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A Novel distributed computing Resource Operation Mechanism for Edge computing 9

A Novel Distributed Computing Resource Operation Mechanism f...

引用

9th international conference on Computer and Communications, ICCC 2023

作者： Wei, Hua Guan, Yunxia Zhao, Qihui Zhang, Tingting Liu, Jinglei Zhang, Hao China Mobile Research Institute Department of Network and It Technology Research Beijing100053 China

ISBN: (纸本)9798350317251

Traditional cloud computing services are generally deployed centrally, which can not meet the ultra-low delay requirements of services such as VR/AR, Internet of Vehicles, and cloud games. Edge computing can solve this problem by deploying nodes near users. Edge nodes are geographically dispersed and great in number, which usually are not provided by single edge computing service provider but by multiple. these providers are in competitive relationship. Tradition centralized cloud computing resource operation model can't achieve unified resource orchestration and operation among edge nodes. therefore, a fair and efficient computing resources operation mechanism is necessary. In this paper, firstly, we design a new distributed computing resource operation strategy. In the state of perfect competition, each edge node decides the price of local computing resources by itself. Users can freely choose among many providers according to their own strategies, realizing fair competition among different edge computing service providers. then, to increase the market size while maximize the revenue of edge computing service providers, we define a multi-objective optimization model. Finally, we design a dynamic price adjustment mechanism to calculate reference price for edge node. the simulation results show that the computing resource operation mechanism we designed is significantly better than the traditional edge computing model. © 2023 IEEE.

关键词： Edge computing

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Blockchain-based distributed consensus system architecture for cooperative vehicle-infrastructure sensing 9

Blockchain-based distributed consensus system architecture f...

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9th international conference on Electromechanical Control Technology and Transportation, ICECTT 2024

作者： Peng, Zhou Chao, Wu Di, Xiang Xiao Chen, Gong Chengjun, Feng China Merchants Testing Vehicle Technology Research Institute Co. Ltd. No.9 Xinjin Avenue High tech Zone Chongqing China No.9 Xinjin Avenue High tech Zone Chongqing China

ISBN: (纸本)9781510682399

this paper proposes a distributed architecture for cooperative vehicle-infrastructure sensing, leveraging blockchain and sensing-communication consensus system to empower intelligent connected vehicles. the architecture comprises three layers: a perception layer, an edge control layer, and a cloud computing layer. the perception layer consists of distributed heterogeneous sensors continuously collecting panoramic environmental data, which are then authenticated and stored on the blockchain. the edge control layer, deployed roadside, is responsible for local data fusion, modeling, and closed-loop control. the cloud computing layer, formed by a cluster of consortium blockchain nodes, performs decision-making analysis on global data and optimizes models. these three layers collaborate through a hierarchical blockchain consensus mechanism. Separate chains record outputs from the sensing, edge control, and cloud computing layers, respectively, and these are then merged into a unified and immutable main chain. Security encryption and economic incentives are integrated throughout the system to ensure its security, trustworthiness, and sustainability. this innovative architecture fuses blockchain and sensing technology, creating a distributed platform for cooperative vehicle-infrastructure sensing. the platform achieves a division of labor among wide-area perception, edge control, and cloud-based decision-making, significantly enhancing sensing capabilities, security, scalability, and decision-making accuracy. this provides new momentum for the development of intelligent transportation systems. © 2024 SPIE.

关键词： Data fusion

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Solar Irradiance Forecasting Utilizing distributed and Federated Learning 25

Solar Irradiance Forecasting Utilizing Distributed and Feder...

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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： Zhang, Hao Yan, Ke College of Information Engineering China Jiliang University Hangzhou China China Jiliang University National University of Singapore Singapore

ISBN: (纸本)9798350330014

Photovoltaic energy generation and prediction are crucial for the integration between solar plants and smart grid. Accurate solar radiation prediction is one of the most important research topics for solar energy generation. Existing deep learning methods require sufficient data for training for achieving the desired results. In traditional deep learning modeling, the data sets required for model training usually come from various data in different regions and organizations, and it is difficult to ensure data security and privacy protection. Federated learning can effectively utilize the data optimization model while ensuring data security and privacy, but there is still the risk of privacy leakage by analyzing the parameters uploaded by the client. To effectively utilize data optimization models while ensuring data security and privacy, we propose a method based on a federated learning framework and N-BEATS to achieve interpretable time series prediction of solar irradiance. the model builds the N-BEATS model on the solar irradiance datasets of multiple institutions in a distributed method, does not share local data to protect institutional data privacy, the concept of differential privacy (DP) is introduced, Gaussian noise is added to the parameters of the client before the server-side aggregation processing, the model parameters of each distributed node are collected through TCP communication for federated average, and the parameters are returned to each distributed node. the experimental results show that compared with other deep learning models, the model has better prediction accuracy under the premise of ensuring data security and privacy. © 2023 IEEE.

