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Research, Development and Application of Railway Bridge information Construction Management Platform Based on BIM+GIS+IoT Technology 3

Research, Development and Application of Railway Bridge Info...

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3rd international conference on Artificial Intelligence and Computer Engineering, ICAICE 2022

作者： Qi, Chenglong China Railway Design Corporation Tianjin300308 China

ISBN: (纸本)9781510663473

In order to resolve the high resource consumption, labour shortage and low information integration problems in the existing extensive construction mode of railway bridges, in combination with railway bridge engineering characteristics, after a general research on intelligent construction necessity and a variety of cutting-edge information technologies, this paper presents a railway bridge information construction management platform which is based on "cloud + end" system, combining with BIM, GIS, cloud computing, big data, Internet of Things, artificial intelligence and other technologies. The main technical route is as follows: in terms of functional architecture, the platform includes 8 modules related to management process and digital construction, ensuring clients two interaction modes: web terminal and mobile terminal;In terms of logical architecture, the platform takes spring cloud as the technical framework, using spring boot to develop distributed systems with Microservices Architecture, and decomposing various business functions into multiple discrete services;In terms of physical architecture, the platform mainly includes front-end server, database server, application server, BIM model management server and firewall, all of which are deployed in Alibaba cloud. The platform is applied to the Changqing Yellow River Bridge Project of Zhengji Railway. Results show that this platform can significantly improve the production efficiency, management efficiency and decision-making ability on site, realize intelligent site with digital twin characteristics, ensure construction safety and save project investment. © 2023 SPIE.

关键词： information management

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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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A Review of Security and information Control in Blockchain-Integrated IoT Applications 3

A Review of Security and Information Control in Blockchain-I...

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3rd IEEE international conference on Blockchain and distributed systems Security, ICBDS 2024

作者： Cholke, Abhijeet Mandhare, V.V. Vikhe, P.S. Matoshri College of Engineering & Research Centre Department of Computer Engineering Nashik India Pravara Rural Engineering College Department of Computer Engineering Loni Ahmednagar India Pravara Rural Engineering College Department of Instrumentation and Control Engineering Loni Ahmednagar India

ISBN: (纸本)9798350354348

The convergence of the Internet of Things (IoT) and blockchain technologies has gained substantial traction in recent years, owing to the rapid advancement of communication technologies worldwide. This research introduces a prototype model that seamlessly integrates an IoT platform with blockchain technology to ensure the integrity of data. The prototype establishes a decentralized framework for IoT devices, underpinned by a private blockchain infrastructure capable of replicating device data and validating transactions among devices through a consensus mechanism. Nevertheless, the implementation of this concept necessitates a closer examination of various considerations. One crucial aspect to address is transforming data generated by diverse IoT devices into a format compatible with the blockchain. This research takes a proactive approach to effective data management within the blockchain. Initially, we collect data from IoT devices and systematically store it in a blockchain-compatible manner. The custom blockchain and smart contract components define the data access policies for end-users. Within this model, we categorize IoT appliances responsible for different services into distinct sets of chains. These sets of chains collaboratively exchange data while adhering to a comprehensive access control *** research endeavors to harmonize IoT and blockchain technologies through a prototype that safeguards data integrity. It tackles the challenge of data conversion from various IoT devices into a blockchain-compatible format and outlines a sophisticated data management strategy. By delineating access policies and segmenting IoT appliances into specialized sets of chains, this model aims to facilitate secure and efficient data sharing among decentralized IoT devices. © 2024 IEEE.

关键词： Data integrity

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Theoretical Study of Underground Wireless Communication System Based on distributed Network 3

Theoretical Study of Underground Wireless Communication Syst...

