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A distributed ML Framework for Service Deployment in the 5G-based Automotive Vertical

A Distributed ML Framework for Service Deployment in the 5G-...

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IEEE international Mediterranean conference on Communications and networking (IEEE MeditCom)

作者： Sourlas, Vasilis Rizk, Amr Katsaros, Konstantinos V. Pantazopoulos, Panagiotis Drainakis, Georgios Amditis, Angelos NTUA Inst Commun & Comp Syst ICCS Athens Greece Univ Duisburg Essen Duisburg Germany

ISBN: (纸本)9781665445054

5G is the convergence technology for the new generation of mobile networks, expected to be massively deployed in the coming years. Building on network slicing and edge computing capabilities, 5G promises to address the diverse and quite demanding performance requirements of a wide range of use cases (UCs). As a result of these technological transformations, vertical industries will have enhanced technical capacity available to trigger the development of new products and services. Driven by these advances, Machine learning (ML) applications are headed towards collaborative distributed (CDL) schemes, to exploit the abundance of clients' data. Contrary to the traditional cloud-based centralized solutions (CML), in CDL schemes, computational load is shifted to the intelligent edge and extends further beyond, to the user-equipment (including connected vehicles). Here, we present a distributed ML (DML) framework, that will provide functionalities for simplified management and orchestration of collections of ML service components and will allow ML-based applications to penetrate the Automotive world.

关键词： Industries 5G mobile communication Network slicing distributed databases Machine learning Task analysis Monitoring

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Quality of Experience Aware Task Offloading in Digital Twinning Vehicular Edge computing

Quality of Experience Aware Task Offloading in Digital Twinn...

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international conference on distributed computing in Sensor Systems (DCOSS)

作者： Mostakim Jihad Mashraba Tasnim Rodshi Abdullah Al Fahad Palash Roy Md. Abdur Razzaque Mohammad Mehedi Hassan Department of Computer Science and Engineering Green University of Bangladesh Dhaka Bangladesh Department of Computer Science and Engineering Green Networking Research Group University of Dhaka Bangladesh Information Systems Dept. College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

Adopting Digital Twin (DT) technology in vehicular edge computing (VEC) enables efficient capture of real-time state information of applications, thereby addressing complex task scheduling problems. Existing literature studies considered only minimizing service latency for task offloading; however, there is room for exploring strategies to enhance user Quality of Experience (QoE) in timeliness and reliability domains. In this paper, we have developed an optimization framework using Mixed Integer Linear Programming (MILP), namely QuETOD, which minimizes service latency by allocating task execution responsibility to highly reliable and reputed vehicles in a DT-enabled VEC environment. The developed QuETOD framework clusters the vehicles based on the demand-supply theory of economics by considering computing resources and utilizing the multi-weighted subjective logic for getting the proper reputation update of the vehicles. The experimental results of the developed QuETOD system depict significant performance improvement in terms of QoE and reliability compared to the state-of-the-art works as high as 15% and 25%, respectively.

关键词： Processor scheduling Computational modeling Reliability theory Real-time systems Polynomials Quality of experience Servers

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distributed Self-Orchestration System based on Home 5G Concept

Distributed Self-Orchestration System based on Home 5G Conce...

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IEEE international conference on Cloud networking (CLOUDNET)

作者： Cheikh Saliou Mbacke Babou Yasunori Owada Masugi Inoue Kenichi Takizawa Toshiaki Kuri National Institute of Information and Communications Technology Tokyo Japan National Institute of Information and Communications Technology Sendai Miyagi Japan

Autonomous orchestration in distributed systems is a solution that attracts attention in 5G and beyond. Indeed, proposing a distributed orchestrator system with an Edge Cloud network can ensure autonomous management and service continuity, even when remote resources are not reachable. This feature is one of the key advantages of fifth-generation (5G and beyond) cellular networks, as stated by 3GPP (release 18), particularly regarding Proximity-based Service (ProSe), service management, and so on. Therefore, there is an urgent need to address the current gap in the edge cloud system to achieve greater proximity and distributed self-management, thereby providing services closer to the users. This is crucial for meeting the requirements of real-time applications such as gaming, Virtual Reality, augmented reality, vehicle-based services, etc. This paper proposes a self-orchestrator system within the concept of Home 5G architecture, based on 3-tier edge cloud networks, known as Home Edge computing (HEC). We validate our proposal using a Vehicle-to-vehicle-to-Home Server (V2V2H) use case to evaluate the latency of content sharing between end-devices and the HEC server.

