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A Synchronized Test Control Execution Model of distributed Systems

international JOURNAL OF grid AND HIGH PERFORMANCE computing 2020年第1期12卷 1-17页

作者： Azzouzi, Salma Hsaini, Sara Charaf, My El Hassan IBN TOFAIL Univ Lab Informat Syst & Optimizat ISO LAB Kenitra Morocco IBN TOFAIL Univ Lab Informat Syst & Optimizat ISO LAB Fac Sci Kenitra Morocco

Conformance testing may be seen as mean to execute an IUT (implementation under test) by carrying out test cases in order to observe whether the behavior of the IUT is conforming to its specifications. However, the development of distributed testing frameworks is more complex and the implementation of the parallel testing components (PTCs) should take into consideration the mechanisms and functions required to support interaction during PTC communication. In this article, the authors present another way to control the test execution of PTCs by introducing synchronization messages into the local test sequences. Then, they suggest an agent-based simulation to implement synchronized local test sequences and resolve the problem of control and synchronization.

关键词： Controllability Coordination distributed Testing Observability Synchronization

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Single-Phase Ground Fault Line Selection Based on RTDS Simulation for Network with New Energy Accessed

Single-Phase Ground Fault Line Selection Based on RTDS Simul...

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international conference on Cyber Security Intelligence and Analytics, CSIA 2021

作者： Deng, Tian Sun, Shuo Chen, Shijun State Grid Xuzhou Power Supply Company Xuzhou Jiangsu China School of Electrical and Power Engineering China University of Mining and Technology Xuzhou Jiangsu China

ISBN: (纸本)9783030699987

Based on the features of zero-sequence components when single-phase line in the distribution network connected with new energy grounding, including parallel lines, a line selection method in view of the sum of vectors about the zero-sequence current at both ends is proposed in this paper. Firstly, using the zero-sequence current measured at the initial end of each line, the current with the largest amplitude and negative direction is identified as the uncertain current. If the uncertain current is in an independent line, it is the faulty line. If the suspected faulty line is a line group containing parallel lines, then the sum of vector about the zero-sequence current at the both ends in the line group is further calculated. The line which has the largest magnitude of the zero-sequence current vector sum at both ends and have negative direction is the faulty line in the parallel line group. The RTDS simulation verifies that this method can effectively conquer the influence of unbalanced current, make line selection more accurate, and improve the safety and dependability of the distribution network. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Vectors

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parallel Deployment of VNFs in Service Function Chain: Benefit or Not?

Parallel Deployment of VNFs in Service Function Chain: Benef...

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IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Kaiwen Ning Hao Wang Zhiheng Zhang Zhou Xu Xiaowei Shu School of Software Engineering Dalian University of Technology China

Network Function Virtualization (NFV) technology facilitates flexible and fast service provisioning by deploying network functions in wished positions and chaining order as Service Function Chain (SFC). Empirically, if the processing inside some Virtual Network Functions (VNFs) does not relate to each other, parallel chaining them can further improve the performance, such as reducing the end-to-end hops of SFCs. However, it is often ignored that parallel deploy VNFs will also introduce additional VNFs to replicate, distribute, and merge data. This will add hops and increase resource consumption. Will parallel deployment of VNFs in SFCs necessarily bring benefits? Regarding multiple parallel forms of an SFC, which one is the best? Further, how does the service process of the NFV network affect the parallel decisions of VNFs? In this paper, we design an NFV orchestrator, DP-NFVO, to maximize the revenue of NFV Service Providers and provide quantitative insights into the impact of parallel VNFs deploy-ment. Precisely, we first refine existing VNF parallelism rules and discuss the impact of VNF parallelism on latency and resource consumption, and analyze the optimal form of parallelism for SFCs. Second, we decompose the service request process in NFV networks into multiple stages and provide a joint model of VNF parallelism and deployment. Further, we design a VNF online deployment and parallelism decision policy for DP-NFVO based on Proximal Policy Optimization (PPO) to maximize revenue. Finally, we demonstrate the effectiveness and adaptability of DP-NFVO on parallel processing and the requests service process with extensive experiments.

关键词： Adaptation models Service function chaining parallel processing Network function virtualization Delays Optimization

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Load Balance Awared Data Sharing Systems In Heterogeneous Edge Environment 26

Load Balance Awared Data Sharing Systems In Heterogeneous Ed...

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26th IEEE international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Chen, Sheng Chen, Zheng Gu, Siyuan Chen, Baochao Xie, Junjie Guo, Deke Tianjin Univ Colledge Intelligence & Comp Tianjin Peoples R China Natl Univ Def Technol Sci & Technol Informat Syst Engn Lab Changsha Hunan Peoples R China PLA Inst Syst Engn AMS Beijing Peoples R China

ISBN: (纸本)9781728190747

Edge computing has become the de facto method for delay-sensitive applications, in which the computation and storage resources are placed at the edge of network. The main responsibility of edge computing is to carry data from the Cloud downlinks and terminal uplinks, and organize these data well on the edge side. This is the basis for subsequent analysis and processing of data. Therefore, this brings about a question as to how those data should be organized on the edge and how to store and retrieve them. In response to this demand, some methods have been proposed to solve the related problems of how to build data storage and retrieval services on the edge side. Those methods propose three different solutions: structured, unstructured, and hybrid schemes. However, the data storage and retrieval services for the heterogeneous edge environment is still lack of research. It is still not considered an important design test load balancing when the data is stored on the edge side. In this paper, we design and implement w-strategy, a load balance approach that implements the appropriate load balance among the heterogeneous edge nodes by using the weighted Voronoi diagram. Our solution utilizes the software defined networking paradigm to support a virtual-space based distributed hash tables (DHTs) to distribute data. Evaluation results show that w-strategy achieves better load balancing among the heterogeneous edge nodes compared to the existing methods, GRED and Chord. And, the w-strategy improves the average underutilization of the resources by 20%.

