manual complicated designing of fusion rules resulted in a blurry artifact in the fused ***,this study has proposed a hybrid algorithm for the integration of multi-features among two heterogeneous ***,fuzzification of two IR/VS images has been done by feeding it to the fuzzy sets to remove the uncertainty present in the background and object of interest of the ***,images have been learned by two parallel branches of the siamese convolutional neural network(CNN)to extract prominent features from the images as well as high-frequency information to produce focus maps containing source image ***,the obtained focused maps which contained the detailed integrated information are directly mapped with the source image via pixelwise strategy to result in fused *** parameters have been used to evaluate the performance of the proposed image fusion by achieving 1.008 for mutual information(MI),0.841 for entropy(EG),0.655 for edge information(EI),0.652 for human perception(HP),and 0.980 for image structural similarity(ISS).Experimental results have shown that the proposed technique has attained the best qualitative and quantitative results using 78 publically available images in comparison to the existing discrete cosine transform(DCT),anisotropic diffusion&karhunen-loeve(ADKL),guided filter(GF),random walk(RW),principal component analysis(PCA),and convolutional neural network(CNN)methods.

关键词： Convolutional neural network fuzzy sets infrared and visible image fusion deep learning

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Behind the Scenes: An Explainable Artificial Intelligence (XAI) on the Service Classification of the 5G/B5G Network 3

Behind the Scenes: An Explainable Artificial Intelligence (X...

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3rd International Conference on Digital Transformation and Applications, ICDXA 2024

作者： Allias, Noormadinah Kadir, Diyana Ab Abdullahi, Akibu Mahmoud Ismail, Shahrinaz Tunku Abdul Rahman University of Management and Technology Faculty of Computing and Information Technology Kuala Lumpur Malaysia Computer Engineering Technology Universiti Kuala Lumpur- Malaysia Institute of Information Technology Kuala Lumpur Malaysia School of Computing and Informatics Albukhary International University Kedah Malaysia Kuala Lumpur Malaysia

ISBN: (纸本)9798350373424

Fifth generation and beyond (5G/B5G) is part of the next generation of mobile technology, which is expected to offer more capacity and faster speeds than the previous generation Long-Term Evolution (LTE) network. These features enable 5G/B5G to offer users a wide range of services, including smart cities, entertainment and multimedia, healthcare and mission-critical applications that benefit the entire economy and communities. However, due to growing demand, telecom service providers need to provide better Quality of service (QoS) on their networks to meet user expectations. Therefore, it is necessary to implement service classification that enables service providers to select the right network slices for each service to improve network QoS. Previous studies have predicted the classification of 5G/B5G services using traditional machine learning algorithms such as random forest and decision tree, achieving good accuracy. However, prediction based on black-box machine learning models was not transparent enough, so mobile service providers could not understand the reliability and interpretation of the results. Therefore, this article aims to model the system performance of 5G Key Performance Indicators (KPI) and extend the experiment to Explainable Artificial Intelligence (XAI) by using the Explainable AI to look behind the scenes of the chosen black-box models for service classification of 5G/B5G networks, as this is crucial for telecom service providers to make critical investment decisions around customer and employee experience. The results from the experiments show that the random forest has the highest confidence towards class Label 3 with the probability of 35 percent. © 2024 IEEE.

关键词： Decision trees

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Handling of Computationally Demanding Digital Controllers in Power System Dynamic Simulations

Handling of Computationally Demanding Digital Controllers in...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Mehran Jafari Gautier Bureau Marco Chiaramello Adrien Guironnet Patrick Panciatici Petros Aristidou Dept. of Electrical Eng. Computer Eng. & Informatics Cyprus University of Technology Limassol Cyprus Réseau de Transport d’ Électricité (RTE) France

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

Nowadays Smart grids utilize digital controllers to guarantee the reliable and efficient operation of their components. However, the numerical simulation of these types of controllers is challenging due to the numerous discrete time events introduced. The interpolation-based method (IBM) can effectively simulate smart digital controllers alongside the differential-algebraic equations of the system under control. Compared to the traditional step-reduction method (SRM) that reduces the time step for each time event during the simulation, IBM allows the use of variable time steps and solves the system while ensuring simulation accuracy. However, in the case of computationally demanding controllers, the computational performance of IBM suffers significantly. In this paper, a modified version of IBM is introduced, which can handle computationally demanding controllers in dynamic simulation of power systems. The performance of the proposed method is assessed and compared to SRM and IBM by simulating a test system with different controllers.