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A Bayesian Belief Network Framework for Protecting Generative AI-driven Attack in Smart Grid Communication

A Bayesian Belief Network Framework for Protecting Generativ...

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international conference on computing, networking and Communications (ICNC)

作者： Md Shirajum Munir Sravanthi Proddatoori Manjushree Muralidhara Sachin Shetty School of Computing Analytics and Modeling Univesity of West Georgia Carrollton GA USA Dept. of Computer Science Old Dominion University Norfolk VA USA Dept. of ECE Old Dominion University Norfolk VA USA

ISBN: (数字)9798331520960

ISBN: (纸本)9798331520977

In the era of artificial intelligence (AI), native generative AI (GenAI) has become prominent in generating intelligent cyber-attacks in a smart grid environment by imitating operational parameters and metrics. As a result, it is imperative to understand the attack generation capabilities of native GenAI models, such as Generative Adversarial Networks (GANs) and Autoencoders in a smart grid environment. This research aims to explore the potential of GenAI models to accurately imitate and analyze the behavior of cyberattacks within a smart grid environment. The goal is to understand the risks posed by these intelligent attacks while developing strategies to protect against disruptive distributed Energy Resources (DER) events, such as incorrect load shifting, imbalanced demand supply, and unstable price forecasting. First, this work leverages two customized native GenAI models, namely GAN and Autoencoder, to synthesize DERs control message parameters such as nominal power consumption, price elasticity coefficients, and communication data packets, among others, to introduce highly unpredictable new intelligent attack vectors. Second, this research proposes and develops a new Bayesian Belief Networks (BBNs) framework by creating correlation dependency nodes among DER control message parameters to understand the risks of intelligent attack vectors better while monitoring and mitigating their impact on smart grid operations. In particular, by leveraging the customized BBN, the system can observe and analyze the uncertain behaviors in DER operations that GenAI introduces, and the proposed framework can help mitigate grid vulnerabilities by understanding the poisonous parameters through mutual information. Finally, the experiment results show that the Autoencoder outperformed GAN in reproducing intelligent attacks with an MSE about 98.984% lower than that of GANs. Additionally, BBN can explain prominent parameters of the intelligent attacks’ by quantifying dependencies thro

关键词： Generative AI Autoencoders Generative adversarial networks Vectors Data models Smart grids distributed power generation Bayes methods Mutual information Load modeling

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distributed Beamforming by Multi-Agent Active Inference

Distributed Beamforming by Multi-Agent Active Inference

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international conference on computing, networking and Communications (ICNC)

作者： Tatsuya Otoshi Masayuki Murata Graduate School of Economics Osaka University Osaka Japan Graduate School of Information Science and Technology Osaka University Osaka Japan

ISBN: (数字)9798350370997

ISBN: (纸本)9798350371000

Massive MIMO systems have emerged as a promising technology for next-generation wireless communication networks. Beamforming, a key technique in Massive MIMO, significantly enhances the system's performance by exploiting the spatial domain. This paper presents a collaborative beamforming approach that leverages vertical collaboration between base stations to improve adaptation and mitigate fading variations, while also applying the principle of free energy to optimize beamforming. The approach involves sharing estimated channel states and learned models among base stations, enabling them to collectively optimize beamforming based on the principle of free energy. Evaluations in single-user operation scenarios demonstrate that both with and without vertical collaboration, the expected free energy, representing beamforming performance, decreases over time. However, vertical collaboration reduces temporary decreases in signal-to-interference-plus-noise ratio (SINR) caused by independent adaptation to fading variations. Furthermore, in a multi-user switching scenario, the proposed approach ensures stable control by utilizing learned models and state estimation results, leading to improved beamforming performance during switching.

