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检索条件"任意字段=Intelligent Computing and Networking - Proceedings of IC-ICN 2023"

共 18 条记录，以下是11-20 订阅

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Cost-Efficient SFC provisioning in Container Environment

Cost-Efficient SFC provisioning in Container Environment

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2023 International Conference on intelligent computing and Control, ic and C 2023

作者： Ganesan, Nithya Nachiappan, S.K. Kamboj, Prateek Thangaraju, B. IIIT Bangalore Bengaluru India

ISBN: (纸本)9781665457095

As an alternative to virtualisation, containerisation has emerged as a significant trend in software development. Their introduction provides for the reduction of costs, time, and energy. A service function chain (SFC) in a container is a collection of sequentially ordered container network functions (CNFs). To efficiently implement CNFs in a network, the SFC placement problem must be solved. SFC placement is primarily concerned with placing the CNFs of an SFC into the appropriate container and chaining them together in accordance with specific SFC requirements. In order to make good use of available network resources and ensure network service performance, network operators must strategise the placement of SFC. Our paper aims to optimise End-To-End delay, minimise operational costs, and increase the acceptance rate when placing SFCs in containers. These requirements must be met by network operators in order to optimise resource consumption and provide better service to end users. Thus, we have formalised the SFC chaining and placement problem in a mathematical model and minimised the operational cost using the proposed Mixed Integer Linear Programming (MILP) model. This paper shows that with the use of CNF, we can further optimise the SFC placement and reduce the operational cost, which, when evaluated, came out to be around 12% less than SFC placement using VNF. © 2023 IEEE.

关键词： Software defined networking

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Generative Artificial Intelligence: Opportunities and Challenges of Large Language Models

Generative Artificial Intelligence: Opportunities and Challe...

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intelligent computing and networking - proceedings of ic-icn 2023

作者： Barreto, Fabian Moharkar, Lalita Shirodkar, Madhura Sarode, Vidya Gonsalves, Saniya Johns, Aaron Department of Electronics and Telecommunication Xavier Institute of Engineering Mumbai India Department of Applied Sciences and Humanities Xavier Institute of Engineering Mumbai India Department of Information Technology St. Xavier’s College Mumbai India

ISBN: (纸本)9789819931767

Artificial Intelligence (AI) research in the past decade has led to the development of Generative AI, where AI systems create new information from almost nothing after learning from trained models. Generative AI can create original work, like an article, a code, a painting, a poem, or a song. Google Brain initially used Large Language Models (LLM) for context-aware text translation, and Google went on to develop Bidirectional Encoder Representations from Transformers (BERT) and Language Model for Dialogue Applications (LaMDA). Facebook created OPT-175B and BlenderBot, while OpenAI innovated GPT-3 for text, DALL-E2 for images, and Whisper for speech. GPT-3 was trained on around 45 terabytes of text data at an estimated cost of several million dollars. Generative models have also been developed from online communities like Midjourney and open-source ones like HuggingFace. On November 30, 2022, OpenAI launched ChatGPT, which used natural language processing (NLP) techniques and was trained on LLM. There was excitement and caution as OpenAI’s ChatGPT reached one million users in just five days, and in January 2023 reached 100 million users. Many marveled at its eloquence and the limited supervision with which it generated code and answered questions. More deployments followed;Microsoft’s OpenAI-powered Bing on February 7, 2023, followed by Google’s Bard on February 8, 2023. We describe the working of LLM and their opportunities and challenges for our modern world. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Social networking (online)

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An intelligent Voice Assistant Engineered to Assist the Visually Impaired 1

引用

International Conference on intelligent computing and networking, ic-icn 2022

作者： Chopda, Rishabh Khan, Aayan Goenka, Anuj Dhere, Dakshal Gupta, Shiwani Thakur College of Engineering & Technology Maharashtra Mumbai400101 India

ISBN: (数字)9789819900718

ISBN: (纸本)9789819900701

Visually handicapped people’s lives are subject to a multitude of unrelenting challenges because they’ve been made bereft of the gift of sight. The proposed solution is a wearable Smart Voice Assistant that is developed to accommodate the needs of the visually impaired to aid them in every aspect of their everyday lives. It takes advantage of recent breakthroughs in the fields of language processing and computer vision to provide a broad spectrum of applications, including emergency response functionality, object recognition, and optical character recognition. It comprises hardware components that provide feedback in the form of sound, haptics, and speech to help with obstacle avoidance. The voice assistant also interacts with a smartphone application to enhance the user’s experience by enabling them to read the messages from their phone, send an SOS message to their closest connections in an emergency, customize the device settings through the mobile application, and find the device with the press of a button if it is misplaced. The proposed solution will enable the user to live a life in relative safety and comfort, which is essential for people suffering from varying levels of visual impairment. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Object recognition

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Support Vector Machine for Multiclass Classification of Redundant Instances

Support Vector Machine for Multiclass Classification of Redu...