关键词： Accuracy Computational modeling Power system dynamics Control systems Numerical simulation Mathematical models Smart grids Power system reliability Reliability

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RF-PSSM:A Combination of Rotation Forest Algorithm and Position-Specific Scoring Matrix for Improved Prediction of Protein-Protein Interactions Between Hepatitis C Virus and Human

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Big Data Mining and Analytics 2023年第1期6卷 21-31页

作者： Xin Liu Yaping Lu Liang Wang Wei Geng Xinyi Shi Xiao Zhang School of Medical Informatics and Engineering Xuzhou Medical UniversityXuzhou 221000China College of Computer Science and Technology China University of Mining and TechnologyXuzhou 221116China Laboratory Medicine Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhou 310005China

The identification of hepatitis C virus(HCV)virus-human protein interactions will not only help us understand the molecular mechanisms of related diseases but also be conductive to discovering new drug *** increasing number of clinically and experimentally validated interactions between HCV and human proteins have been documented in public databases,facilitating studies based on computational *** this study,we proposed a new computational approach,rotation forest position-specific scoring matrix(RF-PSSM),to predict the interactions among HCV and human *** particular,PSSM was used to characterize each protein,two-dimensional principal component analysis(2DPCA)was then adopted for feature extraction of ***,rotation forest(RF)was used to implement *** results of various ablation experiments show that on independent datasets,the accuracy and area under curve(AUC)value of RF-PSSM can reach 93.74% and 94.29%,respectively,outperforming almost all cutting-edge *** addition,we used RF-PSSM to predict 9 human proteins that may interact with HCV protein E1,which can provide theoretical guidance for future experimental studies.

关键词： protein-protein interactions hepatitis C virus position specific scoring matrix two-dimensional principal component analysis rotation forest

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NPRportrait 1.0:A three-level benchmark for non-photorealistic rendering of portraits

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Computational Visual Media 2022年第3期8卷 445-465页

作者： Paul L.Rosin Yu-Kun Lai David Mould Ran Yi Itamar Berger Lars Doyle Seungyong Lee Chuan Li Yong-Jin Liu Amir Semmo Ariel Shamir Minjung Son Holger Winnemöller School of Computer Science and Informatics Cardiff UniversityCardiffUK School of Computer Science Carleton UniversityOttawaCanada Department of Computer Science and Technology Tsinghua UniversityBeijingChina Reichman University(the Interdisciplinary Center) HerzliyaIsrael Department of Computer Science and Engineering Pohang University of Science and TechnologyPohangRepublic of Korea Lambda Labs Inc.San FranciscoUSA Hasso Plattner Institute University of PotsdamPotsdamGermany Multimedia Processing Laboratory Samsung Advanced Institute of TechnologySuwonRepublic of Korea Adobe Systems Inc.San JoseUSA

Recently,there has been an upsurge of activity in image-based non-photorealistic rendering(NPR),and in particular portrait image stylisation,due to the advent of neural style transfer(NST).However,the state of performance evaluation in this field is poor,especially compared to the norms in the computer vision and machine learning ***,the task of evaluating image stylisation is thus far not well defined,since it involves subjective,perceptual,and aesthetic *** make progress towards a solution,this paper proposes a new structured,threelevel,benchmark dataset for the evaluation of stylised portrait *** criteria were used for its construction,and its consistency was validated by user ***,a new methodology has been developed for evaluating portrait stylisation algorithms,which makes use of the different benchmark levels as well as annotations provided by user studies regarding the characteristics of the *** perform evaluation for a wide variety of image stylisation methods(both portrait-specific and general purpose,and also both traditional NPR approaches and NST)using the new benchmark dataset.

关键词： non-photorealistic rendering(NPR) image stylization style transfer portrait evaluation benchmark

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