关键词： Fading channels Base stations Adaptation models Array signal processing Collaboration Channel estimation Switches

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A Deep Reinforcement Learning Approach to Fair distributed Dynamic Spectrum Access 20

A Deep Reinforcement Learning Approach to Fair Distributed D...

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17th EAI international conference on Mobile and Ubiquitous Systems - computing, networking and Services (MobiQuitous)

作者： Jalil, Syed Qaisar Rehmani, Mubashir Husain Chalup, Stephan Univ Newcastle Callaghan NSW 2308 Australia Munster Technol Univ Cork Ireland

ISBN: (纸本)9781450388405

This paper investigates the task how to achieve fairness in distributed dynamic spectrum access (DSA). Specifically, we consider a cognitive radio network scenario with multiple primary users (PUs) and secondary users (SUs). Each PU operates in a licensed channel. We assume that there is no coordination between PUs and SUs, and no coordination among SUs. The key challenges for SUs are to: (1) avoid collisions with PUs, (2) avoid collisions with other SUs, (3) fair access of spectrum resources in an uncoordinated system, (4) deal with different PU activity patterns, (5) deal with spectrum sensing errors. To address these challenges, we propose a deep reinforcement learning (DRL) approach and an associated reward function to achieve fair access to spectrum resources. Specifically, we use the method of Dueling Double Deep Q-Networks with Prioritised Experience Replay (D3QN-PER) as DRL algorithm for each SU. In our simulation experiments, we demonstrate that the proposed approach performs better than existing DRL methods.

关键词： distributed dynamic spectrum access cognitive radio multi-agent deep reinforcement learning

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Detecting distributed Denial of Service Attacks in Software Defined Network Controllers: Proposed Research

Detecting Distributed Denial of Service Attacks in Software ...

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international conference on Network Applications Protocols and Services (NETAPPS)

作者： Etidal Altom Kunna Mohd Nizam Omar Mohamad Fadli bin Zolkipli InterNetworks Lab School of Computing Universiti Utara Malaysia UUM Sintok Malaysia

ISBN: (数字)9798331519513

ISBN: (纸本)9798331519520

This paper addresses the security vulnerabilities in Software Defined networking (SDN), which separates the network control plane from the data plane. A significant concern is the vulnerability of the SDN controller to distributed Denial of Service (DDoS) attacks, which can disrupt or collapse the entire network. To tackle this issue, a hybrid detection is proposed to detect and mitigate DDoS attacks in two phases. The effectiveness of proposed hybrid detection will be evaluated using the Mininet simulator, with a focus on detection rate and false positive rates and compared to existing DDoS detection techniques. Following the Design Research Methodology (DRM) approach, the research will develop and implement hybrid to enhance SDN network security. The findings are expected to demonstrate the mechanism's ability to protect the SDN controller from DDoS attacks, contributing to the overall resilience of SDN architectures. As mentioned in the title, this paper only focused on the proposed research that to be conducted based on the explained literature review.

关键词： Accuracy Statistical analysis Computational modeling Denial-of-service attack Real-time systems Rigidity Reliability Computer crime Software defined networking Resilience

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Robust Decentralized Online Optimization Against Malicious Agents

Robust Decentralized Online Optimization Against Malicious A...

