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the Russian Segment (RU-VRF) in WLCG Infrastructure: High Performance computing Network 4

The Russian Segment (RU-VRF) in WLCG Infrastructure: High Pe...

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4th international Science and Technology conference "Modern Network Technologies", MoNeTec 2022

作者： Velikhov, Vasily E. Korenkov, Vladimir V. Ryabinkin, Eygene A. Dolbilov, Andrey G. Gugel, Yury V. Strizh, Tatiana A. Joint Computing Cluster National Research Center 'Kurchatov Institute' Moscow Russia International Intergovernmental Organization Joint Institute for Nuclear Research Meshcheryakov Laboratory of Information Technologies Dubna Russia

ISBN: (数字)9781665472463

ISBN: (纸本)9781665472463

the paper describes a high-performance computer network optimized for the transmission of experimental data generated by CERN for potential use by the Large Hadron Collider (LHC) network community, including the Russian segment of this network. the Worldwide LHC computing Grid (WLCG) is a global computing infrastructure whose mission is to provide computing resources for storing, distributing and analyzing data generated by the LHC at CERN, making the data equally accessible to all participants, regardless of their physical location. WLCG is a multi-layer distributed computing infrastructure. It provides a community of over 12,200 scientists of 110 nationalities from institutions in over 40 countries with near real-time access to LHC data. WLCG is the world's largest computer network. It is supported by many related national and international networks and projects around the world. Since the beginning of the WLCG Project the Russian computing centers in NRC 'Kurchatov Institute' an JINR have participated with reliable and stable resources as well as personnel for the LHC. Contribution to the ALICE, ATLAS, CMS and LHCb Tier 1 and Tier 2 computing resources (disk and CPUs) in the last 10 years has been substantial. In this paper, we would like to show the evolution and technical updates in the Russian segment Tier1 and Tier 2. the Russian segment is an infrastructure fully integrated into the WLCG. © 2022 ieee.

关键词： Program processors

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2024 4th international conference on Robotics, Automation, and Artificial Intelligence, RAAI 2024

2024 4th International Conference on Robotics, Automation, a...

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4th international conference on Robotics, Automation, and Artificial Intelligence, RAAI 2024

ISBN: (纸本)9798331520038

the proceedings contain 59 papers. the topics discussed include: dynamic automatic chiptune generation for game music;motion planning of counterpoint parallel robot based on improved particle swarm optimization algorithm;evaluating robustness of reinforcement learning algorithms for autonomous shipping;generating spatial binaural environmental audio alert on a personal audio device;convolution on honeycomb structures with three-axis coordinate system;multi-sensor fusion floor location method based on extended Kalman algorithm;adoption of artificial intelligence enabling value creation in business;development and integration of an autonomous in-house manipulator arm for enhanced object interaction in rescue robotics;prediction of particulate matter in a mining environment via machine learning;and development of a reconfigurable holonomic mobile manipulation cobot for smart factory 5.0.

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A Column Sparse Controller Design for distributed Networked Control systems 8th

A Column Sparse Controller Design for Distributed Networked...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

作者： Guan, Yanpeng Yin, Hongjie Sun, Chao Yao, Qingsheng Shanxi University Taiyuan030013 China Kunming Shipborne Equipment Research and Test Center Kunming650216 China

ISBN: (纸本)9789819602933

this paper presents a distributed structured controller design method in the case of finite number of subsystems with sensor failures. the constraint on the number of sensor failures is represented by a cardinality constraint on the controller gain matrix. A mixed integer programming method is employed to deal with this type of column cardinality constraint. By using the Lyapunov functional method, we present a sufficient condition that guarantees the H∞ asymptotic stability of the closed-loop system. And a column sparse controller design method is presented in the form of linear matrix inequalities. Finally, a numerical example is provided to illustrate the effectiveness of the developed approach. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lyapunov functions

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Learning-based Co-Design of distributed Edge Sensing and Transmission for Industrial Cyber-Physical systems 19

Learning-based Co-Design of Distributed Edge Sensing and Tra...

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ieee 19th international conference on Industrial Informatics (INDIN)

作者： Jin, Tiankai Ji, Zhiduo Zhu, Shanying Chen, Cailian Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China

ISBN: (纸本)9781728143958

Industrial cyber-physical systems (ICPS) refer to an emerging generation of intelligent systems, where distributed data acquisition is of great importance and is influenced by data transmission. In the improvement of the overall performance of sensing accuracy and energy efficiency, sensing and transmission are tightly coupled. Due to the unknown transmission channel states in the harsh industrial field environment, intelligently performing sensor scheduling for distributed sensing is challenging. In this paper, edge computing technology is utilized to enhance the level of intelligence at the edge side and deploy advanced scheduling algorithms. We propose a learning-based distributed edge sensing-transmission co-design (LEST) algorithm under the coordination of the sensors and the edge computing unit (ECU). Deep reinforcement learning is applied to perform real-time sensor scheduling under unknown channel states. the conditions for the existence of feasible scheduling policies are analyzed. the proposed algorithm is applied to estimate the slab temperature in the hot rolling process, which is a typical ICPS. the simulation results demonstrate that the overall performance of LEST is better than other suboptimal algorithms.

