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international conference on 6G Communications networking and Signal Processing, SGCNSP 2023

International Conference on 6G Communications Networking and...

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international conference on 6G Communications networking and Signal Processing, SGCNSP 2023

ISBN: (纸本)9789819778751

The proceedings contain 34 papers. The special focus in this conference is on 6G Communications networking and Signal Processing. The topics include: Secure Clustering and Routing Based on Modified Whale Optimization Algorithm in MANET;improved Whale Optimization Algorithm Based Energy Efficient Secure Routing in Mobile Wireless Sensor Networks;resource Allocation in Cloud computing Using Quasi-Opposition Learning Based Aquila Optimizer;the Quasi-Oppositional-Based Learning Aquila Optimization Routing Protocol in Energy-Aware Wireless Communication;exponential-Weighted Ant Lion Optimization Based Clustering Algorithm for Wireless Body Sensor Networks;Optimized Routing Strategy in Mobile Sink Based WSN Using Multi-objective Osprey Optimization Algorithm;the Coverage Optimization in Wireless Sensor Networks Using Improved Artificial Rabbit Optimization;improved Moth Flame Optimization Based Cluster Head Selection and Data Aggregation Using Machine Learning Approach;Multi-objective Deep Reinforcement Learning Approach for Multiple -Input/Multiple-output Routing in WSN;an Effective Energy Consumption and Weighted Clustering Using Improved K-Means Clustering;adaptive Weight Based Harris Hawks Optimization for Energy-Efficient Cluster Head Selection and Routing in Wireless Sensor Networks;An Optimal Cluster Head and Secure Route Path Selection Using Multi Objective—GWO Approach in Wireless Sensor Networks;peak-to-Average Power Ratio Reduction in Orthogonal Frequency Division Multiplexing Using Improved Butterfly Optimization Algorithm;energy Efficient-Based Cluster Head Selection and Routing Protocol for Wireless Sensor Networks Using Aquila Optimizer;ensemble Artificial Neural Network and Support Vector Machine Based Parameter Evaluation in Wireless Sensor Networks;distributed Denial of Service Attack Detection in IoT Utilizing Attention Mechanism Based Long Short-Term Memory;e-commerce Payment System Empowered by Blockchain for Enhanced Security.

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The 6G computing Continuum (6GCC): Meeting the 6G computing challenges 1

The 6G Computing Continuum (6GCC): Meeting the 6G computing ...

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1st international conference on 6G networking (6GNet)

作者： Tarneberg, William Fitzgerald, Emma Bhuyan, Monowar Townend, Paul Arzen, Karl-Erik Ostberg, Per-Olov Elmroth, Erik Eker, Johan Tufvesson, Fredrik Kihl, Maria Lund Univ Dept Elect & Informat Technol Lund Sweden Lund Univ Dept Automat Control Lund Sweden Umea Univ Dept Comp Sci Umea Sweden

ISBN: (纸本)9781665467636

6G systems, such as Large Intelligent Surfaces, will require distributed, complex, and coordinated decisions throughout a very heterogeneous and cell free infrastructure. This will require a fundamentally redesigned software infrastructure accompanied by massively distributed and heterogeneous computing resources, vastly different from current wireless networks. To address these challenges, in this paper, we propose and motivate the concept of a 6G computing Continuum (6GCC) and two research testbeds, to advance the rate and quality of research. 6G computing Continuum is an end-to-end compute and software platform for realizing large intelligent surfaces and its tenant users and applications. One for addressing the challenges or orchestrating shared computational resources in the wireless domain, implemented on a Large Intelligent Surfaces testbed. Another simulation-based testbed is intended to address scalability and global-scale orchestration challenges.

关键词： 6G Large Intelligent Surfaces computing Continuum distributed Orchestration computing at Scale

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Detecting DDoS attacks in Software Define networking: A Machine Learning Based Approach

Detecting DDoS attacks in Software Define Networking: A Mach...

