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Solar Energy-Based Virtual Machine Placement Algorithm for Geo-distributed Datacenters 23

Solar Energy-Based Virtual Machine Placement Algorithm for G...

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23rd IEEE international conference on Software Quality, Reliability, and Security Companion, QRS-C 2023

作者： Panda, Sanjaya Kumar Chopra, Sahil Padhi, Slokashree National Institute of Technology Warangal Department of Computer Science and Engineering Telangana Warangal506004 India

ISBN: (纸本)9798350359398

The cloud computing market is continually rising due to the digital transformation of business sectors, the adoption of information technology devices and the ease of access to the Internet. However, this rise has numerous challenges, including power consumption, customization, security, and compliance. Traditionally, power is generated using fossil fuels, which run the components of datacenters, such as servers, cooling, storage and network systems. Fossil fuels emit carbon dioxide, heat and other gases, directly impacting the environment. Therefore, cloud service providers (CSPs) seek environment-friendly solutions using renewable energy sources to run the datacenters. On the other hand, the datacenters' servers can host multiple customer requests by deploying virtual machines (VMs). The improper placing of the VMs in the servers of datacenters can lead to more energy consumption and increase the overall cost. Recent studies show that VM placement algorithms use renewable energy sources. However, they dispatch the VMs chronologically without considering the types of VMs and servers. This paper proposes a solar energy-based VM placement (SEVMP) algorithm for geo-distributed datacenters. The proposed algorithm dispatches the VMs to the corresponding servers based on their types (groups) and costs, such as power, brown energy usage and fragmentation. Moreover, it selects an appropriate VM from a set of VMs arrived simultaneously to minimize the energy consumption and the overall cost. The SEVMP is simulated by varying VMs, servers and datacenters. The simulation results of SEVMP are compared with four state-of-the-art algorithms to show its effectiveness in the average energy cost, the total energy cost and the number of accepted VMs. © 2023 IEEE.

关键词： Energy utilization

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IoT Equipment ID and Blockchain Driven Internet Fused Learning 3

IoT Equipment ID and Blockchain Driven Internet Fused Learni...

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3rd international conference on Intelligent Engineering and Management, ICIEM 2022

作者： Kumar, D. Dinesh Batla, Vishnu Murtaza Alvi, Syed Ahad Deb, Nabamita Singh, Shweta Bhardwaj, Vikas St. Joseph's College of Engineering Department of Electronics and Instrumentation Engineering Tamilnadu Chennai India Computer Science and Engineering Department Prayagraj Allahabad India King Saud University College of Applied Computer Sciences Riyadh Saudi Arabia Gauhati University Department of Information Technology Assam Guwahati India IES College of Technology Electronics and Communication Department MP Bhopal India Dewan VS Institute of Engineering and Technology UP Meerut India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

Industrial Internet has become a burgeoning study subject as the Internet of Things (IoT), 5G, and current innovation have advanced. Because of the current claim to fame, increased requirements for effort deferment, wellness, and dependability of the distinctive proof investigation administration have been established. Because of the single kind of distinguishing proof topic and powerless acquaintance with security insurance, the conventional DNS can't satisfy the specifications of the new cyberspace. This paper responds by using Block Chain associated with fused learning in presentation of Internet-distinguishing-proof. BC likely to be a distributed foundation that is commonly used in computerized scrambled monetary standards, like as Bit coin, and can provide safe stoke of information with accessibility. Combined training assures particular terminal information that allows for proficient AI among various participants. Our suggested unified training and Block Chain mix offers a heavy framework towards the evolution of the upcoming contemporary Internet, according to the mathematical results. © 2022 IEEE.

关键词： Internet of things

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What Can My Car Tell Me? Consumer Perceptions of Transparency in Self-Driving Vehicles 3

What Can My Car Tell Me? Consumer Perceptions of Transparenc...

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3rd IEEE international conference on Human-Machine systems, ICHMS 2022

作者： Huff, Earl W. Tucker, Natalie Grady, Siobahn Day Brinkley, Julian University of Texas at Austin School of Information AustinTX United States North Carolina Central University School of Library and Information Sciences DurhamNC United States Clemson University School of Computing ClemsonSC United States

ISBN: (数字)9781665452380

ISBN: (纸本)9781665452380

Fully autonomous or 'self-driving' vehicles are emerging mobility technology with potential benefits over conventional motor vehicles. Proponents argue that the widespread adoption of autonomous vehicles may save countless lives and millions of dollars annually by minimizing the likelihood of deadly vehicle crashes. However, widespread adoption of automated-driving technologies is required to realize such benefits, which research suggests, may be undermined by consumer concerns about vehicle operation transparency. Further, there is insufficient research into consumer perceptions of an autonomous vehicle's communication and information-sharing behavior, which may impact their likelihood of purchasing one. We conducted a study using a 63-question internet-based survey distributed in the United States to licensed drivers 18 years of age and older (n=996) to examine consumer perceptions of autonomous vehicles across accountability, communication, information sharing, and concerns. Our findings show that consumer perceptions of the four dimensions vary significantly across race, gender, and ability. © 2022 IEEE.