关键词： Industrial cyber-physical systems (ICPS) distributed edge sensing sensing-transmission co-design deep reinforcement learning

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Optimizing Cloud computing Performance using Adaptive and Evolutionary Algorithms for Large Scale Applications

Optimizing Cloud Computing Performance using Adaptive and Ev...

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distributed computing and Electrical Circuits and Electronics (ICDCECE), ieee international conference on

作者： Parashiva Murthy B M Vidhyadar Unni Krishnan M K Pushpa Madhu B K Falguni Tlajiya Aparajita Mohanty Department of Computer Science and Engineering SJCE JSS Science and Technology University Mysuru India Visa Commercial Solutions Division Visa Inc Foster City USA Department of Electronics and Instrumentation Engineering Ramaiah Institute of Technology Bangalore India Department of Computer Science and Engineering Vidya Vikas Institute of Engineering and Technology Mysore India Department of Electrical Engineering Faculty of Engineering and Technology Parul Institute of Engineering and Technology Parul University Vadodara India Faculty of Law Symbiosis Law School Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331533663

ISBN: (纸本)9798331533670

An increasing number of applications are straining cloud computing structures which require novel optimization strategies to boost performance measurements as well as resource utilization. the research methodology incorporates adaptive algorithms together with evolutionary algorithms which provide real-time workload adaptation and distributed system resource optimization. the project implemented machine learning models which predicted resource needs to trigger automatic parameter modification for computing systems. the three major cloud platforms provided results which showed a 37.8% decrease in response latency and a 42.3% lower resource wastage rate and a 29.5% enhanced throughput capacity than static allocation techniques. the cost efficiency rose 31.7% while service reliability maintained 99.4% during the period. A proposed adaptable-evolutionary framework provides an effective solution that leads to improved performance measurements of large-scale cloud programs while reducing operational expenses for transitioning between dynamic computing settings.

关键词： Performance evaluation Cloud computing Machine learning Evolutionary computation Predictive models throughput Real-time systems Resource management Reliability Optimization

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Online Resource Allocation in Edge computing Using distributed Bidding Approaches 18

Online Resource Allocation in Edge Computing Using Distribut...

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18th ieee international conference on Mobile Ad hoc and Smart systems (ieee MASS)

作者： Rublein, Caroline Mehmeti, Fidan Towers, Mark Stein, Sebastian La Porta, thomas F. Penn State Univ University Pk PA 16802 USA Univ Southampton Southampton Hants England

ISBN: (纸本)9781665449359

Edge computing has become a very popular service that enables mobile devices to run complex tasks with the help of network-based computing resources. However, edge clouds are often resource-constrained, which makes resource allocation a challenging issue. We focus on a distributed resource allocation method in which servers operate independently and do not communicate with each other, but interact with clients (tasks) to make allocation decisions. this provides robustness and does not require service providers to share information about their configurations or workloads. We propose a two-round bidding approach of assigning tasks to edge cloud servers, while taking into account various processing requirements and server constraints. We consider cases in which all jobs have equal utility, cases where jobs have different utilities but users do not disclose these utilities to servers, and cases where users disclose the utility of their jobs to servers. We evaluate the performance using extensive realistic simulations. Results show that our approach is very close to an optimal assignment, with discrepancy not exceeding 5%.

关键词： Edge cloud computing Optimization Bidding

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Energy-Efficient Stable Election Protocol for IoT-Based Healthcare systems Using Wireless sensor Networks 14

Energy-Efficient Stable Election Protocol for IoT-Based Heal...

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14th international conference on computing Communication and Networking Technologies, ICCCNT 2023

作者： Pahuja, Monika Kumar, Dinesh Maharaja Ranjit Singh Punjab Technical University Dept. of Computer Science and Engineering Punjab Bathinda India

ISBN: (纸本)9798350335095

IoT integrated with WSN has become a pivotal force in healthcare, embodying a multitude of transformative applications. A protocol for analyzing data in the context of healthcare utilization is one definition of it, wherein a WSN must offer more dependable routing. As a result, there is a requirement to improve a technique in the healthcare industry that optimizes communication rates and increases dependability. this article presents a new approach for the purpose of routing data packets (DPs) to enhance the dependability of IoT-based WSNs for the Healthcare System (HCS). the study methodology takes into account the behaviour of HCSs as well as the significance of energy consumption (EC), packet delivery rate (PDR), and end-to-end delay (E2D). To accomplish the routing procedure, the research methodology incorporates several situations, such as residual energy (RE) and distance (d) from neighbours. the outcomes of designing the proposed Energy-Efficient Stable Election Protocol for IoT-based WSN in Healthcare systems (EESBOP) protocol demonstrate its favourable performance compared to the I-SEP (Improved Stable Election Protocol) protocol. Additionally, the protocol is effective in achieving its goals of preserving the high quality of DPs that are delivered to the destination and maximizing the efficiency of EC within the HCS. the results of the experiments show that the study protocol beats both the EESBOP and I-SEP protocols. As a result, the throughput of the network is improved by 4%, and the rate at which packets are delivered is increased by 98.9%. © 2023 ieee.