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international conference on distributed computing Systems

作者： Dacheng Wen Yupeng Li Xiaoxi Zhang Francis C.M. Lau Deparrment of Interactive Media Hong Kong Baptist University Hong Kong Department of Computer Science The University of Hong Kong Hong Kong School of Computer Science and Engineering Sun Yat-sen University China

ISBN: (数字)9798350386059

ISBN: (纸本)9798350386066

Decentralized online optimization, a pivotal paradigm in machine learning, involves multiple agents making online decisions cooperatively in a decentralized network. Despite its outstanding capabilities in processing large-scale streaming data, the ubiquitous existence of malicious agents, capable of disseminating arbitrary information among their neighbors and undetectable a priori, poses a severe threat to the reliability and efficacy of existing decentralized online optimization solutions. In response to the above critical vulnerability in practice, we take the first step to properly address the threat posed by malicious agents. We propose ROOO, a novel robust decentralized online optimization algorithm, specifically designed to counteract the detrimental impact of malicious agents. Our theoretical analysis shows that the regret bound of ROOO is sub-linear, indicating that, over time, its performance progressively approximates that of an offline oracle operating with the benefit of hindsight. Empirical evaluations in two networking applications, including opportunistic channel selection and mobile crowdsensing, further validate our theoretical results and demonstrate the competitiveness of ROOO compared to several advanced baselines.

关键词： Crowdsensing Machine learning Cost function Approximation algorithms Robustness Convex functions distributed computing

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Achieving distributed and Privacy-Preserving Cross-Chain Transactions in Account-Model Blockchain Systems

Achieving Distributed and Privacy-Preserving Cross-Chain Tra...

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Metaverse computing, networking and Applications (MetaCom), IEEE international conference on

作者： Chuan Zhang Weijie Wang Weiting Zhang Jiangtian Nie Jinwen Liang Liehuang Zhu School of Cyberspace Science and Technology Beijing Institute of Technology Beijing China Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies Guangdong China School of Computer Science & Technology Beijing Institute of Technology Beijing China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Computer Science and Engineering Nanyang Technological University Singapore Department of Computing Hong Kong Polytechnic University China

Cross-Chain is an emerging technology to enable transaction circulation across different blockchain systems, breaking down transaction isolation among decentralized ecosystems. Existing cross-chain solutions are often constructed based on centralized trusted third parties, which introduce additional threats to users’ identities due to potentially compromised risks on the centralized third parties. To exclude the single-point compromised risk in centralized systems, this paper focuses on a fully decentralized scenario and develops a distributed cross-chain transaction scheme, which enables cross-chain transaction exchanges while ensuring the unlinkability between payees and payers. Specifically, we first propose a cross-chain cryptocurrency exchange scheme by leveraging Ethereum’s smart contracts, which achieves transaction exchanges in decentralized settings. Then, we leverage zero-knowledge succinct non-interactive argument of knowledge (i.e., zk-SNARKs) to explore a privacy-preserving method for cross-chain transactions in account-model blockchain systems, such that the unlinkability between payees and payers and the privacy of cross-chain participants can be guaranteed. Security analysis and experimental evaluations demonstrate that the proposed scheme achieves the security goal at acceptable costs.

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Managing Network Requirements in distributed and Cooperative Media Algorithms

Managing Network Requirements in Distributed and Cooperative...

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international conference on computing and networking Technology (ICCNT)

作者： Rahul Amina Deepak Kumar R Manjunatha Department of Journalisim & Mass Communication ARKA JAIN University Jamshedpur Jharkhand India Department of Mathematics Vivekananda Global University Jaipur India Department of Data analytics and Mathematical Sciences School of Sciences JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

This paper offers a complete analysis of network requirements for disbursed and cooperative media algorithms to maximize overall performance while shared over an allotted network setting. Network requirements along with bandwidth, latency, scalability, and security had been diagnosed and discussed in the element. The requirement’s impact on the implementation of disbursed and cooperative media algorithms has been analyzed through the usage of an experimental setup and established mathematically. The components of community requirements to enhance the general overall performance of dispensed and cooperative media algorithms as been formulated in a fixed of fashions, which are distinct in the paper. With the models provided, the complexity and scalability, in addition to the requirements to leverage disbursed and cooperative media algorithms for effective communiqué, can be evaluated. Sooner or later, the suggestions for green usage of allotted and cooperative media algorithms and green implementation of community requirements within the design and operation of disbursed structures are discussed in the paper.

关键词： Heuristic algorithms Scalability Bandwidth Media Mathematical models Complexity theory Security Optimization

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