关键词： Autonomous vehicles

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DDoS Cyber-Attacks Detection-Based Hybrid CNN-LSTM 3rd

DDoS Cyber-Attacks Detection-Based Hybrid CNN-LSTM

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3rd international conference on Computing and Communication Networks, ICCCN 2023

作者： Khaleel, Thura Jabbar Shiltagh, Nadia Adnan Iraqi Commission for Computers and Information/Informatics Institute for Postgraduate Studies Baghdad Iraq Computer Engineering Department College of Engineering University of Baghdad Baghdad Iraq

ISBN: (纸本)9789819708918

Protecting software-defined networking (SDN) against cyber-attacks has become crucial in an expanding digital threat environment. distributed Denial-of-Service (DDoS) attacks are risky since they may seriously interrupt operations. To mitigate these risks, this study introduces an anomaly detection method that utilizes a hybrid convolutional and short-term memory (CNN-LSTM) deep neural network. This model merges the CNN's ability to automatically extract spatial features with the LSTM's proficiency in sequence modeling, thereby enhancing the detection of anomalies in network traffic metadata. The model also integrates an autoencoder structure to facilitate representation learning and reduce dimensionality. The model's effectiveness was tested using publicly accessible SDN datasets, and the results were remarkable. The model identified DDoS attacks with an accuracy rate of over 99%, surpassing the performance of previous shallow learning models. Moreover, the model proved highly adaptable, successfully detecting attacks across various data samples. This deep learning-based detection system is a significant advancement, providing precise and efficient analytics that bolster real-time cybersecurity monitoring. However, it's crucial to continue research in deployment, interpretability, and the potential of combinatorial learning with other advanced technologies. We can only fully harness the great potential of artificial intelligence for adequate cyber protection by looking into these areas. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Denial-of-service attack

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3rd international conference on Machine Intelligence and Smart systems, MISS 2023

3rd International Conference on Machine Intelligence and Sma...

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3rd international conference on Machine Intelligence and Smart systems, MISS 2023

ISBN: (纸本)9783031317224

The proceedings contain 59 papers. The special focus in this conference is on Machine Intelligence and Smart systems. The topics include: Chronic Kidney Disease Prediction and Interpretation Using Explainable AI;systematic Review and Analysis of Artificial Intelligence-Based Breast Cancer Classification and Detection;war of Tweets: Sentiment Analysis on Ukraine Russia Conflict;Implementing HRRN for Evaluating Cloud Performance Using Reinforcement Learning;using Machine Learning for Prediction of Obstructions for Indoor Location systems;privacy Threats and Protection in Artificial Intelligence and Machine Learning;Combining Linguistic information with BERT for Span Based End-to-End Aspect Based Sentiment Analysis;a Dimensionality Reduction Model: A Retrospective Approach on Dementia Triggering Parameters and Feature Ranking;effective Identification of Lung Diseases Using Few-Shot Learning;comparative Study on Classification Based-Data Mining Techniques in Early Diabetes Prediction;optimize Machine Learning Model for Sentiment Analysis of Online Education During Covid-19 Pandemic;review on the Challenges and Future Directions of Deep Learning-Based Techniques for Advance Prediction of Cardiac Attack;different Techniques for Detecting Plant Leaf Disease Using Machine Learning;proposed Framework of Extensive Humanoid Design Cycle and Recent Developments in Bipedal Walk;natural Language Processing for Waste Management Using Public Opinions in Smart Cities;prediction of Diabetes During Pregnancy Through Fog Environment;empirical Wavelet Transform Grounded Poignant Ground Target Recognition and Classification by Seismic Signal Processing;A Powered-Up Classification of Disabling distributed Network Cloud-Based Attacks Using MLPNN-BP and MLPNN-LM;stroke Prediction Framework Based on Missing Value information and Outlier Detection by Using Machine Learning Techniques in E-Healthcare;magnetic Resonance Imaging Digitization for Brain Abnormality Recognition.

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3rd international conference on Machine Intelligence and Smart systems, MISS 2023

3rd International Conference on Machine Intelligence and Sma...

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3rd international conference on Machine Intelligence and Smart systems, MISS 2023

ISBN: (纸本)9783031691140

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Analysis and suppression of bifurcation behaviors for a new electric energy router based on series-parallel architecture 3

Analysis and suppression of bifurcation behaviors for a new ...

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3rd IEEE international Power Electronics and Application conference and Exposition, PEAC 2022

作者： Zhang, Zehui Yang, Li Zhao, Xiaojun Wang, Xiaohuan Zhang, Chunjiang YanShan University School of Electrical Engineering Qinhuangdao China

ISBN: (数字)9781665491419

ISBN: (纸本)9781665491419

With the popularity of distributed generations (DGs), electric energy routers (EER) integrating DGs have been widely used in low-voltage distribution network (LVDN). A series-parallel architecture EER (SPA-EER) for LVDN has been proposed to make up for shortcomings of series architecture EER (SA-EER) in energy flexible operation. However, when some parameters in the SPA-EER system change beyond a certain range, the system will present low-or high-frequency bifurcation behaviors, resulting in system oscillation and instability. To analyze and suppress bifurcation behaviors in the SPA-EER system, the discrete models of series and parallel converters are respectively established to obtain the operational stability domains of above parameters. Then, a new bifurcation behavior suppression method is proposed to enhance these stability domains, in which a second-order generalized integrator (SOGI) is introduced into the traditional time-delayed feedback control (TDFC), namely SOGI-TDFC, to compensate for the shortcoming of traditional TDFC. Finally, the simulation results verify the correctness of the theoretical analysis and the proposed control method. © 2022 IEEE.