关键词： Energy utilization

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Research on Ship Remote Monitoring and Intelligent Decision-making System Supported by 5G Communication

Research on Ship Remote Monitoring and Intelligent Decision-...

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ieee international conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Shufei Qi Wenyi Sun Yonggang Zong Ocean Department Binzhou Polytechnic Binzhou China

ISBN: (数字)9798350389418

ISBN: (纸本)9798350389425

this paper proposes a remote monitoring and decision-making system for intelligent ships based on edge computing and distributed algorithms. Relying on the high bandwidth and low latency characteristics of 5 G communication, real-time data processing and remote monitoring of ship operation status are realized. the system localizes a large amount of sensor data through edge computing, and combines distributed algorithms to improve data fusion and decisionmaking efficiency. Data transmission supported by 5G communication provides technical guarantee for seamless connection between ships and shore-based monitoring centers. through real-time analysis of ship sensor data, the system can predict potential faults and optimize navigation strategies. Model simulation results show that the distributed algorithm based on edge computing has significant advantages in improving data processing speed, reducing decision response time by 15% and improving monitoring accuracy by 8.5%. this study provides technical support for remote monitoring and autonomous decision-making of intelligent ships, and verifies the broad application prospects of $\mathbf{5 G}$ communication in the field of maritime communications.

关键词： Navigation Decision making distributed databases Real-time systems Safety Data communication Marine vehicles distributed algorithms Remote monitoring Edge computing

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Situation theory Based Query Generation for Determining Situation Awareness Across distributed Data Streams

Situation Theory Based Query Generation for Determining Situ...

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ieee international conference on Human-Machine systems

作者： Lesong Jia Anfeng Peng Huao Li Xuehang Guo Michael Lewis School of Computing and Information University of Pittsburgh Pittsburgh PA

ISBN: (数字)9798350315790

ISBN: (纸本)9798350315806

While conventional measures of Situation Awareness (SA) focus on its adequacy in supporting decisions, fully exploiting information being returned by teams of unmanned aerial vehicles (UAVs) requires close attention to the sources as well as the impact of information. the problem of measuring SA for UAV teams lies in determining the extent to which information is being integrated from across the team. To address this problem, we are developing a Situation theory based method for spatially and temporally indexing relevant situations. Observations from each UAV are treated as ‘infons’ indexed by their particular time and place. By maintaining provenance on individual observations, we can trace their participation in supporting operator SA and use these data to evaluate the effects of alternative data presentations for multi-UAV surveillance. A wildfire monitoring application domain is introduced, and an example developed from a wildfire training scenario for Great Sand Dunes National Park.

关键词： Training Wildfires Surveillance Human-machine systems distributed databases Autonomous aerial vehicles Encoding

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Cost Sensitive based Support Vector Machine for Energy Efficient Clustering and Routing

Cost Sensitive based Support Vector Machine for Energy Effic...

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distributed computing and Electrical Circuits and Electronics (ICDCECE), ieee international conference on

作者： Vijaya Bhaskar Reddy Muvva Mohammed I. Habelalmateen V Shridhar Pradeep V Manohar M Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Shinas Sultanate of Oman Department of Computer Technical Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India Department of Information Science and Engineering Alva's Institute of Engineering and Technology Mangalore India Department of Computer Science and Engineering CHRIST (Deemed to be University) Bangalore India

ISBN: (数字)9798331533663

ISBN: (纸本)9798331533670

Wireless sensor Networks (WSNs) are ideal for applications requiring rapid deployment, as they operate without the need for a pre-existing network infrastructure. WSNs have constrained capacity to manage large volumes of data, and processing, transmitting as well as receiving this data consumes substantial energy. On account of their constrained power usage and bandwidth, sensors are unable to transmit each gathered information to a Base Station (BS) or sink for analysis. thus, this research proposes the Cost Sensitive based Support Vector Machine (CS-SVM) approach for the energy efficient clustering and routing. the proposed approach minimizes an energy consumption at data transmission and clustering, extending network lifetime through effectively selects CHs according to energy levels as well as node distribution. the CH selection considers the three important fitness functions such as distance from sink to CH, distance from CH to sensor nodes and residual energy. then, the routing considers the two important fitness functions. the various performance indices are considered to validate the effectiveness of proposed method. the simulation outcomes proven that the proposed CS-SVM approach attains the better energy consumption of 8.32J as compared to the previous approach named distributed Energy-efficient two-hop-based Clustering and Routing (DECR).

关键词： Support vector machines Wireless sensor networks Energy consumption Costs Routing Energy efficiency Energy states Magnetic heads sensors Data communication

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