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2023 international conference on Next-Generation computing, IoT and Machine Learning, NCIM 2023

作者： Bala, Shimul Ahsan, Sk. Md. Masudul Khulna University of Engineering & Technology Department of CSE Khulna Bangladesh

ISBN: (纸本)9798350316001

Software-Defined networking (SDN) is a type of network strategy that enables the separation of a network's control plane and data plane, thereby allowing centralized management and control of network traffic. Although SDN has many remarkable advancements, it encounters several security concerns like DDoS attack. The distributed Denial-of-Service (DDoS) attack is a fast-growing threat that endangers the future of internet technology. In this paper, some machine learning classifiers namely support vector machine (SVM) using linear based kernel and radial basis function (RBF) based kernel, random forest (RF), decision tree (DT), logistic regression (LR), and k-nearest neighbors (KNN) are evaluated to identify and analyze DDoS assaults within an SDN environment. A comparative performance study according to the results from the experiments is described to determine the best suitable techniques for DDoS detection. The results show that some classifiers reached up to 100% accuracy and the performance is validated using ROC-AUC curve. By utilizing proper classifiers derived from machine learning and taking the benefits of SDN, the controller can be safeguarded against DDoS attacks. © 2023 IEEE.

关键词： Denial-of-service attack

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Extending TWJ for Triangles Detection in Large Graphs 4

Extending TWJ for Triangles Detection in Large Graphs

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4th international conference on Embedded and distributed Systems, EDiS 2024

作者： Balbouzi, Sarah Zekri, Lougmiri Mechach, Kheira Ahmed Ben Bella Oran1 University Department of computer science Oran Algeria

ISBN: (纸本)9798331519872

In light of social networks' expansion and the ever-increasing number of subscribers who daily sign up to them. Detecting and counting triangles of subscribers in these networks are the basis of community detection. This detection is expressed as the computation of intersections between neighbors' subscribers lists. However, it remains very cumbersome and time-consuming to perform intersection operations. The significant detection cost is due to the fact that, until now, the treatment of intersections has been approached naively. Indeed, each element in the sorted neighborhood list of two neighboring vertices (listel and list2) in the network is compared one by one until one of the lists is exhausted. Given large-scale context, this results in a very high complexity of |liste1| + |liste2|. In this paper, we introduce a new technique for triangle detection. This approach aims to optimize intersection computing through minimizing the number of comparisons skipping the neighbors of one list that have no chance appearing in the second one, and thus making the triangle detection in large-scale networks more efficient. © 2024 IEEE.

关键词： Social networking (online)

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OMN-IBUS Type of networking System for the Communication System in 6G 4

OMN-IBUS Type of Networking System for the Communication Sys...

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

作者： Devi, A. Sangeetha Bhatt, Deepanshu Bansal, Saloni Keerthika, A. Mohanraj, T. Santhosh, S. Tamil Nadu T.M.Palayam India Ies Institute of Technology and Management Ies University Department of Mechanical Engineering M.P Bhopal India Gla University Department of Computer Engineering and Applications Mathura India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering TN India TN India Einstein College of Engineering Department of Electronic and Communication Engineering Tamil nadu India

ISBN: (纸本)9798350360165

The scientific community and industry have been working together in recent years to shift computational resources off centralized cloud systems to decentralized computing, or 'edge' computing. This change is a result of the cloud system's inability to keep up with the growing demands of emerging relationships, which are marked by the spread of time-sensitive applications like sophisticated robotics, augmented reality/virtual the truth technologies, self-driving cars, and vital remote control of Internet of Things applications. Decentralized computing at the border is still in its infancy and lacks a full platform, despite the critical role that it will play in future distributed systems. This article presents OMNIBUS, a novel decentralized edge architecture. This approach uses moving vehicles as resources for processing and storage, enabling the continuous delivery of computational capability to end-devices across many locations. Scalability and flexibility are two characteristics that set OMNIBUS distinct from other edge computing solutions. The suggested method, which is based on mathematical models of prediction, determines computational capacity for particular locations by learning the direction and time of vehicle movements. It also presents a theoretical foundation for learning, improvement, and caching amid dynamic conditions caused by moving vehicles, specifically for sequential concurrent conversion. OMNIBUS's scalability allows for almost infinite growth, which might result in a significant increase in network speed. © 2024 IEEE.