关键词： distributed power generation

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Suspension Control Sensors Embedded with Smart Grid- Smart Car System 3

Suspension Control Sensors Embedded with Smart Grid- Smart C...

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3rd international conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2023

作者： Sasirekha, R. Nandhini, P. Kalpana, R. Saraswathi, T. Judi, Asha Padmavathy, T. Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering VelTech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College Avadi Chennai India Department of Information Technology Easwari Engineering College Chennai Ramapuram India Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Department of Computer Science and Engineering Sri Venkateswara College of Engineering Chennai India

Nowadays, sensors have become an integral part of human lives. Generaly, sensors are considered as the fastest sensing device, which can sense the environment and transmit the data in a fraction of second. Most of the tracking systems use sensors to navigate anything. Several types of sensors are currently used to transfer data in any medium. Every day, numerous vehicular accidents are reported in India. Most of the accidents occur due to the lack of safety precautions. Hence, this research study aims to develop a sensor based model for preventing accidents. The proposed model integrates the distributed systems, cyber-physical system and suspension control sensors. The proposed model is then integrated into the moving vehicles for monitoring the roadway and the surrounding environment. © 2023 Elsevier B.V.. All rights reserved.

关键词： Smart power grids

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Research on Proof of Stake Consensus Algorithm Based on Dynamic Trust 3

Research on Proof of Stake Consensus Algorithm Based on Dyna...

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3rd international conference on Signal Image Processing and Communication, ICSIPC 2023

作者： Jiang, Yuhao Zhao, Jinyi Chen, Taowei School of Information Yunnan University of Finance and Economics Kunming China School of Logistics and Management Engineering Yunnan University of Finance and Economics Kunming650221 China

ISBN: (纸本)9781510670945

Blockchain is a decentralized and tamper-proof distributed ledger technology. The consensus algorithm is one of the key technologies underlying blockchain. The Proof of Stake (PoS) consensus mechanism determines the next block producer on the blockchain based on the user's staked equity. Compared to Proof of Work (PoW), the Proof of Stake consensus mechanism solves the problem of wasted resources. However, the PoS consensus mechanism faces serious issues such as the coin age accumulation attack and the zero-cost benefit problem. Therefore, this paper proposes a Trust-Based Proof of Stake (TPoS) mechanism based on dynamic trustworthiness. TPoS divides nodes in the network into miner nodes and basic equity representative (shareholder) nodes, and assigns corresponding trustworthiness to nodes based on their participation in creating blocks. Shareholder nodes sign blocks and assign them trustworthiness, and finally compete for the weight of trustworthiness obtained by blocks to go on the chain. In addition, this paper analyzes the attack cost and system response to bribery attacks and common equity accumulation attacks. The results of simulation experiments show that the TPoS mechanism has significant advantages over traditional Proof of Stake mechanisms in dealing with bribery attacks and equity accumulation attacks. © 2023 SPIE.

关键词： Blockchain

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Optimal configuration of multi energy flow system of electric heating and cooling air considering source load uncertainty 3

Optimal configuration of multi energy flow system of electri...

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3rd international conference on Mechanical, Electronics, and Electrical and Automation Control, METMS 2023

作者： Xing, Jiawei Sun, Shumin Yu, Peng Cheng, Yan Li, Yong Wang, Shibai Wang, Yuejiao Li, Sun Wang, Di Ai, Qian State Grid Shandong Electric Power Research Institute Jinan250003 China State Grid Shandong Electric Power Company Jinan250001 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781510666689

Multi energy flow coupling, such as electric heating and cooling, is an important feature of integrated energy system. Aiming at the uncertainty of source load caused by the deviation of wind and solar output prediction and load growth prediction in the optimal configuration of multi energy flow system, an optimal configuration method of electric heating and cooling multi energy flow system considering the uncertainty of source load is proposed. Firstly, the physical mechanism and characteristics of the key distributed energy equipment and energy supply network in the multi flow energy supply network of the energy hub are analyzed;The information gap decision theory is used to deal with the prediction deviation caused by the increase of electric heating and cooling air load in the model, and the conditional risk value theory is used to adjust the modeling scheme to assess the risk loss caused by the wind and solar power output prediction deviation. The example analysis shows the optimal allocation results of the deterministic model and the model taking into account uncertainty. The comparison with other optimal allocation methods verifies the effectiveness and superiority of the method in this paper. At the same time, it analyzes the impact of the changes in the avoidance coefficient and risk coefficient in the model on the model results and investment strategies, which proves that the model has the ability to quantify and evaluate the output uncertainty on both sides of the source load. © 2023 SPIE. All rights reserved.

关键词： Forecasting

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