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International Symposium on parallel and distributed Processing with Applications, ISPA

作者： Kunpeng Li Lei Wang Hongjun Ren Yangjie Cao School of Cyber Science and Engineering Zhengzhou University Zhengzhou China Hanwei Electronics GroupCorporation Zhengzhou China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

The main idea of Multi-Object tracking is to accurately identify and track the position and motion status of multiple objects in a video sequence in real time. The current mainstream tracking algorithm is to associate the detection boxes with the trajectory in a comprehensive and violent way, as a way to accurately determine and maintain the unique identity mark of the moving object. However, implementing a unified association process for detection boxes with different confidence levels, this suffers from non-negligible low information utilization, long association time, and high resource consumption. To solve this problem, we propose a faster, simple and effective association algorithm ADAPT, dividing the queue of detection boxes and trajectories by confidence level to achieve adaptive association of detection boxes and trajectories in the queue, so as to realize tracking, shorten the association time, and improve tracking effect. When applied to six different trackers, our method achieved significant improvements in both MOTA and IDF1 scores. In order to improve the MOT performance, we designed a simple and powerful tracker, AdaptTrack, and evaluated it on 3090GPU for VisDrone-MOT datasets, achieving 41.3 MOTA, 53.6 IDF1, and 42.9 HOTA. AdaptTrack on UAVDT datasets also shows the same excellent results of 69.8 MOTA, 78.9 IDF1, 66.3 HOTA, and achieves a tracking speed of 18.2 FPS.

关键词： distributed processing Correlation Accuracy Video sequences Robustness real-time systems Trajectory Object tracking Object recognition

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An On-Line Sensor Fault Detection System for an AC Microgrid Secondary Control Based on a Sliding Mode Observer Model

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ENERGIES 2024年第15期17卷 3808页

作者： Bravo, John Ortiz, Leony Garcia, Edwin Ruiz, Milton Aguila, Alexander Univ Cent Ecuador Fac Engn Min Petr & Environm Geol Quito 170129 Ecuador Salesian Polytech Univ Elect Engn Dept Smart Grid Res Grp GIREI Quito 170702 Ecuador

The current study proposes a strategy for sensing fault detection in the secondary control of an isolated Microgrid based on a high-order Sliding Mode Robust Observers design. The proposed strategy's main objective is to support future diagnostic and fault tolerance systems in handling these extreme situations. The proposal is based on a generation system and a waste management system. Four test scenarios were generated in a typical Microgrid to validate the designed strategy, including two Battery Energy Storage systems in parallel, linear, and non-linear loads. The scenarios included normal grid operation and three types of sensing faults (abrupt, incipient, and random) directly affecting the secondary control of a hierarchical control strategy. The results showed that the proposed strategy could provide a real-time decision for detection and reduce the occurrence of false alarms in this process. The effectiveness of the fault detection strategy was verified and tested by digital simulation in Matlab/Simulink R2023b.

关键词： battery energy storage systems distributed generation microgrids secondary control sensing fault detection sliding mode observers

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Finding the Signal: Near real-time Data Analysis for Urban Traffic Monitoring on a distributed Bluetooth Sensor Network 18

Finding the Signal: Near Real-time Data Analysis for Urban T...

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IEEE 18th International Conference on E-Science (E-Science)

作者： Sichani, Mohsen Arnold, Richard Bubendorfer, Kris Victoria Univ Wellington Sch Engn & Comp Sci Wellington New Zealand Victoria Univ Wellington Sch Math & Stat Wellington New Zealand

ISBN: (数字)9781665461245

ISBN: (纸本)9781665461245

The development of pervasive personal digital devices such as phones, watches, and headphones, interconnected by technologies such as Bluetooth, has led to a disruptive change in the ways in which local governments can monitor both vehicular and pedestrian traffic flows within their cities. In modern vehicles, navigation systems interconnect the personal devices of drivers and passengers typically via Bluetooth. By continuously monitoring such devices when they are in discover mode, traffic flows can be estimated almost in real-time. This paper examines traffic data collected from a Bluetooth Traffic Monitoring systems installed by the Wellington City Council. Potentially such an installation could assist a local authority in real-time monitoring of normal traffic, as well as events including concerts and sport events, or in reaction to unanticipated events such as disasters. The limitation in this technology is that the data collected is of low fidelity, that is: not every vehicle has a detectable device, some have many, and there are devices carried by pedestrians and non-motor vehicles as well as stationary devices. This paper enumerates and investigates these challenges through statistical modelling, cleaning and data analysis. We present two novel algorithms for the processing of Bluetooth traffic data and validate our algorithms against a physical road counter. A case study is of a major earthquake is then presented as a proof of concept. The earthquake led to road closures, building collapse and other infrastructure damage and we examine three weeks of BTMS data and visualise how this earthquake impacted daily traffic flows.

