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An Effective and Reliable Cross-Blockchain Data Migration Approach 22nd

An Effective and Reliable Cross-Blockchain Data Migration Ap...

引用

22nd international conference on Parallel and distributed computing, Applications and Technologies (PDCAT 2021)

作者： Zhang, Mengqiu Qu, Qiang Ning, Li Fan, Jianping Yang, Ruijie Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Huawei Cloud Blockchain Lab Shenzhen Peoples R China

ISBN: (纸本)9783030967727;9783030967710

As blockchain is widely applied, various decentralized applications would inevitably encounter data migration problems, for reasons, such as the multilevel blockchain scenarios, the exhaustion of blockchain disk space and the swap of the rapidly evolving blockchain engines. In order to proceed the applications smoothly, it is necessary to migrate original blockchain data to a new blockchain instance, which is the cross-blockchain data migration. However, ensuring the reliability of data provenance and the data consistency, and balancing migration efficiency and historical state granularity, introduce unique challenges over cross-blockchain data migration. This paper proposes an effective and reliable cross-blockchain data migration approach to coping with these challenges. To ensure the reliability, a collective mechanism of controlling, executing and storing procedures is proposed to assort migration transactions between blockchains. Furthermore, we propose two migration schemes in order to adapt decentralized application scenarios. Extensive experiments are conducted to demonstrate the effectiveness of the proposed approach.

关键词： Blockchain Data migration Cross-blockchain distributed transactions Decentralized applications

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Role of Serverless computing in Healthcare Systems: Case Studies 22nd

Role of Serverless Computing in Healthcare Systems: Case Stu...

引用

22nd international conference on Computational Science and its Applications (ICCSA)

作者： Kumari, Anisha Behera, Ranjan Kumar Sahoo, Bibhudatta Misra, Sanjay Natl Inst Technol Dept CSE Rourkela India Birla Inst Technol Dept CSE Ranchi Bihar India Ostfold Univ Coll Dept Informat Technol Halden Norway

ISBN: (纸本)9783031105425;9783031105418

Recently, serverless architecture has gained popularity due to its cost-effective policies, independent stateless functions, auto-scaling, and simplified code deployment. It allows the developer to deploy and run their applications without worrying about the underlying architecture. The healthcare services can be made available as a serverless application that consists of distributed cloud services achieving the various requirements in the healthcare industry. The services offered may be available on-premise on a cloud infrastructure to users and health service providers. This paper presents four case studies that have been successfully adapted serverless architecture for health care systems, where the health services are provided as functional units to various stakeholders. We have also discussed various components of healthcare systems that may require serverless services over the cloud infrastructure.

关键词： Serverless computing Function as a service Healthcare systems HIPAA Amazon lambda Orchestration OpenWhisk

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Orchestration of Heterogeneous, distributed, Real-Time Control Containers

Orchestration of Heterogeneous, Distributed, Real-Time Contr...

引用

IEEE international conference on Industrial Informatics (IndIN)

作者： Moritz Walker Leonard Rupietta Armin Lechler Michael Neubauer Alexander VerI Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Stuttgart Germany

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

In today's global market, manufacturers must be highly adaptable, producing profitably smaller batches. Disin-tegrating hardware and software and embracing modern IT concepts like containerization and Service-oriented Architecture enable this flexibility. While offering rapid reconfiguration, these approaches add complexity. Orchestration tools aid in analyzing response times, workload mapping, and parameter selection for containerized real-time applications. However, current tools struggle with managing distributed, heterogeneous, real-time apps. This paper proposes an orchestration solution based on Compositional Performance Analysis and Genetic Algorithm to optimize task allocation across diverse computing resources. The approach enables the orchestration of heterogeneously scheduled, container-based. distributed real-time systems.

关键词： Globalization Real-time systems Software Hardware Service-oriented architecture Performance analysis Time factors Resource management Informatics Genetic algorithms

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Slicing-Based Offloading in Vehicular Edge computing 22

Slicing-Based Offloading in Vehicular Edge Computing

引用

IEEE 22nd international conference on High Performance Switching and Routing (IEEE HPSR)

作者： Berri, Sara Hejja, Khaled Labiod, Houda Inst Polytech Paris Telecom Paris INFRES F-91120 Palaiseau France CY Cergy Paris Univ UMR 8051 ETIS ENSEACNRS F-95000 Cergy France

ISBN: (纸本)9781665440059

Vehicular edge computing (VEC) provides an environment for offloading tasks from vehicles. Indeed, the advantage through VEC is to push power computational and storage capacities at the edge nodes near the vehicles to handle the enormous resources required by some applications. On the other hand, in order to manage efficiently these resources, it would be necessary to partition them into several parts, each dedicated to a specific service. Thus, integrating network slicing in VEC appears to be relevant. Therefore, in this paper we study the task offloading problem from vehicles to wireless 5G new generation nodes (gNBs) and road side units (RSUs) hosting sliced edge computing servers. We formulate the problem as an integer linear programming problem and propose a new algorithm, which follows a centralized control strategy to holistically view and manage the whole network, and the sliced edge nodes. In addition, it follows network function virtualization framework to separate the logical network from the physical resources. The simulation results show that, in terms of acceptance ratio, the proposed algorithm provides very close results to the optimal solution, and when compared to state-of-art algorithm, integrating slicing is better when there is enough resources on the hosting nodes, but it still guarantees the differentiation among services.

