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检索条件"任意字段=2nd International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering"

共 1401 条记录，以下是161-170 订阅

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Automated Denial of Service Detection Using Moth Flame Optimization With Machine Learning in cloud Environment 2

Automated Denial of Service Detection Using Moth Flame Optim...

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2nd international conference on Smart Technologies and Systems for Next Generation computing, ICSTSN 2023

作者： Thillaivanan, Alagu Wategaonkar, Somnath Raghunath Duraisamy, Suganthi Mishra, Ravi Nagaraj, S. Singh, Kamlesh Shadan College of Engineering and Technology Peerancheru Hyderabad India Electronics and Telecommunication Bharati Vidyapeeth College of Engineering Maharashtra Navi Mumbai India Saveetha College of Liberal Arts and Sciences SIMATS Tamilnadu Chennai India Electronics and Telecommunication Engineering GHRIET Maharashtra Nagpur India Department of Computer Science and Engineering & IT Jain University Karnataka Bengaluru India Department of Computer Science and Engineering Graphic Era Hill University Dehradun Campus Uttarakhand Dehradun India

ISBN: (纸本)9798350348002

Denial of Service (DoS) attack detection refers to preventing and detecting malicious attempts to make network resources or services unavailable to its intended users. DoS attacks is been a main concern for organizations since they can disturb the accessibility of critical services and cause economic losses. In cloud environments, the mitigation and detection of such attacks were very challenging because of the dynamic and distributed nature of infrastructure. In this regard, Machine Learning (ML) methods are potential in identifying DoS attacks, by using network traffic features to find unusual anomalies or paradigms that may specify an attack. This research work introduces an automated Denial of Service Detection using Moth Flame optimization with Machine Learning (DoSD-MFOML) technique in cloud environment. The DoSD-MFOML technique recognizes DoS attacks and the MFO algorithm is used for feature selection purposes to attain improved results. The detection of DoS attacks takes place using extreme gradient boosting (XGBoost) classifier. Finally, the DoSD-MFOML technique employs grey wolf optimizer (GWO) algorithm for the parameter tuning procedure. The performance validation of the DoSD-MFOML method is tested on benchmark dataset and the outcomes are studied under several measures. The experimental outcome confirms the increased performances of the DoSD-MFOML technique for DoS attack detection purposes. © 2023 IEEE.

关键词： Machine learning

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Improved Secure Communication Based Adhoc Routing in Mobile Network Technology 2

Improved Secure Communication Based Adhoc Routing in Mobile ...

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2nd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Mishra, Saket Chitkara University Institute of Engineering and Technology Punjab India

ISBN: (纸本)9798350347456

Fifth-generation (5G) is the future of mobile network technology;the development of 5G mobile services is based on a comprehensive study of mobile services' global trends. 5G is, innovation and support of the implementation are to change over all the vertical industries and society's progress, is the next-generation mobile network. 5G mobile network providing new online products business opportunities within the enhanced performance, flexibility, and personalization worldwide. In the case of a 5G mobile network, optimization of the active system plays an important role in the severe service requirements in meeting the index traffic growth and reducing capital and operating costs. Optimization of the dynamic network is generally based on big data analysis and cloud computing. It has been considered one of the most promising ways to convert the 5G network;many traffic and packet loss problems exist. The proposed algorithm, Efficient Software Optimization Networking (ESON), is used to improve network throughput, reduce traffic and packet loss for an online product design economic growth. Data Authentication Encryption Standard (DAES) algorithm is used to secure communication, and Shortest Vector Routing (SVR) algorithm is used to find the shortest path for avoiding packet loss. The simulation result shows the high performance compared to other existing methods. © 2023 IEEE.

关键词： Authentication

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Block Chain and distributed computing Aided with cloud Technology- A Specific Reference to Security Issues of Healthcare Industry 2

Block Chain and Distributed Computing Aided with Cloud Techn...

