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Integration of Fuzzy Model with the IOT Model to Achieve Better Health(Medical) Care Design System 4

Integration of Fuzzy Model with the IOT Model to Achieve Bet...

引用

4th ieee international conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Raman, Ramakrishnan Kumar, Vikram Pillai, Biju G. Verma, Apurv Rastogi, Shailesh Meenakshi, R. India Srv Media Pvt. Limited India Sri Balaji University Faculty of Management It & Business Analytics Pune India Parul Institute of Technology Parul University Computer Science and Engineering Faculty of Engineering and Technology India India Computer Science and Engineering Chennai Institute of Technology India

ISBN: (纸本)9798350360165

the Internet of things is a pervasive network that utilizes sensor-equipped devices by the billions to observe the real-world environment. the Internet of things technology presents considerable potential for the development of various industries, including medical treatment, where it can decrease the impact that the combination of old age and chronic ailments puts on health care systems. this paper tends to put forward a secure hierarchical routing approach, so-called Fuzzy Logic-based secure Hierarchical Routing using the Firefly Algorithm, to mitigate the issued challenges in IoT technologies for healthcare. A Fuzzy Trust Framework, an Inter-cluster Routing Framework, and a Firefly Algorithm-based Clustered Framework are the three main components of the proposed FSRF. the Fuzzy Security Framework identifies the trustworthiness of IoT devices in the network to resist routing attacks. the Firefly Algorithm-based Colony Framework selects IoT devices as cluster head nodes using the fitness function that measures the trust level, residual power hop count, connectivity radius, and centrality. FSRF goes further to apply an on-demand routing technique to ensure efficient data transmission. Simulation analysis compared with the current protocol was presented that showed that FSRF significantly improves the network lifetime, and energy efficiency, but security is the issue that needs further concern to improve the system. © 2024 ieee.

关键词： sensor nodes

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Investigating the Impact of Barrier Adjustment and Priority Caching on Improving Quality of Service in Named Data Vehicular sensor Networks 4

Investigating the Impact of Barrier Adjustment and Priority ...

引用

4th international conference on computing and Communication systems, I3CS 2023

作者： Dhakal, Dependra Dey, Sudipta Dey, Prantik Rathor, Mohit Sharma, Kalpana Sikkim Manipal Institute of Technology CSE Department Majhitar India

ISBN: (纸本)9798350323771

Named Data Networking (NDN) is an exciting and potential Internet infrastructure focused on content. Furthermore, it should also accommodate various forms of traffic and their Quality of Service (QoS) specifications to make NDN's utility more widespread. In recent years, Vehicular sensor Network (VSN) have developed rapidly for sharing information, especially in safe and efficient driving. the Named Data Network does well in information retrieval with its in-network caching and named-based routing. Because of the transition from end-to-end communication to named-based communication, the replacement of cache to achieve QoS in Named Data Vehicular sensor Network (NDVSN) is critical. In this paper, we consider an NDVSN network and investigate priority caching algorithm (PBDCV) for improving QoS that relies on the priority of data based on safety and non-safety applications and dynamic cache with barrier adjustment partition. the study has been evaluated through simulations and found to outperform some traditional caching strategies in terms of cache hit and Quality of Service. © 2023 ieee.

关键词： Quality of service

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Design of Automatic Allocation System for Power Supply Service Terminals Based distributed Decision Mechanism and threshold Decision 4

Design of Automatic Allocation System for Power Supply Servi...

引用

4th ieee international conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Chen, Yuwei Zhou, Jing Chen, Zongwei Fu, Xiaofei State Grid Fuzhou Electric Power Supply Company Fuzhou China

ISBN: (纸本)9798350352931

Nowadays, automatic systems for power supply terminals have huge demand in power distribution networks. To optimize and streamline the process of allocation of power supply points, these systems were designed for the power supply. the challenges in automatic systems for power supply terminals include with the service terminal allocation such as manual intervention causes human error, time-consuming, and incapable of real-time response in emergencies. To overcome these challenges proposed distributed Decision Mechanism (DDM) and threshold Decision (TD) method for power supply allocation. Initially, the input data is collected from the power demand dataset whereas the dataset consists of electrical consumption and weather data. then the preprocessing is done by the vertical partitioning and pairing in power supply allocation by dividing it into subsets based on attributes and similarities. the power supply allocation is done through the DDM-TD which allows multiple agents to make power supply allocation decisions independently. From the results the proposed DDM-TD shows better performance in terms of Accuracy of (77.86%) and MAPE of (65.67 %) when compared to previous existing method of method Bidirectional Long Short-Term Memory Neural Network (Bi-LSTM) respectively. © 2024 ieee.

关键词： Multi agent systems

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Design of Market Trading Mechanisms for distributed Resources Based on Credit Evaluation 4

Design of Market Trading Mechanisms for Distributed Resource...