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3rd international conference on Electronics and Communication;Network and Computer Technology (ECNCT)

作者： Liang Mo Beijing Huayu Engn Co Ltd Xian Branch China Coal Technol & Engn Grp Xian 710075 Shaanxi Peoples R China

ISBN: (数字)9781510652118

ISBN: (纸本)9781510652118;9781510652101

To prevent communication failure in presence of severe underground coal-mine accidents, a large number of research was conducted to improve the effectiveness and reliability of the underground wireless communication systems in literature. In this paper, we first propose to replace the conventional lumped communication system, with the distributed network system. We also demonstrate a software-defined adaptive networking scheme. This scheme enables the automatic re-configuration, when some links or nodes fail in the network. At the same time, the routing strategy based on field strength is provided and the simulation verification is carried out. The results show that the proposed strategy can avoid the inefficient information exchange in the network, and significantly prolong the network life cycle. In addition, we propose an accumulative reception method, coupled with a multi-node co-transmission technique, that significantly improve the transmission reliability. The method is derived mathematically and verified by numerical simulations. The results show that the signal-to-noise ratio at the receiving end is improved, leading to a more reliable communication. The transmission throughput can be maximized when downhole accidents occur. These technologies lay a solid foundation for a more intelligent, efficient and reliable next generation underground wireless communication system.

关键词： underground wireless communication distributed network adaptive network effectiveness reliability

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Optimization of Edge Computing Task Offloading Based on Multi-Agent Game 3

Optimization of Edge Computing Task Offloading Based on Mult...

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3rd international conference on High Performance Computing and Communication Engineering, HPCCE 2023

作者： Yang, Bo Liu, Yusheng Li, Hao Chen, Yimin Deng, Xuegang School of Information Science Yunnan University Kunming650500 China School of Agricultural Economics and Rural Development Renmin University Beijing100000 China Yunnan University School of Information Science & Engineering Yunnan Engineering Rese Arch Center of Smart Tourism Kunming Kunming650500 China Yunnan Development and Reform Commission Kunming China

ISBN: (数字)9781510674653

ISBN: (纸本)9781510674646

In a multi-access edge computing environment, optimizing task offloading under various constraints is a complex challenge. Traditional methods often neglect constraint relationships, leading to uneven resource allocation and suboptimal system performance. Additionally, these methods struggle to adapt to dynamic demands in edge computing. This paper introduces a novel distributed task offloading algorithm based on multi-agent deep reinforcement learning. This approach coordinates multiple agents in making task offloading decisions, aiming to achieve optimized task allocation while respecting constraints, thereby enhancing system performance and reducing latency and energy consumption. Simulation experiments in edge computing scenarios validate the effectiveness and stability of the proposed method. Results demonstrate that the multi-agent deep reinforcement learning approach outperforms traditional methods significantly. It excels in reducing task completion time and lowering terminal device energy consumption, affirming its effectiveness. This research offers a fresh perspective on task offloading strategies in edge computing, addressing limitations in traditional methods and providing a foundation for further exploration in this domain. © 2024 SPIE.

关键词： Reinforcement learning

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Adaptive Fuzzy Logic in Backstepping Control for 3-DOF parallel Delta Robot 3rd

Adaptive Fuzzy Logic in Backstepping Control for 3-DOF Paral...

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3rd international conference on Advances in information and Communication Technology, ICTA 2024

作者： Le, Anh Tuan Truong, Giang Luong Nguyen, Huy Quang Ngoc, Tuan Anh Than The, Bach Tran Khac, Long Nguyen Le, Hoang Giap Le Xuan, Hai Le Van, Dung Ha Tinh College of Technology Ha Tinh Viet Nam Univeristy of Engineering and Technology Vietnam National University Hanoi Viet Nam International School Vietnam National University Hanoi Viet Nam Falcuty of Engineering Technology Hung Vuong Univerisy Phu Tho Viet Nam