关键词： Vehicular Edge computing Network Slicing Task Offloading Software Defined networking Network Function Virtualization

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A Learning-Based Scheduler for High Volume Processing in Data Warehouse Using Graph Neural Networks 22nd

A Learning-Based Scheduler for High Volume Processing in Dat...

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22nd international conference on Parallel and distributed computing, Applications and Technologies (PDCAT 2021)

作者： Bengre, Vivek HoseinyFarahabady, M. Reza Pivezhandi, Mohammad Zomaya, Albert Y. Jannesari, Ali Iowa State Univ Dept Comp Sci Lab Software Analyt & Pervas Parallelism SwAPP Ames IA USA Univ Sydney Ctr Distributed & High Performance Comp Sch Comp Sci Camperdown NSW Australia

ISBN: (纸本)9783030967727;9783030967710

The process of extracting, transforming, and loading (also known as ETL) of a high volume of data plays an essential role in data integration strategies in data warehouse systems in recent years. In almost all distributed ETL systems currently use in both industrial and academia context, a simple heuristic-based scheduling policy is employed. Such a heuristic policy tries to process a stream of jobs in the best-effort fashion, however, it can result in under-utilization of computing resources in most practical scenarios. On the other hand, such inefficient resource allocation strategy can result in an unwanted increase in the total completion time of data processing jobs. In this paper, we develop an efficient reinforcement learning technique that uses a Graph Neural Network (GNN) model to combine all submitted tasks graphs into a single graph to simplify the representation of the states within the environment and efficiently make a parallel application for processing of the submitted jobs. Besides, to positively augment the embedding features in each leaf node, we pass messages from leaf to root so the nodes can collaboratively represent actions within the environment. The performance results show up to 15% improvement in job completion time compared to the state-of-the-art machine learning scheduler and up to 20% enhancement compared to a tuned heuristic-based scheduler.

关键词： Extract Transform Load (ETL) operations Scheduling policy Data streaming processing system Graph neural networks Job completion time Reinforcement learning

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international Program Committee

International Program Committee

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ACIS international conference on Software Engineering, Artificial Intelligence, networking, and Parallel/distributed computing (SNPD)

Provides a listing of current committee members and society officers.

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AKMA for Secure Multi-access Edge computing Mobility in 5G 22nd

AKMA for Secure Multi-access Edge Computing Mobility in 5G

引用

22nd international conference on Computational Science and its Applications (ICCSA)

作者： Akman, Gizem Ginzboorg, Philip Niemi, Valtteri Univ Helsinki Helsinki Finland Aalto Univ Helsinki Finland Huawei Technol Helsinki Finland

ISBN: (纸本)9783031105425;9783031105418

Multi-Access Edge computing (MEC) extends the cloud computing capabilities to the edge of the 5G network. The current 3rd Generation Partnership Project (3GPP) and European Telecommunications Standard Institute (ETSI) specifications about MEC cover connectivity between a mobile user and a MEC host, including security, but they do not extend to application-level security and privacy issues. We solve the problem of creating a secure and privacy-preserving communication channel between a mobile user and a distributed MEC application. The solution is limited to the case where the mobile network remains the same during communication. The solution is based on the 3GPP AKMA for authentication and key sharing. It includes protocols for (1) registering the user to the main server of the application, (2) updating the user information and shared keys with the main server of the application, (3) using the application in the MEC host in the static case, (4) using the application in MEC host while moving.

关键词： MEC 5G AKMA MEC mobility Security Privacy

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Llama-Recipe - Fine-Tuned Meta's Llama LLM, PBOM and NFT Enabled 5G Network-Slice Orchestration and End-to-End Supply-Chain Verification Platform 22

Llama-Recipe - Fine-Tuned Meta's Llama LLM, PBOM and NFT Ena...