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intelligent computing and networking - proceedings of ic-icn 2023

作者： Surbakti, Herison Kumar, Athmakuri Naveen Tara, Saikumar Keshta, Ismail khare, Amit Prasad, G.N.R. Faculty of Computing and Digital Technology HELP University Kuala Lumpur Malaysia Senior Software Engineer Glosoft Technologies Pvt Ltd Chennai India Department of ECE BVRIT Hyderabad College of Engineering for Women Hyderabad India Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Department of Technology JIET Institute of Design and Technology Rajasthan Jodhpur India Telangana Hyderabad500091 India

ISBN: (纸本)9789819931767

In recent years, support vector machine has become one of the most important classification techniques in pattern recognition, machine learning, and data mining due to its superior classification effect and solid theoretical base. However, its training time will increase dramatically as the number of samples increases, and training will become more sophisticated when dealing with problems involving multiple classifications. A quick training data reduction approach MOIS appropriate for multi-classification tasks is presented as a solution for the aforementioned issues. While eliminating redundant training samples, the boundary samples that play a vital role are chosen in order to considerably reduce training data and the problem of unequal distribution between categories. The experimental results demonstrate that MOIS may maintain or even improve the classification performance of support vector machines while substantially enhancing training efficiency. On the Opt digit dataset, the suggested method improves classification accuracy from 98.94% to 99.05%, while training time is reduced to 15% of the original;in HCL2000, the proposed method improves classification accuracy from 98.94% to 99.05%. When the accuracy rate is marginally increased (from 99.29% to 99.30%) on the first 100 categories dataset, the training time is dramatically reduced to less than 6% of the original. Additionally, MOIS has a high operational efficiency. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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Energy Efficient Lightweight Scheme to Identify Selective Forwarding Attack on Wireless Sensor Networks

Energy Efficient Lightweight Scheme to Identify Selective Fo...

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intelligent computing and networking - proceedings of ic-icn 2023

作者： Jawarneh, Malik Jayakrishna, M. Davuluri, Sandeep Kumar Ramanan, S.V. Singh, Pavitar Parkash Joseph, J. Armstrong Faculty of Computing Sciences Gulf College Muscat Oman Mechanical Engineering Sri Sivani Engineering College Srikakulam India Department of Information Technology University of the Cumberlands WilliamsburgKY40769 United States Department of Electronics and Communication Engineering PPG Institute of Technology Coimbatore641035 India Department of Management Lovely Professional University Phagwara India Chittoor517127 India

ISBN: (纸本)9789819931767

To protect wireless sensor networks from selective forwarding attacks, a lightweight WSN selective forwarding attack detection technique (LSFAD) is presented. The proposed approach identifies selective forwarding attack paths based on the average packet loss rate (PLR). It compares the PLR of attacked path with its normal PLR, and it can detect and pinpoint malicious links by doing the same for each node. The LSFAD technique detects malicious pathways during regular data packet sending and receiving without disrupting the normal operation of the entire network. Its simple design eliminates the need for listening nodes and sophisticated evaluation models. According to the results of the security and performance investigation, the LSFAD scheme is secure against passive and active selective forwarding attacks launched by malicious nodes. The LSFAD method has a significantly lower communication overhead compared to similar schemes. Despite an average PLR of 0.125 on the link, the LSFAD method detected the selective forwarding attack path in experimental simulations. Identifying the malicious nodes that launch a selective forwarding attack is possible when the link's usual PLR is more than 0.025. It is effectively detected and localized, and the network's energy consumption for doing so is not significantly higher than under normal conditions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Energy utilization

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A Privacy-Preserving Timing Attacks Mitigation in Information-Centric Edge Networks 25

A Privacy-Preserving Timing Attacks Mitigation in Informatio...

