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Predictive virtual machine placement for energy efficient scalable resource provisioning in modern data centers 8

Predictive virtual machine placement for energy efficient sc...

引用

8th International Conference on Computing for Sustainable Global Development, INDIACom 2021

作者： Bharanidharan, G. Jayalakshmi, S. VISTAS Department of Computer Science Chennai India VISTAS Dept. of Computer Applications Chennai India

ISBN: (纸本)9789380544434

In modern data Centers (DCs), the major significant and challengeable task is resource management of cloud and efficient allocation of Virtual Machines (VMs) or containers in Physical Machines (PMs). There are several schemes proposed regarding this factor that includes VM placement considering utilization of resources. The process of consolidation may be done efficiently using 'opportunities' discovery for migrating VMs and estimating utilization of resource to VM placement. However, the deduction of energy utilized over cloud DCs by physical resources with heterogeneous mode gets accomplished using consolidation of VM. This assists in minimize of PM numbers to be utilized and rely on constraints of Quality of Services (QoS). Therefore, this paper has proposed a predictive VM placement using an efficient Learning Automata (LA) with probability distribution activity set and it can be represented as Probability Distribution Action-set Learning Automata (PDALA) which results to the VM placement over heterogeneous cloud DCs. Thus, the proposed algorithm gets beneficial by implementing LA theory and correlation coefficient parameter to generate best decision making over VM allocation. Moreover, CloudSim plus simulator is used to simulate results and the simulation output gets compared with Power Aware Best Fit Decreasing (PABFD) as reactive VM placement. The proposed PDALA method performance is evaluated using parameters like VM migration, SLA Violation and energy consumption having comparatively better performance than existing reactive VM placement. © 2021 Bharati Vidyapeeth, New Delhi. Copy Right in Bulk will be transferred to IEEE by Bharati Vidyapeeth.

关键词： Virtual machine

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ABC-DE-WOA: A New Hybrid Algorithm for Optimization Problems 4

ABC-DE-WOA: A New Hybrid Algorithm for Optimization Problems

引用

4th International Conference on Circuits, Control, Communication and Computing, I4C 2022

作者： Pradeep Kumar, D. Sowmya, B.J. Kanavalli, Anita Vincent, Annvin Dept. of Computer Science and Engineering Bangalore India Dept. of Artificial Intelligence and Data Science Bangalore India

ISBN: (纸本)9798350397475

One of the most effective swarm intelligence-based algorithms for many global optimization issues is the Artificial Bee Colony (ABC) strategy. Despite the fact that there are many Artificial Bee Colony (ABC) variants, the algorithm normally has a low convergence rate. Therefore, it is still essential to moderate an algorithm's intensity and diversity. In this instance, the standard Artificial Bee Colony (ABC) algorithm has been combined with the Whale Optimization Algorithm (WOA) and Differential Evolution Algorithm (DE) to generate a novel Hybrid Artificial Bee Colony algorithm (ABC), Artificial Bee Colony-Differential Evolution-Whale Optimization Algorithm (ABC-DE-WOA). For simple benchmark problems with up to 100 dimensions, 50 dimensions, 30 dimensions, and 10 dimensions, the proposed hybrid technique is compared with Artificial Bee Colony (ABC) variants like Artificial Bee Colony-Whale Optimization Algorithm (ABC-WOA), Artificial Bee Colony-Differential Evolution Algorithm (ABC-DE), and original Artificial Bee Colony Algorithm (ABC). The results show that the proposed technique performs better than its competitors in terms of convergence speed. © 2022 IEEE.

关键词： Global optimization

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Genome Assembly : A Review 7

Genome Assembly : A Review

引用

7th International Conference on Advanced Computing and Communication Systems, ICACCS 2021

作者： Kumar, Arun Verma, Vishal Chaudhary Ranbir Singh University Dept. of Computer Science and Applications Jind India

ISBN: (纸本)9781665405201

Genome is complete set of DNA, including all of its genes. After getting reads from sequencing technologies, it's a huge task to reconstruct the original genome because there are millions of overlapping reads which are of poor quality at ends and generate many types of errors while reconstructing. A number of techniques and technologies are already there but still there is need of tools which are fast and accurate for assembling genomes. These tools are based on various algorithms and error handling techniques. Primarily we discussed OLC and De Bruijn Graph. Also, there is discussion related to different techniques used to structure genome using above graph concepts. Also we have discussed about different tools which are already being used and their specific roles. © 2021 IEEE.

关键词： advanced computing bruijn graph communication system de bruijn graph genome assembly genome assembly algorithm genome sequence layout consensus overlap layout sequencing technology short read

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Fine Grained Sentiment Analysis of Malayalam Tweets Using Lexicon Based and Machine Learning Based Approaches 4

Fine Grained Sentiment Analysis of Malayalam Tweets Using Le...