引用

22nd IEEE Consumer Communications and networking conference, CCNC 2025

作者： Bandara, Eranga Bouk, Safdar H. Shetty, Sachin Roy, Sandip Mukkamala, Ravi Rahman, Abdul Foytik, Peter Liang, Xueping Keong, Ng Wee De Zoysa, Kasun Old Dominion University NorfolkVA United States Deloitte & Touche Llp United States Florida International University United States Nanyang Technological University Singapore University of Colombo School of Computing Sri Lanka

ISBN: (纸本)9798331508050

Modern 5G networks offer a network-sliced infrastructure where each network slice contains a dedicated 5G core software service layer. The 5G core software services in each slice shares common core network resources to meet specific customer needs. A primary challenge in 5G network slicing involves resource sharing and efficient network slice orchestration. Container-based methodologies, including tools like Docker and Kubernetes, have become popular for orchestrating 5G network slice services and managing configurations in microservices-based cloud-native service deployment. However, despite their utility, these tools present significant challenges. Their complexity often necessitates dedicated DevOps teams for effective management, while configuration management can prove arduous, and end-to-end supply chain oversight is lacking. To address these challenges, this paper introduces 'Llama-Recipe,' a cloud-native 5G-core service deployment and orchestration platform integrating Generative AI, SBOM, PBOM and NFT. 5G-core service configurations across different network slices are represented as 'HOCON (Human-Optimized Config Object Notation)' config objects adhering to the GitOps paradigm. Leveraging custom-trained Meta's Llama2 LLM, Llama-Recipe generates the Kubernetes manifests for network-sliced 5G-core services based on the defined HOCON configurations. The generated Kubernetes manifests of the 5G-core services are deployed in designated Kubernetes clusters utilizing GitOps tools (e.g., ArgoCD), ensuring seamless and automated deployment processes. Additionally, Llama-Recipe introduced a novel mechanism to handle end-to-end supply chain verification of 5G-core software services using Software-Bill of Materials (SBOM) and Pipeline-Bill of Materials (PBOM). SBOMs track all the dependencies and PBOMs facilitate the comprehensive tracking of end-to-end supply chain data for 5G-core software services, enhancing transparency and security. These PBOMs are also generated

关键词： DevOps

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Quantum Annealing Approach for the Optimal Real- time Traffic Control using QUBO

Quantum Annealing Approach for the Optimal Real- time Traffi...

引用

22nd IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, networking and Parallel/distributed computing (SNPD-Fall)

作者： Singh, Amit Lin, Chun-Yu Huang, Chung-, I Lin, Fang-Pang Natl Appl Res Labs Natl Ctr High Performance Comp Hsinchu 300 Taiwan Natl Yang Ming Chiao Tung Univ Dept Mech Engn Hsinchu 300 Taiwan

ISBN: (纸本)9781665404037

Traffic congestion is one of the major issues in urban areas, particularly when traffic loads exceed the road's capacity, resulting in higher petrol consumption and carbon emissions as well as delays and stress for road users. In Asia, the traffic situation can be further deteriorated by road sharing of scooters. How to control the traffic flow to mitigate the congestion has been one of the central issues in transportation research. In this study, we employ a quantum annealing approach to optimize the traffic signals control at a real-life intersection with mixed traffic flows of vehicles and scooters. Considering traffic flow is a continuous and emerging phenomenon, we used quadratic unconstrained binary optimization (QUBO) formalism for traffic optimization, which has a natural equivalence to the Ising model and can be solved efficiently on the quantum annealers, quantum computers or digital annealers. In this article, we first applied the QUBO traffic optimization to artificially generated traffic for a simple intersection, and then we used real-time traffic data to simulate a real "Dongda-Keyuan" intersection with dedicated cars and scooter lanes, as well as mixed scooter and car lanes. We introduced two types of traffic light control systems for traffic optimization: C-QUBO and QUBO. Our rigorous QUBO optimizations show that C-QUBO and QUBO outperform the commonly used fixed cycle method, with QUBO outperforming C-QUBO in some instances. It has been found that QUBO optimization significantly relieves traffic congestion for the unbalanced traffic volume. Furthermore, we found that dynamic changes in traffic light signal duration greatly reduce traffic congestion.

关键词： real-time optimization traffic optimization traffic signal control quantum annealing quantum computing QUBO

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Retrieval-Augmented Generation Powered by a Multi-agent System to Assisted the Operation of Industries 22nd

Retrieval-Augmented Generation Powered by a Multi-agent Syst...

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22nd international conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2024

作者： Oliveira, Francisco Gomes, Luis Vale, Zita GECAD – Research Group on Intelligent Engineering and Computing for Advancement Innovation and Development Polytechnic of Porto Porto Portugal LASI – Intelligent Systems Associate Laboratory Polytechnic of Porto Porto Portugal

ISBN: (纸本)9783031704147

The introduction of large language models in recent years transformed the use of artificial intelligence in our daily life, making it available to common users and allowing them to interact with natural language processing machines. However, the common and general knowledge of large language models is not reliable when it comes to the quality of the response and its veracity. The proposed work integrates the use of retrieval-augmented generation with large language models with a multi-agent system framework to enable the creation of trees of knowledge where multiple agents have domain specific knowledge. The proposed agent-based solution was tested in a realistic case study where multiple knowledge domains are distributed amongst six different agents. The case study evaluates the capacity of agents to delegate questions according to its topics and the capacity of correctly replying to questions. The results are promising, demonstrating the ability of large language models to assess and process information that wasn’t used in its training process. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Natural language processing systems

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