引用

25th IEEE International Conferences on High Performance computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Liu, Ningchun Gao, Shuai Liang, Teng Hou, Xindi Yu, Lei Zhang, Hongke Research Institute of Intelligent Networks Zhejiang Lab Hangzhou311121 China School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Peng Cheng Laboratory Department of New Networks Shenzhen518066 China China Telecom Zhejiang CO. Ltd Intelligent Cloud Network Operation Center Hangzhou310009 China

ISBN: (纸本)9798350330014

In-network caching is one of the most important features of Information-Centric networking (icn), which reduces data-retrieval latency, especially at edge networks. However, in-network caching can lead to privacy leakage with timing attacks, i.e., an adversary retrieves cached data and identifies it based on the difference of round trip time (rtt) of cached and non-cached data retrieval. Existing mitigation mechanisms either abandon in-network caching or intentionally add latency to cached data retrieval but fails to prove their effectiveness. In this paper, we propose a timing attack mitigation mechanism based on differen-tial privacy exponential mechanism that strictly protects content privacy against timing attacks without significantly increasing the content retrieval delay. Theoretical analysis and evaluation results show that our mechanism protects content privacy effectively at a low cost. © 2023 IEEE.

关键词： Timing circuits

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1st International Conference on Emerging networking Architecture and Technologies, icENAT 2022

1st International Conference on Emerging Networking Architec...

引用

1st International Conference on Emerging networking Architecture and Technologies, icENAT 2022

ISBN: (纸本)9789811996962

The proceedings contain 50 papers. The special focus in this conference is on Emerging networking Architecture and Technologies. The topics include: CQCF: A Cyclic Queuing Cluster Forwarding Based Transmission Mechanism for Large-Scale Deterministic Network;a Task-Resource Joint Optimization Model in Distributed computing;cache Strategy for Information Center Satellite Networks Based on Node Importance;intelligent Online Traffic Optimization Based on Deep Reinforcement Learning for Information-Centric Networks;detection and Defense Schemes for Cache Pollution Attack in Content-Centric Network;SBR-based User Intent Extraction Mechanism for Intent-Based Network;SPOF-NDN: A POF-Based NDN Forwarding Scheme;customizable Service Identification Method and System Design for Smart Integration Identifier Network;a Dynamic Live Streaming Service Architecture Integrated Sensing and Control;Detection of SDN Flow Rule Conflicts Based on Knowledge Graph;Risk-Aware SFC Placement Method in Edge Cloud Environment;preface;An In-Network computing Service Placement Mechanism for NUMA-based Software Router;network Traffic Identification Method Based on Temporal and Multi-scale Spatial Fusion;a Trustworthy Content Moderation Scheme Based on Permissioned Blockchain;multi-agent Deep Reinforcement Learning-Based Content Caching in Cache-Enabled Networks;mutual Authentication Protocol in a Distributed Heterogeneous Environment: A Blockchain-Based Approach;performance Evaluation of Transmission Protocols Based on Satellite Networks;optimizing Communication Topology for Collaborative Learning Across Datacenters;design of Reliable Parallel Transmission System in Complex Heterogeneous Network;design of Privacy-Preserving in Multi-link Vehicle-Ground Communication;smart Mobile Router Wireless Heterogeneous Network Access Mechanism;A Comparative Study on Routing Convergence of IP-Based and icn-Based Routing Protocols in Satellite Networks;implementation and Deployment of Digital Twin in Cloud-Nativ

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proceedings of the Second International Conference on computing, Communication, Security and intelligent Systems 1

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丛书名： Algorithms for intelligent Systems

1000年

作者： Shahid Mumtaz Danda B. Rawat Varun G. Menon

ISBN: (数字)9789819983988

ISBN: (纸本)9789819985753;9789819983971

This book presents the best-selected research papers presented at the Second International Conference on computing, Communication, Security & intelligent Systems (ic3SIS 2023), organized by SCMS School of Engineering and Technology, Kochi, on July 06–07, 2023. It discusses the latest technologies in communication and intelligent systems, covering various areas of computing, such as advanced computing, communication and networking, intelligent systems and analytics, 5G and IoT, soft computing, and cybersecurity in general. Featuring work by leading researchers and technocrats, the book serves as a valuable reference resource for young researchers, academics, and industry practitioners.

关键词： Computational Intelligence Communications Engineering, Networks Artificial Intelligence

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