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2nd IEEE international conference on Advances in computing, Communication and Applied Informatics, ACCAI 2023

作者： Murugamani, Chakravarthi Nadh Singh, Bhaludra R. Pravalika, Kallu Rethvikha Sri, P. Sowmya, Chennuru Sai Reddy, Mankhala Shreya Department of Information Technology Bhoj Reddy Engineering College for Women Telangana Hyderabad59 India Department of Computer Science and Engineering Bhoj Reddy Engineering College for Women Telangana Hyderabad59 India Bhoj Reddy Engineering College for Women Telangana Hyderabad59 India

ISBN: (纸本)9798350315905

There has been a significant uptick in the need for user-centric electronic records to save the many characteristics of a patient's medical history as they are recorded at a hospital during treatment and to make those records available as and when they are needed for future treatment, care, or invoicing. Blockchain technology allows us to save these data on a distributed ledger, allowing us to begin and enable use at breakneck speeds while still maintaining a transparent and secure system. To save records safely and in an interoperable fashion, a distributed system with ledger functionality is used. Block chain technology has the potential to revolutionize the way digital assets are transacted by removing the need for a trusted third party to authenticate data authenticity, record asset ownership, or mediate financial or data transactions. Immutability, decentralisation, and transparency are three of its defining characteristics, making it well suited to resolving pressing problems in the healthcare industry, such as the lack of comprehensive peer-to-peer files and the inability to easily access patients' medical histories. Health care systems that are efficient and successful depend on interoperability, the capacity of different health organisations and manufacturers of different software products to connect and share data in a safe and smooth manner. Many problems in modern healthcare can be traced back to a lack of interoperability, such as siloed data, sluggish communications, and different workflow tools. To address this, it is recommended to implement a system that provides secure, pseudo-anonymous access to complete, recognised longitudinal medical records stored in silos. In this article, we conducted a system overview and literature review of block chain technology in a fog computing environment, both of which are capable of processing vast amounts of data in a decentralised fashion. Our in-progress experimental study reveals weaknesses in existing systems

关键词： Interoperability

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A Nonlinear Interval Programming Model based on Fuzzy Neural Networks 2

A Nonlinear Interval Programming Model based on Fuzzy Neural...

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2nd international conference on distributed computing and Optimization Techniques, ICDCOT 2024

作者： Zhu, Jijin Wu, Qinqin Luo, Chan College of Mechanical and Electrical Engineering Guangdong University of Science and Technology Dongguan China Mathematics Teaching and Research Office Dongguan Guangming Primary School Dongguan China

ISBN: (纸本)9798350382952

Compared to traditional deterministic problem research methods, interval analysis methods have a larger computational load and longer computational time due to the presence of uncertainty. Therefore, for models with complex structures or large scales, there is a lot of uncertain information, which requires a significant amount of computation and reduces the efficiency of the algorithm. The current optimization algorithms also have such shortcomings. In order to improve algorithm efficiency, this article focuses on researching parallel computing methods for interval optimization, designing efficient parallel algorithms, decomposing optimization problems into multiple subtasks that can be parallelized, and analyzing the feasibility and effectiveness of these algorithms in detail. The results indicate that multiple artificial neural network models are used to establish mapping relationships between design variables and uncertain variables, corresponding objective function values, and constraint function values. The objective function and each constraint function are trained with one network each, and a heuristic algorithm is selected as the inner and outer layer optimization solver. © 2024 IEEE.

关键词： Fuzzy neural networks

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Data-Driven Retention Strategies: Exploring the Efficacy of Composite Deep Learning for Customer Churn Prediction in Telecommunications 2

Data-Driven Retention Strategies: Exploring the Efficacy of ...

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2nd international conference on distributed computing and Optimization Techniques, ICDCOT 2024

作者： Habelalmateen, Mohammed I. Bala Dhandayuthapani, V. Malathy, V. Pramodhini, R. Ramakrishna, D. The Islamic University Najaf Iraq College of Computing and Information Sciences University of Technology and Applied Sciences Shinas Branch Department of It Oman Sr University Department of Ece Warangal India Nitte Meenakshi Institute of Technology Dept of Ece Bengaluru India Electronics and Communication Engineering Department Telangana Hyderabad India

ISBN: (纸本)9798350382952

The customer churn, otherwise known as subscriber loss, inclusive among one of the key challenges of the telecommunication industry (TCI). Forecasting churn gives rise to telecoms step-saving retentional strategies, serving as the means preventing losing revenue. To this research applies of the innovative customer churn prediction (CCP) model employing data transformation approaches and feature selection schemes. The work entail analyzing six data transformation methods (Log, Rank, Box-Cox, Z-score, Discretization, and weight-of-evidence) and eight classifiers such that each data conversion technique is applied or tested on multiple types of classifiers such as K-Nearest Neighbors (KNN), Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF) The univariate way of feature selection is used to determine the features which have major effect and the proposal grid search is also adopted for hyperparameter optimisation. Experiments are conducted on four selected telecommunication industry (TCI) datasets. The evaluation of the model's performance involves using metrics such as accuracy and recall which are understood to be better than existing tools. © 2024 IEEE.