ISBN: (纸本)9783031809422

In this study, we propose applying the Backstepping control method to the Delta robot, incorporating Fuzzy Logic to handle fuzzy input values and provide solutions based on fuzzy sets. This approach aims to enable the robot to approximate the desired motion trajectory within a short timeframe and maintain system stability in the face of disturbances that hinder movement between joint torques. The system's stability is ensured and successfully demonstrated based on Lyapunov stability theory. The performance of the controller is evaluated through numerical simulation results using Matlab & Simulink tools on the figure-eight trajectory. Comparing the Backstepping controller combined with Fuzzy Logic to traditional Backstepping, the results demonstrate the superior performance of the Backstepping controller combined with Fuzzy Logic. It can effectively control the motion of the Delta robot along the desired trajectory with small errors, and short response times, providing a more flexible and adaptive control approach that can handle uncertain inputs, especially when the system is affected by unknown external disturbances. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Backstepping

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Speed up QC-LDPC decoder through memory subsystem optimization 3

Speed up QC-LDPC decoder through memory subsystem optimizati...

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3rd international conference on Electronic Communication and Artificial Intelligence, IWECAI 2022

作者： Li, Yajie Liu, Dake Zhou, Xinbing Chen, Wei School of Information And Communication Engineering Hainan University Haikou China

ISBN: (纸本)9781665479974

In this paper, we proposed a QC-LDPC decoder for 5G NR, WiMAX, and WLAN applications. The decoder can flexibly support arbitrary code length and rate under 5G NR standard. This design follows programmable ASIP (Application Specific Instruction-set Processor) design method and uses data parallel SIMD (Single Instruction Multiple Data) architecture. We doubled the logic computing speed to improve the throughout instead of using double speed memory architecture. Compared with the design mentioned in [1], the original design could achieve the highest QC-LDPC decoding throughput of 533Mbps (12 SISO in parallel) when the clock frequency is 200MHz (memory clock frequency is 400MHz). The existing design saved 47% of the decoding clock cycle without lossing decoding circuit quality. We achieved a maximum QC-LDPC decoding throughput of 1984 Mbps (with 48 SISO in parallel) when the system frequency is 400MHz (memory clock frequency is also 400MHz). Further, through circuit optimization, the upper limit of the system clock is promoted from 344MHz to 1.1GHz. The throughput can possibly be upto 5456Mbps. Finally, through the logic synthesis using 28nm SMIC CMOS cell library, the design is physically verified, and the logic gate count is reported 1716K. It is similar to that of the original design per SISO. © 2022 IEEE.

关键词： Memory architecture

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The Role of Blockchain Technology in Supply chain Management for Data Security 3

The Role of Blockchain Technology in Supply chain Management...

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3rd IEEE international conference on Blockchain and distributed systems Security, ICBDS 2024

作者： Birari, Dipika R. Rathod, Vijay U. Dandavate, Aarti Shelke, Nilesh Kumar, Ranjit Kulkarni, Masira M. S Army Institute of Technology Department of Information Technology Pune India G H Raisoni College of Engineering and Management Department of Artificial Intelligent and Machine Learning Wagholi Pune India Dhole Patil College of Engineering Department of Computer Engineering Pune India Symbiosis International Deemed University Symbiosis Institute of Technology Department of Computer Science and Engineering Nagpur Campus Pune India Ajeenkya D Y Patil University Department of Computer Engineering Pune India G H Raisoni College of Engineering and Management Department of Cyber Security and Data Science Wagholi Pune India

ISBN: (纸本)9798350354348

In a traditional supply chain system, the process of producing raw materials so that a product may be delivered to a customer is a manual operation with insufficient data and transaction security. The entire process is time consuming and requires a lot of effort. The undivided process is generally ineffective and unreliable for consumers. The data security, authenticity, the inclusion of will significantly improve the time management and transaction procedures of conventional supply chain management systems. Data is shielded from illegal access via the ground-breaking, decentralized technology known as blockchain. After smart contracts are put into place, the complete supply chain management (SCM) will be satisfied with the customer. When the mediator is contracted, which is possible in various ways, the plan becomes more reliable. This article places particular emphasis on lowering third party involvement in the supply chain system and enhancing data security. Conventional supply chain management techniques have several serious shortcomings. Some of them include a lack of traceability, difficulties maintaining product safety and quality, a failure to track and manage inventories in stores and warehouses, escalating supply chain costs, and so on. The reduction of third-party involvement in the supply chain system and the improvement of data security are the main goals of this article. This enhances process accessibility, effectiveness, and timeliness overall. They will feel safer throughout the payment procedure, which is the main benefit. Yet in this investigation, a smart contract and a peer-to-peer encrypted system were both used. There are a few additional features as well. © 2024 IEEE.