关键词： Solar radiation

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Efficient distributed Parallel Inference Strategies via Block-based DNN Structure in Edge-to-IoT Continuum 24

Efficient Distributed Parallel Inference Strategies via Bloc...

引用

9th international conference on Intelligent Information Technology (ICIIT)

作者： Choi, Inhun Akhter, Sharmen Jeong, Hong-Ju Huh, Eui-Nam Kyung Hee Univ Dept Comp Sci & Engn Gyeonggi Do 17104 South Korea Kyung Hee Univ Dept Artificial Intelligence Yeonggi Do 17104 South Korea

ISBN: (纸本)9798400716713

Recently, AI and deep neural networks have found extensive applications in mobile devices, drones, carts, and more. To meet the demands of processing large-scale data and providing DNN inference services with minimal latency, there is a need. However, IoT devices, with their limited computing capabilities, are not well-suited for AI inference. Moreover, considering the diverse requirements of different services, it is necessary to provide inference services that address these variations. To address these challenges, many previous studies have explored collaborative approaches between edge servers and cloud servers by partitioning DNN models. However, these methods face difficulties in finding optimal partitioning points for splitting DNN models and are heavily influenced by network bandwidth since intermediate computation results need to be transmitted to other devices. In this paper, we propose the Adaptive block-based DNN network inference framework. this involves breaking down a large DNN model into block-level networks, training them using knowledge distillation techniques to enable inference only through each block network. Subsequently, dynamic block-level inference calculations are offloaded based on the computing capabilities of edge clusters, providing inference results. Even when using multiple devices, our method is not affected by network bandwidth since only input images need to be transmitted. Experimental results demonstrate that our approach consistently reduces inference latency as the number of devices increases. Additionally, by controlling the trade-off between latency and accuracy, we can provide inference services tailored to various latency requirements.

关键词： DNN inference Block-based DNN network trade-off between latency and accuracy

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Demand Response Scheme: Achieving Sustainability in distributed Data Processing 9

Demand Response Scheme: Achieving Sustainability in Distribu...

引用

9th IEEE international conference on Data Science in Cyberspace, DSC 2024

作者： Zhai, Xueying Peng, Yunfeng Guo, Xiuping Zhang, Liang Zhang, Wei University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China Beijing University of Posts and Telecommunications School of Economics and Management Beijing China Guizhou Institute of Technology Guizhou Key Laboratory of Electric Power Big Data Guizhou China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China

ISBN: (纸本)9798350391367

the rapid development of Internet of things (IoT) technology has driven the intelligent transformation of various industries, including manufacturing, agriculture, and healthcare, etc., significantly enhancing their management capabilities and decision-making efficiency. Data analysis is crucial, serving as both the core technology of this transformation and a major driving force for advancing industry intelligence. However, the increasing volume of data has led to high energy consumption during data analysis, posing significant challenges to environmental and economic sustainability. Integrating renewable energy sources (RESs) is an effective way to reduce greenhouse gas emissions due to their low-carbon and renewable nature. Additionally, the spatiotemporal variability and complementarity of RES generation and grid electricity prices provide favorable conditions for distributed data processing. therefore, a two-stage demand response scheme is proposed to reduce carbon emissions and electricity costs by prioritizing data processing in data centers (DCs) where RES is abundant or electricity prices are low, based on RES generation and electricity price signals. Simulation results show that the proposed scheme reduces 36.37% carbon emissions and 20.49% electricity costs compared to the benchmark algorithm, indicating its potential for both environmental and economic optimization. © 2024 IEEE.