关键词： Telecommunication industry

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A Decentralized Vehicle-to-Vehicle Energy Trading System Based on Efficient Sharding Services 21

A Decentralized Vehicle-to-Vehicle Energy Trading System Bas...

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21st IEEE international Symposium on parallel and distributed Processing with Applications, 13th IEEE international conference on Big Data and cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDcloud/SocialCom/SustainCom 2023

作者： Meng, Kun Sun, Lijun Chen, Xiao Wu, Haiqin Li, Shuaiyong Qingdao University of Science and Technology College of Information Science and Technology Shandong China University of Leicester School of Computing and Mathematical Sciences Leicester United Kingdom Software Engineering Institute Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing China

ISBN: (纸本)9798350329223

Vehicle-to-vehicle (V2V) energy trading stands as a significant technology, allowing electric vehicles (EVs) to share energy. This balances energy demand and supply, reducing pressure on the power grid. However, two substantial challenges require attention: 1) Creating a standardized protocol universally adoptable by EV manufacturers and energy trading participants to establish a common secure and reliable platform for real-time energy trading between EVs. 2) Determining a fair and transparent pricing and transaction management mechanism, accounting for factors such as energy demand and supply, location, and user preferences. To tackle these hurdles, this paper proposes a decentralized V2V energy trading system (VETS) based on a novel high-performance sharding blockchain framework. VETS incorporates a standard energy trading management protocol, achieving trustless and transparent transaction processing. It employs a blockchain sharding and parallel architecture for high transaction throughput, catering to a large number of EVs. Furthermore, an efficient consensus algorithm is developed to minimize service delays and adapt to real-time transaction demands. A practical testbed operationalizes VETS, facilitating experimental analysis within a real-world cloud environment. © 2023 IEEE.

关键词： Blockchain

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Front end computer configuration design of power monitoring system based on cloud computing access control 2

Front end computer configuration design of power monitoring ...

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2nd international conference on Electronic Information engineering and Computer Technology, EIECT 2022

作者： Chen, Haiguang Zha, Jing Hu, Zhaohui Chen, Shanfeng Yang, Yiyue China Southern Power Grid Digital Grid Research Institute Co. Ltd. Guangzhou China

ISBN: (纸本)9798350399561

Aiming at the problem that the current power monitoring system front-end computer has poor access control capability, which leads to the long time-consuming of data sending and receiving, a front-end computer configuration method for power monitoring system based on cloud computing access control is designed. The BQ4011YMA-100 chip is selected as the core chip of the front-end computer, and the peripheral circuit and network interface of the chip are set. Build a cloud computing access control model, analyze the reliability of data receiving nodes according to the AHP, and control access security. Set the front-end data transceiver program to realize the front-end configuration data transceiver function of the power monitoring system. So far, the design of the front-end computer configuration method of the power monitoring system based on cloud computing access control is completed. Build a test link to analyze the front-end function after this configuration method is used. The test results show that this configuration method can shorten the data sending and receiving time to a certain extent and improve the performance of the system. © 2022 IEEE.

关键词： cloud computing

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IoT based Transformer Protection and Load Sharing Automation 2

IoT based Transformer Protection and Load Sharing Automation

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2nd international conference on Applied Artificial Intelligence and computing, ICAAIC 2023

作者： Ragavapriya, R.K. Sakthivel, S. Prasannaa, R.Sharan Sudhir, U. Sri Ramakrishna Engineering College Electrical & Electronics Engineering Coimbatore India