引用

4th Biennial International Conference on Nascent Technologies in Engineering, ICNET 2021

作者： Soumya, S. Kumar, Pramod Cochin University of Science and Technology Dept. of Computer Applications Kerala Cochin India

ISBN: (纸本)9781728190617

Fine-Grained Sentiment Analysis (FGSA) of Malayalam Tweets have been implemented in this work. The tweets are classified into positive, strongly positive, negative, strongly negative, and neutral sentiments. Both lexicon-based and machine learning-based approaches are used for sentiment classification of Malayalam Tweets. Lexicon based approach uses both dictionary-based and corpus-based approach. The dictionary-based approach is used in this work. The machine learning algorithms such as Support Vector Machine (SVM) and Random Forest (RF) classifiers are used for sentiment classification of the dataset. Bag of Words (BoW), Term-Frequency vs. Inverse Document Frequency (TF-IDF), and Sentiwordnet feature matrices are used to vectorize the input dataset. Lexicon based approach got an accuracy of 84.8%. In machine learning algorithms, the SVM (kernel = linear), SVM (kernel = RBF) and RF with the Sentiwordnet feature vector got an accuracy of 92.6%, 92.9%, and 93.4%, respectively. © 2021 IEEE.

关键词： Sentiment analysis

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Overdispersed black-box variational inference 32

Overdispersed black-box variational inference

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32nd Conference on Uncertainty in Artificial Intelligence 2016, UAI 2016

作者： Ruiz, Francisco J.R. Titsias, Michalis K. Blei, David M. Data Science Institute Dept. of Computer Science Columbia University United States Dept. of Informatics Athens University of Economics and Business Greece Data Science Institute Dept. of Computer Science and Statistics Columbia University United States

ISBN: (纸本)9781510827806

We introduce overdispersed black-box variational inference, a method to reduce the variance of the Monte Carlo estimator of the gradient in black-box variational inference. Instead of taking samples from the variational distribution, we use importance sampling to take samples from an overdispersed distribution in the same exponential family as the variational approximation. Our approach is general since it can be readily applied to any exponential family distribution, which is the typical choice for the variational approximation. We run experiments on two non-conjugate probabilistic models to show that our method effectively reduces the variance, and the overhead introduced by the computation of the proposal parameters and the importance weights is negligible. We find that our overdispersed importance sampling scheme provides lower variance than black-box variational inference, even when the latter uses twice the number of samples. This results in faster convergence of the black-box inference procedure.

关键词： Importance sampling

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Two-Phase Deep Q Learning Network for Secure Healthcare Model in the Internet of Things 2

Two-Phase Deep Q Learning Network for Secure Healthcare Mode...

引用

2nd International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Selvam, Thamizh D. Vinothkumar, J. Madhubala, S. Dept. of Computer Science Rajiv Gandhi Arts and Science College Puducherry India Dept. of Computer Applications Rajiv Gandhi Arts and Science College Puducherry India

ISBN: (纸本)9798331541217

The Internet of Things (IoT) embodies a revolutionary networking technology that links both living beings and inanimate objects. Its utilization is rapidly growing across diverse sectors, particularly in healthcare, where it is instrumental in enabling healthcare providers and individuals to monitor and diagnose diseases. It is crucial to ensure the security of healthcare data on IoT devices to prevent intermediary attacks and unauthorized access. This study explores the increasing security challenges associated with IoT in the healthcare field. To enhance the security and privacy of healthcare data, we propose a combination of the Two-Phase Deep Q Learning Network (TPDQN) and the Deep Learning Network (DLN). The DLN is primarily focused on authenticating certified IoT devices to prevent intermediate attacks, while the TPDQN is designed to detect and mitigate Distributed Denial of Service (DDoS) attacks and malware as they traverse multiple locations. The effectiveness of the proposed solution is measured using metrics such as mean square error (MSE), longevity, accuracy, throughput, and energy consumption, demonstrating improved performance relative to existing solutions. © 2024 IEEE.

关键词： Denial-of-service attack

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Enhancing 5G Efficiency: Regression Analysis for Resource Allocation Optimization in Wireless Networks

Enhancing 5G Efficiency: Regression Analysis for Resource Al...