关键词： Low emission

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Towards Mobility Management in MEC Simulation 9

Towards Mobility Management in MEC Simulation

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9th IEEE international conference on Network Softwarization (IEEE NetSoft) - Boosting Future Networks through Advanced Softwarization

作者： Araujo, Paulo J. Lopez, Helena Fernandez Faria, Joao Santos, Alexandre Univ Minho Algoritmi Res Ctr Braga Portugal Univ Minho Algoritmi Res Ctr LASI Braga Portugal Dstelecom SA Dept Innovat Braga Portugal

ISBN: (纸本)9798350399806

Multi-access Edge computing (MEC) brings cloud capabilities to the edge, allowing less powerful devices to offload tasks while, together with the effective distribution of content and resources across edge hosts, enabling ultra-low latency. With the distributed resources across the network and mobile devices constantly changing location, it is most important to correctly manage and orchestrate those resources to deliver the best possible network performance efficiently. this paper investigates how MEC systems manage mobility and which efforts have been made in mobility simulation in MEC. A MEC simulation setup and two scenarios were developed using Simu5G and evaluated regarding their latency and use of resources when subject to SUMOgenerated mobility data. Analysis of the simulated scenarios show that the MEC systems reacts differently depending upon different mobility conditions. Also, the developed setup showed to be very useful to develop and test mobility management strategies in MEC environments.

关键词： multi-access edge computing mobility simulation simu5g

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Design and Analysis of Proposed Smartphone-based distributed Parallel Processing System 9

Design and Analysis of Proposed Smartphone-based Distributed...

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9th international Engineering conference on Sustainable Technology and Development, IEC 2023

作者： Muhammed, Nashma Taha Rashid, Zryan Najat Zeebaree, Subhi R. M. Jghef, Yousif Sufyan Ibrahim, Rowaida Khalil Sami, Teba Mohammed Ghazi Sulaimani Polytechnic University It Department Sulaymani Iraq Sulaimani Polytechnic University Computer Network Department Sulaymani Iraq Duhok Polytechnic University Energy Eng. Department Duhok Iraq Knowledge University Computer Eng. Department Erbil Iraq University of Zakho Computer Science Department Duhok Iraq

ISBN: (纸本)9798350335064

Online storage and use of digital assets and applications are both aspects of cloud computing. through a computer network, distributed information systems store and transmit data. Data and effort have both grown for studying and keeping track of outcomes. Cloud-based parallel processing techniques must be improved. Our research hastens the resolution of interactive composite jobs. In this innovative architecture, cell phones act as servers for distributed parallel processing and cloud computing. Users with restricted availability could find the update useful for completing challenging jobs. the recommended strategy is supported by cloud computing, which may expand to infinity servers (webserver). Servers between clients and servers are automatically registered by web servers. Cloud storage and client-side matrices (web server). To ensure timely completion, the server distributes matrix algebra assignments to all subscribed workstations. Before transmitting results to the user, the server uploads them to the cloud. A large number of sets of two-dimensional matrices were requested from the user, and the responses were compared to the total number of servers that were available. © 2023 IEEE.

关键词： Smartphones

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Enhancing Forecasting Precision in Indian Industrial Workers' Inflation: A Comparison of Advanced Machine Learning Models 9

Enhancing Forecasting Precision in Indian Industrial Workers...

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9th international conference on Wireless Communications, Signal Processing and networking, WiSPNET 2024

作者： Amirthavarshini, V. Singh, Soumyendra Prasanna Kumar, R. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science Engineering Chennai India Amrita School of Computing Chennai CSE Amrita Vishwa Vidyapeetham Chennai India

Inflation is a key economic indicator of a country9;s growth in the contemporary world. this research paper focuses on time series analysis and forecasting of inflation data for Indian industrial workers by employi... 详细信息

ISBN: (纸本)9798350350845

Inflation is a key economic indicator of a country's growth in the contemporary world. this research paper focuses on time series analysis and forecasting of inflation data for Indian industrial workers by employing various machine learning models. this study utilizes the Consumer Price Index (CPI) to measure inflation. It explores and compares the application of Long ShortTerm Memory (LSTM), bidirectional LSTM (BiLSTM), XGBoost, and Random Forest models for predicting future inflation values. the dataset used for this spans from January 1993 to November 2023, sourced from the Labour Bureau of the Government of India. the models are evaluated based on mean squared error (MSE) and their ability to forecast the inflation value for November 2023. the proposed BiLSTM model outperforms the others in terms of MSE and accuracy in forecast values. Although computationally intensive, BiLSTM demonstrates enhanced context understanding and improved learning for long-term dependencies in time series data with a MSE value of 0.9410. the study emphasizes the effectiveness of various forecasting models and the use of data-driven approaches to make decisions based on empirical evidence and inflation trends. It also highlights the potential for incorporating AI into economic analyses for continuous monitoring, effective policy-making, and future advancements. © 2024 IEEE.