关键词： Bluetooth Local government Roads Earthquakes Urban areas Data visualization Traffic control

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Modeling and Verification of Asynchronous systems Using timed Integrated Model of distributed systems

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SENSORS 2022年第3期22卷 1157-1157页

作者： Daszczuk, Wiktor B. Warsaw Univ Technol Inst Comp Sci Nowowiejska Str 15-19 PL-00665 Warsaw Poland

In modern computer systems, distributed systems play an increasingly important role, and modeling and verification are crucial in their development. The specificity of many systems requires taking this into account in real time, as time dependencies significantly affect the system's behavior, when achieving the goals of its processes or with adverse phenomena such as deadlocks. The natural features of distributed systems include the asynchrony of actions and communication, the autonomy of nodes, and the locality of behavior, i.e., independence from any global or non-local features. Most modeling formalisms are derived from parallel centralized systems, in which the behavior of components depends on the global state or the simultaneous achievement of certain states by components. This approach is unrealistic for distributed systems. This article presents the formalism of a timed integrated model of distributed systems that supports all of the mentioned features. The formalism is based on the relation between the states of the distributed nodes and the messages of distributed computations, called agents. This relation creates system actions. A specification in this formalism can be translated into timed automata, the most popular formalism for specifying and verifying timed parallel systems. The translation rules ensure that the semantics of T-IMDS and timed automata are consistent, allowing use of the Uppaal validator for system verification. The development of general formulas for checking the deadlock freedom and termination efficiency allows for automated verification, without learning temporal logics and time-dependent formulas. An important and rare feature is the finding of partial deadlocks, because in a distributed system a common situation occurs in which some nodes/processes are deadlocked, while others work. Examples of checking timed distributed systems are included.

关键词： timed distributed systems distributed system timed specification deadlock detection distributed termination model checking timed automata

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11th Mining Humanistic Data workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st workshop/Special Session on Machine Learning and Big Data in Health Care, ML@HC 2022 and 2nd workshop on Artificial Intelligence in Biomedical Engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022

11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putt...

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11th Mining Humanistic Data workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st workshop/Special Session on Machine Learning and Big Data in Health Care, ML@HC 2022 and 2nd workshop on Artificial Intelligence in Biomedical Engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022

ISBN: (纸本)9783031083402

The proceedings contain 35 papers. The special focus in this conference is on Mining Humanistic Data. The topics include: Digitally Assisted Planning and Monitoring of Supportive Recommendations in Cancer Patients;CAIPI in Practice: Towards Explainable Interactive Medical Image Classification;a Deep Q Network-Based Multi-connectivity Algorithm for Heterogeneous 4G/5G Cellular systems;simulating Blockchain Consensus Protocols in Julia: Proof of Work vs Proof of Stake;Maximum Likelihood Estimators on MCMC Sampling Algorithms for Decision Making;employing Natural Language Processing Techniques for Online Job Vacancies Classification;Probabilistic Quantile Multi-step Forecasting of Energy Market Prices: A UK Case Study;proactive Buildings: A Prescriptive Maintenance Approach;performance Meta-analysis for Big-Data Univariate Auto-Imputation in the Building Sector;non-intrusive Diagnostics for Legacy Heat-Pump Performance Degradation;a 5G-Based Architecture for Localization Accuracy;anomaly Detection in Small-Scale Industrial and Household Appliances;an Innovative Software Platform for Efficient Energy, Environmental and Cost Planning in Buildings Retrofitting;deep Learning-Based Segmentation of the Atherosclerotic Carotid Plaque in Ultrasonic Images;An Intelligent Grammar-Based Platform for RNA H-type Pseudoknot Prediction;An Automated 2D U-Net Segmentation Method for the Identification of Cancer Brain Metastases Using MRI Images;The Use of Robotics in Critical Use Cases: The 5G-ERA Project Solution;fundamental Features of the Smart5Grid Platform Towards realizing 5G Implementation;experimentation Scenarios for Machine Learning-Based Resource Management;efficient Data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases;5G for the Support of Smart Power Grids: Millisecond Level Precise distributed Generation Monitoring and real-time Wide Area Monitoring;monitoring Neurological Disorder Patients via Deep Learning Based Facial Expressions An

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Performance Improvements of parallel Applications thanks to MPI-4.0 Hints 34

Performance Improvements of Parallel Applications thanks to ...