ISBN: (纸本)9781665456302

The transformer is a passive component, which steps-up or step-down voltage from the primary to secondary coil and then serves what a load needs. The main aim is to give protection to the transformer under overload conditions by sharing the load and can also monitor the performance of the transformer. When overloading appears, the efficiency lowers down and the winding gets overheated and can catch fire easily. Thus by sharing the load on transformer, the transformer is protected and this will be connecting to another transformer in parallel through an embedded controller. The controller compares the load and the first transformer with a value that can be taken as a reference. When the load goes above the reference value, the second transformer will assist the main transformer with extra load. Therefore, the two transformers work efficiently and damage is prevented, also monitoring the performance of transformers which helps in the protection of domestic supply and power transformers concerning load using the Internet of Things (IoT), a communication protocol to transmit and display the monitored results in an output device through cloud. The proposed model holds the advantages such as supply without disturbances, deviating the damages of short circuit, absence of overload and heat issues, etc. © 2023 IEEE.

关键词： Internet of things

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Monitoring of Photovoltaic Fed Induction Motor Control using IoT 2

Monitoring of Photovoltaic Fed Induction Motor Control using...

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2nd international conference on Edge computing and Applications, ICECAA 2023

作者： Nandhini, M. Arunsankar, G. Anbu Sujitha, S. Daisylin Venkatasubramanian, R. Sri Sai Ranganathan Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Coimbatore India Gojan School of Business and Technology Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Sri Sairam Institute of Technology Department of Chemistry Tamil Nadu Chennai India New Prince Shri Bhavani College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350347579

Renewable energy fed motor drives are becoming popular in recent years, and solar photovoltaic (PV) is chosen as the source because of its efficient economic benefits and clean nature. Since the majority of the electricity supplied at the utility grid is an alternating current (AC) supply. As a result, induction motors (IMs) are employed in both industrial and household equipment. Experts are therefore attracted to the IM's speed control problems. Among many IM control schemes, v/f control is implemented in this paper using the space vector pulse width modulation (SVPWM) technique and the motor parameters are monitored by the internet of things (IoT). Owing to the use of non-sinusoidal voltages, voltage source inverter (VSI) fed IMs generate pulsing torque. The output voltage of the SVPWM technique is closer to sinusoidal and it performs better spectrally. The IM control design is implemented in MATLAB/ Simulink. The IoT platform is included in this system for analyzing and collecting the IM parameters. The gathered data may be kept on a cloud platform and accessed via a web page. The benefits of the system are failure alerts and historical data for preventative maintenance. © 2023 IEEE.

关键词： Induction motors

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Low Latency Consistency based Protocol for Fog computing Systems using CoAP with Machine Learning 2

Low Latency Consistency based Protocol for Fog Computing Sys...

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2nd international conference for Innovation in Technology, INOCON 2023

作者： Jha, Surbhi Tripathy, Divya Noida Institute of Engineering and Technology Department of CSE Uttar Pradesh Greater Noida India Galgotias University Department of Bio-Sciences Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350320923

In a distributed system, fog computing (FC) is an emerging computer technique. The goal of FC is to position cloud-based services in close proximity to endpoints. The method is meant to meet the minimal latency requirement for Iot - based healthcare equipment. There is a wide range of healthcare data volumes produced by Iot - based healthcare equipment. Network congestion and increased delay are the direct effects of this massive influx of data. Patient information is rendered useless and insufficient for end-users when round-trip time delays rise due to huge data transfer and increasing hop counts between IoTs and cloud servers. In the healthcare industry, real-time data is essential for time-sensitive applications. The medical IoT devices and their users have stringent requirements for latency, and traditional cloud servers just can't provide them. Therefore, it is important to decrease network delay, compute latency, and communications latency while transmitting data through the Internet of Things. FC allows data to be stored, processed, and analyzed in the cloud and at the network's edge, where the latency is lower. This article proposes an innovative approach to solving the aforementioned issue. It combines an FC-based analytical model with a hybrid fuzzy-based RL algorithm. High latency in healthcare IoTs, between users and cloud servers, is something that has to be mitigated. Allocation and selection of data packets in an IoT-FC setting are handled with the help of a fuzzy inference system, reinforcement learning, and neural network evolution techniques provided by the suggested smart FC model parameters and algorithms. The method is put through its paces on the iFogSim (Net-Beans) as well as Spyder simulations (Python). The acquired findings demonstrated that the suggested strategy outperformed the state-of-the-art techniques. © 2023 IEEE.

关键词： Fog computing

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