关键词： Scalability

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Efficient Diabetes Detection using Hybrid Machine Learning Model

Efficient Diabetes Detection using Hybrid Machine Learning M...

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2024 international conference on distributed Systems, Computer Networks and Cybersecurity, ICDSCNC 2024

作者： Gowri, A.S. Jose, P. Karthik, S.M. Shaheema, S Berlin Karuppasway, K.M. Balamurugan, R. School of Computing Srm Institute of Science and Technology Department of Networking and Communications Kattankulathur India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Department for Applied Research Gandhigram India Stella Mary's College of Engineering Department of Artificial Intelligence and Data Science Azhikal India Bharath Institute of Higher Education and Research Department of Mathematics and Statistics Chennai India Dmi College of Engineering Department of Information Technology Chennai India

ISBN: (纸本)9798350375442

Diabetes is a metabolic disease that affects a large number of the global population and is incurable. The primary causes of death symptoms are kidney failure, heart attacks, strokes, and blindness. In this paper Principal component analysis used for pre-processing the data to extract features and The Efficient Hybrid Machine Learning Model Convolution Neural Network-Support Vector Machine is used to categorize the Pima Indian dataset. CNN and non-linear SVM used in a hybrid model to classify the diabetes data from the Pima Indians. To identify positive classes of pima Indians diabetes, the HCNN-SVM extract the features from the original data expression and learns diabetes data through a novel convolution network environment to the SVM classifier with RBF function and achieve the accuracy as 98,04%. © 2024 IEEE.

关键词： Adversarial machine learning

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SP-ADMM: a distributed optimization method of SFC placement for 5G-MEC networks 3

SP-ADMM: a distributed optimization method of SFC placement ...

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3rd international conference on Algorithms, Microchips, and Network Applications, AMNA 2024

作者： Zhang, Zhibo Wang, Huiqiang Niu, Shuangyue Lv, Hongwu College of Computer Science and Technology Harbin Engineering University Harbin China AVIC Chengdu Aircraft Design and Research Institute Chengdu China

ISBN: (纸本)9781510680098

Recently, the combination of a service function chain (SFC) with network function virtualization (NFV) and software-defined networking (SDN) has provided customers with flexible and efficient services. The emergence of multi-access edge computing (MEC) further enhances the level of service customization. However, achieving joint optimization of virtual network function (VNF) deployment and flow allocation in resource-constrained scenarios while meeting the diverse requirements of 5G verticals is challenging. Current research rarely addresses dedicated service provisioning for edge servers and considers the additional instantiation overhead introduced by adjusting cloud server parameters. In fact, this is a non-negligible issue during SFC deployment in 5G-MEC scenarios. Based on the above considerations, this paper constructs a joint SFC deployment problem for edge-cloud networks with the goal of maximizing network utility. We first propose a univariate modeling method based on meta-links that effectively avoids the variable coupling problem in traditional multivariate modeling approaches and reduce the problem size by at least half. Subsequently, to solve the NP-hard integer nonlinear problem (INLP), we propose a distributed computing architecture named SP-ADMM, which improves the speed and quality of SFC deployment in large-scale scenarios via convex combinatorial formulations and a Viterbi-based heuristic algorithm (PAC-GREP). Finally, we experimentally verify the convergence and approximation of the algorithms. Our solution demonstrates advantages in terms of network utility and convergence speed under the same network resources, increasing service capacity by at least 39%. © 2024 SPIE.

关键词： Network function virtualization

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Symbiotic Content Caching in Next-Generation Information-Centric networking 19

Symbiotic Content Caching in Next-Generation Information-Cen...