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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Padmageetha, B.G. Kumar Naik, Pramod Patil, Mallanagouda Dayananda Sagar University Dept. of Computer Applications Bengaluru India Dayananda Sagar University Dept. of Computer Science and Engineering Bengaluru India RVITM Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350378092

The advent of 5G networks signifies a major breakthrough in mobile communications, providing better data rates, low latency, and improved connectivity. Efficient resource allocation within 5G networks is paramount to fully leverage these capabilities, ensuring optimal performance and user satisfaction. Traditional resource allocation methods often struggle to keep pace with the dynamic and complex nature of 5G environments. The potential benefits of machine learning (ML) is explored in this research to enhance resource allocation in 5G networks. We begin by examining the unique challenges posed by 5G networks, by ML approaches employed for resource allocation, including supervised learning such as Trees, SVM, Neural Networks. Our study we train the model using MATLAB simulator. Analysis on the response and residual plot is conducted for predicted response. Analysis and comparative study is made to find the best performance metric suitable for the predicting the model for resource allocation. The study shows the improvisation in the metrics of regression learner. Simulation results demonstrate significant improvements in network performance. Finally, we have done the comparison between the results of MATLAB simulation. This study gives better decisions to service providers to enhance the overall performance of network © 2024 IEEE.

关键词： MATLAB

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Multi-level secure framework (MLSF) for composite Web services 09

Multi-level secure framework (MLSF) for composite Web servic...

引用

2nd International Conference on Interaction sciences: Information Technology, Culture and Human, ICIS 2009

作者： Sathiaseelan, J.G.R. Rabara, S.Albert Martin, J.Ronal Dept of Computer Applications Tiruchirappalli - 620 017 India Dept. of Computer Science Tiruchirappalli - 620 002 India

ISBN: (纸本)9781605587103

The Web services technology is the emerging field in the area of Web engineering which emphasizes on designing web services-based applications, architectural models and standards, web services technology platforms, tools and specifications for building standard web services and WS-Security technologies. The web services technologies change the software industry dramatically by developing and integrating enterprise web services and applications so as to enable the users to access them. The web services platform is an integration platform for applications and data of the enterprises. Researchers put on efforts to bring out the state-of-the art in web services technologies and security technologies for web services. Web service composition is the combination of web services from different service providers to create a more sophisticated, value added web service to the web users. The composition of web services is another promising area for research and development. There are several research initiatives in the field of Web services for enterprise applications. However, none of the initiatives have attempted for educational institution applications using Web services technology. A study reveals that there are number of approaches providing secure web services. However, there is no attempt made so far to secure the services at multi-level. This paper proposes a Multi-level Secured Framework (MLSF) for academic institutions that provides secured composite web services such as admission service, fees payment service, library service, personalized service for the students, staff and management etc. The MLSF enhances the security at various levels such as user level, device level, web services manager level and Institutional services level. Copyright © 2009 ACM.

关键词： Web services

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Finding Optimal Routes in MaaS Framework using ParetoBFS 6

Finding Optimal Routes in MaaS Framework using ParetoBFS

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6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022

作者： Mitra, Poojarini Rehena, Zeenat Mukherjee, Nandini University of Engineering & Management Dept. of Computer Applications Kolkata India Aliah University Dept. of Computer Science & Engineering Kolkata India Jadavpur University Dept. of Computer Science & Engineering Kolkata India

ISBN: (纸本)9781665410359

To offer Mobility as a Service (MaaS) to the consumers while handling time-dependent multi-modal transportation and maintaining multiple criteria is a complex task. The system needs to be intelligent enough to provide optimal routes within the least possible computation time. This paper proposes a simple method that seeks to provide a solution by using the ParetoBFS algorithm, a modified version of the traditional BFS algorithm, which uses Pareto constraints to prune the graph and find all Pareto-optimal paths in a network considering multiple criteria. Evaluations with different scenarios were performed using the proposed mechanism and its performance was compared with Weighted-Sum Dijkstra's Algorithm. It can be observed that the proposed mechanism is achieving better results than Weighted-Sum Dijkstra's Algorithm. © 2022 IEEE.

关键词： Pareto principle

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A comparative study on video steganography in spatial and IWT domain

A comparative study on video steganography in spatial and IW...

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2016 IEEE International Conference on Advances in computer applications, ICACA 2016

作者： Rosemary Euphrasi, K. Mary Shanthi Rani, M. Dept. of Computer Science Fatima College Madurai India Dept. of Computer Science and Applications Gandhigram Rural Institute Deemed University Gandhigram Dindigul India

ISBN: (纸本)9781509037704

Steganography is a technique for embedding digital information inside another digital medium such as text, images, audio signals or video signals, without revealing its presence in the medium. In video steganography, a video file will be used as a cover medium within which any secret message can be embedded. In steganography, the secret information can be hidden either directly by altering the pixel values of the images in the spatial domain or in the frequency components of the images after transforming the images into frequency domain by using transformation algorithms such as DCT (Discrete Cosine Transform), DWT(Discrete Wavelet Transform) and IW(Integer Wavelet Transform). In this paper, secret data are embedded inside a video file using both the methods, spatial and frequency, and the outcomes are analysed and compared. Results are compared based on PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error), BER (Bit Error Rate) and Standard Deviation. The findings of this study are given as suggestions for further enhancement. © 2016 IEEE.

关键词： Steganography

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