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34th IEEE International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)

作者： Moraru, Maxim Roussel, Adrien Taboada, Hugo Jaillet, Christophe Perache, Marc Krajecki, Michael Univ Reims LICIIS F-51097 Reims France CEA DAM DIF LRC DIGIT F-91297 Arpajon France Univ Paris Saclay CEA Lab Informat Haute Peiformance Calcul & Simulat Bruyeres Le Chatel France CEA DAM DIF F-91297 Arpajon France Univ Reims LRC DIGIT LICIIS F-51097 Reims France

ISBN: (数字)9781665451550

ISBN: (纸本)9781665451550

HPC systems have experienced significant growth over the past years, with modern machines having hundreds of thousands of nodes. Message Passing Interface (MPI) is the de facto standard for distributed computing on these architectures. On the MPI critical path, the message-matching process is one of the most time-consuming operations. In this process, searching for a specific request in a message queue represents a significant part of the communication latency. So far, no miracle algorithm performs well in all cases. This paper explores potential matching specializations thanks to hints introduced in the latest MPI 4.0 standard. We propose a hash-table-based algorithm that performs constant time message-matching for no wildcard requests. This approach is suitable for intensive point-to-point communication phases in many applications (more than 50% of CORAL benchmarks). We demonstrate that our approach can improve the overall execution time of real HPC applications by up to 25%. Also, we analyze the limitations of our method and propose a strategy for identifying the most suitable algorithm for a given application. Indeed, we apply machine learning techniques for classifying applications depending on their message pattern characteristics.

关键词： HPC distributed programming MPI Matching MPI 4.0 Sessions

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Performance Models of Data parallel DAG Workflows for Large Scale Data Analytics 37

Performance Models of Data Parallel DAG Workflows for Large ...

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37th IEEE International Conference on Data Engineering (IEEE ICDE)

作者： Shi, Juwei Lu, Jiaheng Microsoft Cooperat STCA Redmond WA 98052 USA Univ Helsinki Dept Comp Sci Helsinki Finland

ISBN: (纸本)9781665448901

Directed Acyclic Graph (DAG) workflows are widely used for large-scale data analytics in cluster-based distributed computing systems. Building an accurate performance model for a DAG on data-parallel frameworks (e.g., MapReduce) is critical to implement autonomic self-management big data systems. An accurate performance model is challenging because the allocation of pre-emptable system resources among parallel jobs may dynamically vary during execution. This resource allocation variation during execution makes it difficult to accurately estimate the execution time. In this paper, we tackle this challenge by proposing a new cost model, called Bottleneck Oriented Estimation (BOE), to estimate the allocation of preemptable resources by identifying the bottleneck to accurately predict task execution time. For a DAG workflow, we propose a state-based approach to iteratively use the resource allocation property among stages to estimate the overall execution plan. Extensive experiments were performed to validate these cost models with HiBench and TPC-H workloads. The BOE model outperforms the state-of-the-art models by a factor of five for task execution time estimation.

关键词： Data Analytics

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Monitoring and Mitigating Climate-Induced Natural Disasters with Cloud IoT

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JOURNAL OF CLIMATE CHANGE 2024年第1期10卷 61-66页

作者： Taneja, Harsh Verma, Rohan Singh, Prabh Deep Singh, Kiran Deep Graphic Era Dehra Dun India Chitkara Univ Inst Engn & Technol Chandigarh Punjab India