引用

4th international conference on Energy Engineering and Power systems, EEPS 2024

作者： Cheng, Shuaihao Li, Yang Liu, Xiaodan Xiang, Sheng Meng, Ke Zheng, Yu Changsha University of Science and Technology Ministry of Education International Cooperation Joint Laboratory of Energy Internet Operation and Planning Based on Distributed Optical Storage Hunan Changsha China State Grid Hunan Electric Power Company Energy Internet Supply and Demand Operation Hunan Provincial Key Laboratory Hunan Changsha China

ISBN: (纸本)9798350366914

With the rapid expansion of distributed resources, the trading market for distributed resources is imperative. therefore, this paper proposes trading mechanisms for distributed resources based on credit evaluation to promote the full entry of distributed resources into the market. At first, a credit evaluation method for distributed resources is constructed, including the evaluation principles, indexes, and evaluation method, which is used to quantify the credit level of distributed resources that participate in the market, then, a P2P trading mechanism for distributed resources based on the credit evaluation is introduced. Finally, a case study is carried out. the results show that strictly according to the bid power output ratio is not completely according to the bid power output, the credit level is higher and the income is considerable. At the same time, the overall income and the user's trading enthusiasm are improved to achieve the purpose of maintaining market order. © 2024 ieee.

关键词： Marketplaces

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Trade off between Accuracy and Message Complexity for Approximate Data Aggregation 18

Trade off between Accuracy and Message Complexity for Approx...

引用

18th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Nugroho, Saptadi Weinmann, Alexander Schindelhauer, Christian Albert Ludwigs Univ Freiburg Freiburg Germany

ISBN: (纸本)9781665495127

We consider large scale Peer-to-Peer sensor Networks, which try to calculate and distribute the mean value of all sensor inputs. For this we design, simulate and evaluate distributed approximation algorithms which reduce the number of messages. the main difference of these algorithms is the underlying communication protocol which all use the random call model, where in discrete round model each node can call a random sensor node with uniform probability. the amount of data exchanged between sensor nodes and used in the calculation process affects the accuracy of the aggregation results leading to a trade-off situation. the key idea of our algorithms is to limit the sample size using the Finite Population Correction (FPC) method and collect the data using a distribution aggregation using Push-Pull Sampling, Pull Sampling, and Push Sampling communication protocols. It turns out that all methods show exponential improvement of Mean Squared Error (MSE) with the number of messages and rounds.

关键词： data aggregation sensor network message complexity approximation random call model

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Efficient Humidity sensor Based on An Etched No-core Fiber Coated with SiO2- nanoparticles 4

Efficient Humidity Sensor Based on An Etched No-core Fiber C...

引用

4th international conference on Advances in Electrical, computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Ahmad, Nadia Ali, Adnan Hussein Al-Askery, Ali Middle Technical University Electrical Engineering Technical College Baghdad Iraq Middle Technical University Department of Institute of Technology Baghdad Iraq

ISBN: (纸本)9798350343670

this work presents the simple architecture of a relative humidity detection probe based on a Mach-Zehnder interferometer (MZI). the interferometer structure is made of non-core multimode fibre (NCF) sandwiched between two pieces of single-mode fibre to create the SMF sensor structure. A chemical etching process using hydrofluoric acid (HF) reduces the diameter of the NCF to 64.2 μm. then, the etched NCF was coated with a thin layer of polyvinylpyrrolidone (PVP)/silica (SiO2). Results show that the PVP/SiO2 NLs coating is a moisture coating material, which allows a significant improvement in sensitivity compared with an uncoated probe due to the improvement in the evanescent field. Experimental results indicate an excellent sensitivity of - 0.2718 dB/% RH at R2 of about 94% and an ultra-fast response time of 2 s for the PVP/SiO2 NLs-coated sensor at RH ranging from 47% to 100%. the sensor also shows good stability © 2024 ieee.

关键词： etched no core fiber evanescent wave Fiber optic Mach-Zehnder interferometer MZI polyvinglpyrrolidone relative humidity sensor SiO2

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A Neural Network and Bloom Filter-Based Name Search Method in Named Data Networking 4

A Neural Network and Bloom Filter-Based Name Search Method i...

引用

4th international conference on Neural Networks, Information and Communication Engineering, NNICE 2024

作者： Liu, Yue Li, Xiaoyong Si, Xiaotian Zhang, Mengyang Yuan, Kaiguo Li, Pengcheng Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Beijing China

ISBN: (纸本)9798350394375

In a new network architecture like NDN, designing an efficient name lookup method has always been a valuable challenge. the paper studies the name lookup technology based on the Bloom filter and BPNN neural network mapping model in named data networking. In the part of the hybrid model based on the Bloom filter and BPNN, the paper proposes the fusion idea of the Bloom filter and BPNN, and provides a detailed introduction to the construction process of the hybrid model. At the same time, in order to improve the memory utilization of traditional Bloom filters, this article proposes a way to use neural networks to enhance it, and proved its effectiveness through experiments. © 2024 ieee.