关键词： Time series analysis

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A Multi-Hop-Aware User To Edge-Server Association Game 9

A Multi-Hop-Aware User To Edge-Server Association Game

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9th IEEE international conference on Network Softwarization (IEEE NetSoft) - Boosting Future Networks through Advanced Softwarization

作者： Kardjadja, Youcef Tsang, Alan Ibnkahla, Mohamed Ghamri-Doudane, Yacine Carleton Univ Syst & Comp Enginering Dept Ottawa ON Canada Carleton Univ Sch Comp Sci Dept Ottawa ON Canada Univ La Rochelle Lab Informat Image & Interact L3I La Rochelle France

ISBN: (纸本)9798350399806

Nowadays, services and applications are becoming more latency-sensitive and resource-hungry. Due to their high computational complexity, they can not always be processed locally in user equipment, and have to be offloaded to a distant powerful server. Instead of resorting to remote Cloud servers with high latency and traffic bottlenecks, service providers could map their users to Multi-Access Edge computing (MEC) servers that can run computation-intensive tasks nearby. this mapping of users to MEC distributed servers is known as the Edge User Allocation (EUA) problem, and has been widely studied in the literature from the perspective of service providers. However, users in previous works can only be allocated to a server if they are in its coverage. In reality, it may be optimal to allocate a user to a distant server (e.g., two hops away from the user) if the latency threshold and system cost are both respected. this work presents the first attempt to tackle the multi-hop aware EUA problem. We consider the static EUA problem where users have a simultaneous-batch arrival pattern, and detail the added complexity compared to the original EUA setting. Afterwards, we propose a game theory-based distributed approach for allocating users to edge servers. We finally conduct a series of experiments to evaluate the performance of our approach against other baseline approaches. the results illustrate the potential benefits of allowing multi-hop allocations in providing better overall system cost to service providers.

关键词： Edge User Allocation Multi-Access Edge computing Game theory Multi-hop Networks

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Quarks: A Secure and Decentralized Blockchain-Based Messaging Network 10

Quarks: A Secure and Decentralized Blockchain-Based Messagin...

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10th IEEE international conference on Cyber Security and Cloud computing and 9th IEEE international conference on Edge computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Shuhan, Mirza K. B. Islam, Tariqul Shuvo, Enam A. Bappy, Faisal H. Hasan, Kamrul Caicedo, Carlos Software Research and Engineering BKash Limited Dhaka Bangladesh SyracuseNY United States Asia Pacific University of Technology and Innovation School of Computing Kuala Lumpur Malaysia Tennessee State University NashvilleTN United States

ISBN: (纸本)9798350312461

Over the past two decades, the popularity of messaging systems has increased both in enterprise and consumer level. Many of these systems used secure protocols like end-to-end encryption to ensure strong security features such as 'future secrecy' for one-to-one communication. However, the majority of them rely on centralized servers owned by big IT companies, which allows them to use their users' personal data. Also it allows the government to track and regulate their citizens' activities, which poses significant threats to 'digital freedom'. Also, these systems have failed to achieve security attributes like confidentiality, integrity, privacy, and future secrecy for group communications. In this paper, we present a novel blockchain-based secure messaging system named Quarks that overcomes the security pitfalls of the existing systems and eliminates the centralized control. We have analyzed our design of the system with security models and definitions from existing literature to demonstrate the system's reliability and usability. We have developed a Proof of Concept (PoC) of the Quarks system leveraging distributed Ledger Technology (DLT), and conducted load testing on that. We noticed that our PoC system achieves all the desired attributes that are prevalent in a traditional centralized messaging scheme despite the limited capacity of the development and testing environment. therefore, this assures us the applicability of such systems in near future if scaled up properly. © 2023 IEEE.

关键词： Blockchain

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