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19th Annual international conference on distributed computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

作者： Rahman, Aisha B. Charatsaris, Panagiotis Siraj, Md Sadman Tsiropoulou, Eirini Eleni University of New Mexico Dept. of Electrical and Computer Engineering AlbuquerqueNM United States School of Electrical and Computer Engineering National Technical University of Athens Athens Greece

ISBN: (纸本)9798350346497

The continuous growth of mobile data traffic with strict time requirements calls for the development of sustainable edge content caching solutions. This becomes more prominent in the setting of Information-Centric networking (ICN) architectures, where different ICNs are leasing caching slices to the available content providers (CPs), who in turn offer their services to the users. In this paper, we introduce a novel symbiotic content caching framework that provides the necessary economic benefits to the ICNs and the CPs to mutualistically collaborate among each other. The corresponding mutualistic interactions among the ICNs and CPs are studied under the prism of two different market-based models, namely the competitive market and oligopoly market models. A game-theoretic approach is followed in order to determine the optimal leasing prices of the ICNs' content caching slices and the CPs' optimal amount of leased caching memory from the ICNs. The performance evaluation of the proposed new symbiotic content caching paradigm is achieved via modeling and simulation, while the benefits and drawbacks of the competitive and oligopoly market modeling approaches are revealed and discussed. © 2023 IEEE.

关键词： Game theory

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Efficient Data Transmission using PSO Algorithm in Wireless Sensor Networks 15

Efficient Data Transmission using PSO Algorithm in Wireless ...

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15th international conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Kalaiselvi, K. Thilak, K.Deepa Devi, K.Lalitha Kumaresan, K. Malathi, M. Faculty of Engineering and technology Department of Networking and communications SRM Institute of science and technology Kattankulathur Tamilnadu Chennai India Department of Computer science and Engineering Sathyabama Institute of Science and Technology India Department of CSE KSR College of Engineering Tiruchengode Tamilnadu Namakkal India Tamilnadu Namakkal India

ISBN: (纸本)9798331300579

A Wireless Sensor Network is made up of a large number of small, low-power sensor nodes that are randomly or manually distributed across an uncontrolled target ***, the WSNs' main constraint is the sensor nodes' restricted power *** a result, energy saving at sensor nodes is the most difficult barrier for WSNs' long-term *** and low-energy routing are two well-known optimization tasks that have received a lot of attention in the quest to extend the life of wireless sensor networks (WSNs).In a periodic data gathering application, the Particle Swarm Optimization (PSO) technique is employed to overcome this *** monitor the environment on a regular basis and send data to the base station (BS), which analyses the data and draws conclusions about the field activities.A cluster is used to send the data to the base station.A cluster head receives data from sensor nodes and transmits it to the cluster head, which combines the information and sends it to the base *** packet delivery ratios and throughput have both been *** a result, total energy consumption is reduced. © Grenze Scientific Society, 2024.

关键词： Particle swarm optimization (PSO)

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UAV Trajectory Optimization for PHY Secure Communication Against Cooperative Eavesdroppers 12

UAV Trajectory Optimization for PHY Secure Communication Aga...

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12th international conference on Cyber-Enabled distributed computing and Knowledge Discovery (CyberC)

作者： Zhang, Huanran Shen, Lingfeng Wang, Ning Mu, Xiaomin Zhengzhou Univ Sch Elect & Informat Engn Zhengzhou 450001 Peoples R China Henan Int Joint Lab Intelligent Networking & Data Zhengzhou 450001 Peoples R China

ISBN: (纸本)9798350331547

In this paper, we study the maximization of the secrecy throughput of an air-to-ground UAV communication system through UAV trajectory optimization, in a scenario where multiple cooperating eavesdroppers exist. Two cooperative eavesdropping strategies, namely Selection Combing-Cooperative Eavesdropping (SC-CE) and Maximal Ratio Combining-Cooperative Eavesdropping (MRC-CE) are considered for the cooperating eavesdroppers. Based on the mathematical forms of the formulated optimization problems corresponding to the two cooperative eavesdropping schemes, we propose to use the Trajectory Increment Iteration (TII) algorithm and the Particle Swarm Optimization (PSO) algorithm to solve for the optimal trajectory, respectively. Simulation results show that by optimizing the UAV trajectory against cooperative eavesdropping, the physical layer security performance of the system can be effectively improved.

关键词： UAV communication trajectory optimization collaborative eavesdroppers physical layer security

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