关键词： Network architecture

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DL-Based Secure Wearable Scheme for Remote Patient Data Monitoring in Healthcare 4.0 4

DL-Based Secure Wearable Scheme for Remote Patient Data Moni...

引用

4th ieee international conference on computing, Communication, and Intelligent systems, ICCCIS 2023

作者： Ramoliya, Fenil Darji, Krisha Gupta, Rajesh Kakkar, Riya Tanwar, Sudeep Kumari, Aparna Inst. of Technology Nirma University Dept. of Computer Sci. and Engg. Ahmedabad382481 India

ISBN: (纸本)9798350306118

the paper articulates an exploration into the integration of wearable devices for remote patient data monitoring, which marks a transformative shift in healthcare practices. this transition is underscored by user-centric interfaces and applications, enabling convenient remote monitoring. However, the escalating concern of patient data vulnerability to network breaches presents a substantial impediment. In response, we introduce the proposed scheme that harnesses Machine Learning (ML) and Deep Learning (DL) techniques. the main objective of the proposed scheme is to meet the exacting requirements of healthcare systems, aiming to fortify data integrity and confidentiality. Within this context, the proposed scheme unveils a sophisticated DL-driven detection model, adeptly tailored for discerning and countering data manipulation endeavors through a nuanced multi-label classification paradigm. Notably, the emphasis lies on safeguarding patient data privacy and security, which is paramount in today's information-rich landscape. the narrative seamlessly interweaves elements of wearable technology, sensor networks, advanced DL capabilities, and robust security measures, resulting in an innovative scheme. Finally, the proposed scheme is evaluated against various metrics such as accuracy and loss curve and F1, recall, and precision comparison. © 2023 ieee.

关键词： sensor networks

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Design of hierarchical adaptive control scheme for distributed resources based on cloud-edge collaboration 4

Design of hierarchical adaptive control scheme for distribut...

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4th international conference on New Energy and Power Engineering, ICNEPE 2024

作者： Ma, Biyan Li, Ping Wu, Lin Guangzhou City University of Technology Guangzhou510800 China

ISBN: (纸本)9798331516086

Large-scale distributed resources are connected to the distribution network, which puts forward new requirements for peak regulation and frequency regulation of the dispatching system. In order to improve the network construction capability of the new power system, this paper proposes a hierarchical adaptive control scheme for distributed resources with cloud-edge collaboration, in which the gateway forms a panoramic data-based master station control command decomposition strategy based on the minute-level distribution network island information synchronized by the master station, and realizes the local AGC and AVC functions, dynamically corrects the power frequency static characteristic coefficient of the power system according to the distribution network control effect, and continuously optimizes the control performance. through the real-time collection of data from the photovoltaic power station, the gateway advanced application function model is constructed, and the master station dispatching command is simulated to verify the correctness of the gateway's response, and the priority-based cloud-edge collaborative scheduling control strategy is verified. © 2024 ieee.

关键词： Adaptive control systems

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Quantum Long Sort-Term Memory-based Identification of distributed Denial of Service Attacks 4

Quantum Long Sort-Term Memory-based Identification of Distri...

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4th ieee international conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Tripathi, Sarvapriya Upadhyay, Himanshu Soni, Jayesh Florida International University Electrical and Computer Engineering Miami United States

ISBN: (纸本)9798331518882

distributed Denial of Service (DDoS) is defined as an attack targeting a server, where the server is overwhelmed by an overflow of traffic, leading to a computer system being compromised. To prevent these attacks from happening, thus allowing the computer systems to maintain their normal behavior, a long short-term memory (LSTM) Time-Series model can recognize sequential characteristics in the data in order to predict whether a DDoS attack is occurring. Our approach leverages various aspects of network traffic such as Flow ID, Source IP, Destination IP, and Destination Port, and analyzes the accuracy and reliability using LSTMs to improve DDoS attack prediction accuracy. In this study we analyzed the relative efficiency of Quantum LSTM (QLSTM) over that of Classical LSTM, and found that both Quantum and Classical LSTM models train quickly and within a few epochs the accuracy increases to 0.99 and above. the validation of the models proved that QLSTM achieved better Recall, Accuracy, Precision, and F1 scores as compared to classical LSTM, making it an ideal candidate for DDoS attack predictions. this study proves the potential of applying deep learning techniques to strengthen network security, which has become increasingly important with the rise of complex cybersecurity threats. © 2025 ieee.

关键词： Denial-of-service attack

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