Innovative solutions are necessary for efficient monitoring and mitigation techniques as climate change increases the frequency and severity of natural catastrophes. In this study, we investigate how Cloud Internet of Things (IoT) might help mitigate climate-related calamities. Through the use of cloud computing and sensor networks, Cloud IoT facilitates the capture, processing, and distribution of data in near-real time. This strategy promotes catastrophe planning, response, and recovery by offering early warnings, predictive insights, and simplified communication. The article emphasises the cumulative influence of Cloud IoT components such as sensor networks, data analytics, decision support systems, and remote control in the context of disaster management. Cloud IoT is useful in real-world scenarios, such as the tracking of floods in Bangladesh and the identification of wildfires in California. These cases show how the technology may prevent injuries and preserve property through early warnings and well-coordinated responses. Despite its potential, it faces obstacles including ensuring the safety of data and dealing with issues related to the necessary infrastructure. In conclusion, including Cloud IoT in disaster management provides a cost-effective, scalable, and efficient solution, greatly contributing to constructing resilient communities and creating a sustainable future in the face of climate-induced natural catastrophes.

关键词： Big data distributed computing parallel processing Tuning parameters Java virtual machine Hadoop Yarn Hadoop distributed file system MapReduce

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EdgeBooster: Edge-Assisted real-time Image Segmentation for the Mobile Web in WoT

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IEEE INTERNET OF THINGS JOURNAL 2021年第9期8卷 7288-7302页

作者： Huang, Yakun Qiao, Xiuquan Ren, Pei Dustdar, Schahram Chen, Junliang Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Tech Univ Wien Distributed Syst Grp A-1040 Vienna Austria

Combining image segmentation with Web technology lays a good foundation for lightweight, cross-platform, and pervasive Web artificial intelligence applications, and further improves the capability of Web-of-Things (WoT) applications. However, no matter whether we use a Web real-time communication media server for advanced processing that views camera inputs as a video stream, or transfer continuous camera frames to the remote cloud for processing, we are unable to obtain a satisfactory real-time experience due to high resource consumption and unacceptable latency. In this article, we present EdgeBooster, a computational-efficient architecture that leverages a common edge server to minimize the communication costs, accelerates the camera frame segmentation, and guarantees an acceptable segmentation accuracy with the prior knowledge. EdgeBooster provides real-time segmentation by developing parallel technology that enables segmentation on slices of a camera frame and using presegmentation based on superpixels to accelerate the graph-based segmentation. It also introduces recent DNN-based segmentation results as the prior knowledge to improve the performance of the graph-based segmentation, especially in nonideal scenes, such as dark light and weak contrast. Finally, it creates a pure frontend segmentation that can provide continuous and stable services for mobile users in unstable networks, such as a weak network or with an unstable edge server. The experimental results show that EdgeBooster is able to achieve a considerable accuracy for the mobile Web, running at no less than 30 frames per second in real scenes.

关键词： Image segmentation Servers Image edge detection real-time systems Streaming media Cameras Media Edge computing image segmentation mobile Web Web-of-Things (WoT) applications

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distributed real-time optimal control of central air-conditioning systems

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ENERGY AND BUILDINGS 2022年第0期256卷 111756-111756页

作者： Asad, Hussain Syed Wan, Hang Kasun, Hewage Rehan, Sadiq Huang, Gongsheng Univ British Columbia Life Cycle Management Lab LCML Sch Engn Vancouver BC Canada City Univ Hong Kong Dept Architecture & Civil Engn Hong Kong Peoples R China

real-time optimal control (RtOpt) is an efficient tool to improve the energy efficiency of heating, ventilating and air-conditioning (HVAC) systems. RtOpt is always centralized and solved entirely in building energy management systems (BEMSs). However, centralized optimization is not be an efficient solution because real-time operation data in local loops need to be sent to the central computation unit in BEMS for optimization. This paper, therefore, proposes a distributed RtOpt scheme for typical centralized HVAC systems, which uses a dual decomposition mechanism to break the centralized problem into one mater problem and several sub-problems that can be solved in parallel and independently. The mater problem is converted to a simple mean value calculation using a projected sub-gradient method, thus distributing the computation load from the central computation unit into local computation units. Unlike available decomposition schemes in literature, the proposed method considered the functionality and spatial distribution of the major components of HVAC systems, which could enhance the physical meaning and facilitate the application of the decomposition scheme. The proposed distributed RtOpt scheme was tested in case studies, with numerical analysis being used to demonstrate its potential benefits. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Heating, ventilation, and air-conditioning system real-time optimal control distributed intelligence Computation efficiency Energy efficiency

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