关键词： Smart contract

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Reinforcement Learning-Based Optimal Power Flow Control in Islanded Microgrids 3

Reinforcement Learning-Based Optimal Power Flow Control in I...

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3rd IEEE international conference on Automation and Computation, AUTOCOM 2025

作者： Agarwal, Ankita Kumar, Amit Maity, Dipankar Ojha, Varun Nalini Sunil, M. Dore, Aruna Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Department of Computer Science and Information Technology Odisha Bhubaneswar India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Karnataka Bangalore India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798331542375

One of the popular paradigms for control problems in different applications is Reinforcement Learning. In this paper, we develop an RL-based technique for OPF control in islanded micro grids. Micro grids are small power systems for remote or rural regions that can function independently of the national grid and serve as a dependable alternative. The dependence on their decentralized power generation over DERs is a major complication for micro grid system stability and noteworthy optimization of reactive power flow. The operation of micro grids is both dynamic and stochastic;as a result, operational models based on traditional control methods at the model level or rule-based conflicts with optimized controllers that need to work in an environment where the future long-term forecasts remain uncertain. RL is suggested as a data-driven and adaptive control method to address these issues and optimize power flow in islanded micro grids. The RL-based control proposed in this paper uses realtime data from the micro grid to learn an optimal policy. The presented micro grid environment is for the reinforcement learning agent with which it interacts, and on success or failure of its actions, it will be given a reward signal to learn. The RL agent, through its interactions and learning process by taking actions during the operation of islanded micro grids, can optimize power flow in a distributed manner given DERs availability, load demand dynamics, and network constraints. © 2025 IEEE.

关键词： Reinforcement learning

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Optimized Task Scheduling in Diverse distributed systems with a Hybrid Genetic Algorithm Approach 3rd

Optimized Task Scheduling in Diverse Distributed Systems wit...

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3rd international conference on Intelligent systems and Sustainable Computing, ICISSC 2023

作者： Muthusamy, Ramesh Kumar Kadu, Swati Ayyasamy, Karthikeyan Pichuka Veera Venkata Satya, Srinivas Arumugam, Ramachandran Ammasai, Viswanathan Sengan, Sudhakar Department of Information Technology V.S.B. College of Engineering Technical Campus Tamil Nadu Coimbatore642109 India Department of AI&DS AISSMS IOIT Pune411001 India Department of Computer Science and Engineering Panimalar Engineering College Tamil Nadu Chennai600123 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522502 India Department of Computer Science and Engineering Saveetha Engineering College Tamil Nadu Chennai602105 India School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli627012 India

ISBN: (纸本)9789819783540

In Heterogeneous distributed systems (HDS), efficient task scheduling (TS) across diverse resources remains a pressing challenge. This paper introduces a Hybrid Genetic Algorithm (HGA) as a solution, blending heuristic techniques with the evolutionary strengths of Genetic Algorithms (GAs) to optimize Task Scheduling (TS). Traditional algorithms often fall short in balancing computational speed with solution quality, especially in large-scale environments. This proposed HGA addresses this by leveraging domain-specific heuristics to provide a promising starting point for the GA's optimization process. The TS dilemma has been successfully defined by an all-encompassing logical system, which ensures the accuracy of the design of algorithms. In comparison tests, the HGA frequently comes out on top, demonstrating less makespan and a more excellent distribution of tasks among the resources available. Also, resources with more efficient processing capabilities will be provided priority in this recommended heuristic method, which focuses on tasks with higher computational demands. The findings of the present investigation demonstrate that the HGA may transform TS approaches by providing high-quality solutions while increasing performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Scheduling algorithms

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