关键词： weighted Voronoi SDN load balance edge computing

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Restructured LFC Scheme with Renewables and EV Penetration using Novel QOEA Optimized parallel Fuzzy I-PID Controller 7th

Restructured LFC Scheme with Renewables and EV Penetration u...

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7th international conference on Advances in Control and Optimization of Dynamical Systems (ACODS)

作者： Aryan, Pulakraj Raja, G. Lloyds Natl Inst Technol Dept Elect Engn Patna Bihar India

An effective controller configuration improves the action of the load frequency control (LFC) mechanism. In the present work, a novel parallel fuzzy integral - proportional-integral-derivative (FI-PID) controller is suggested for a two-area power system in the deregulated environment. The controller gains are optimized using novel quasi-oppositional equilibrium algorithm (QOEA). The proposed control scheme has been subjected to step and random load disturbances. Moreover, the suggested scheme is also compared with different prevalent controllers and optimizing techniques. EV and the distributed generation (DG) act as energy storing elements and improve system transients during peak demands. Hence, the integration of electric vehicle into the grid and its impact on frequency regulation is also studied. Simulation results establish the efficacy of the suggested controller over prevailing ones.

关键词： Load frequency control electric vehicle optimization fuzzy proportional-integral-derivative (PID)

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4th EAI international conference on Advanced Hybrid Information Processing, ADHIP 2020

4th EAI International Conference on Advanced Hybrid Informat...

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4th EAI international conference on Advanced Hybrid Information Processing, ADHIP 2020

ISBN: (纸本)9783030678739

The proceedings contain 43 papers. The special focus in this conference is on Advanced Hybrid Information Processing. The topics include: Network Dynamic Bad Information Security Filtering Algorithms Based on Large Data Analysis;analysis of Intelligent Monitoring Model of Network Security Situation Based on grid Power Flow;online Monitoring Method for Hazard Source of Power System Network Based on Mobile Internet;an Algorithm of Intelligent Classification For Rotating Mechanical Failure Based on Optimized Support Vector Machine;research on Anti-point Source Jamming Method of Airborne Radar Based on Artificial Intelligence;statistical Analysis of Catalytic Removal of Soot Particles Based on Big Data;research on Electric Drive Control Method Based on parallel computing;community Discovery Algorithm Based on parallel Recommendation in Cloud computing;Deployment Optimization of Perception Layer Nodes in the Internet of Things Based on NB-IoT Technology;research on Intelligent Investment Prediction Model of Building Based on Support Vector Machine;analysis of Energy Saving Method for Multiple Relay Nodes in Wireless Volume Domain Network;study on Probability Statistics of Unbalanced Cloud Load Scheduling;intelligent Authentication Method for Trusted Access of Mobile Nodes in Internet of Things Driven by Cloud Trust;Research on Dynamic Integration of Multi-objective Data in UI Color Interface;the Application of Visualization of Internet of Things in Online Teaching of Mobile Interactive Interface Optimization;Research on Feature Extraction Method of UAV Video Image Based on Target Tracking;automatic Recognition of Tea Bud Image Based on Support Vector Machine;automatic Color Image Segmentation Based on Visual Characteristics in Cloud computing.

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Analysis of electricity service evaluation based on multi-mode heterogeneous data fusion

Analysis of electricity service evaluation based on multi-mo...

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IEEE international Symposium on Information (IT) in Medicine and Education, ITME

作者： Wenjing Li Nan Zhang Qing Liu Shiqian Ma Wenjing Guo Chuanjiang Wang Zhipeng Yang State Grid Information & Telecommunication Co. Ltd. Beijing China State Grid Tianjin Electric Power Company Tianjin China

The electricity Internet of Things (IoT) generates a large amount of heterogeneous data under the edge cloud topology. The rational use of the heterogeneous data of the electricity Internet of Things can effectively improve the benefits of electricity enterprises. User service evaluation is a key indicator reflecting the good or bad service quality of the enterprise, and accurate identification of user sentiment is an important reference for subsequent service adjustment of the enterprise. In this paper, a distributed cloud computing-based data collection framework is proposed, which has the advantages of low cost and fast collection, and provides a physical basis for effective integration of multi-source heterogeneous data resources. In addition, this paper also proposes an emotion recognition method based on user evaluation of audio and text multimodal data fusion, constructs BiLSTM-Transformer and CNN-BiLSTM models for text and audio emotion analysis respectively, then uses self-assignment fusion strategy to realize decision fusion and verifies its efficient performance on the dataset.

关键词： Emotion recognition Cloud computing Analytical models Biological system modeling Data integration Data collection Data models

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25th international European conference on parallel and distributed computing, Euro-Par 2019

25th International European Conference on Parallel and Distr...

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25th international European conference on parallel and distributed computing, Euro-Par 2019

ISBN: (纸本)9783030293994

The proceedings contain 36 papers. The special focus in this conference is on parallel and distributed computing. The topics include: Toggle: Contention-Aware Task Scheduler for Concurrent Hierarchical Operations;load-Balancing for parallel Delaunay Triangulations;design-Space Exploration with Multi-Objective Resource-Aware Modulo Scheduling;implementing YewPar: A Framework for parallel Tree Search;PLB-HAC: Dynamic Load-Balancing for Heterogeneous Accelerator Clusters;Enhancing the Programmability and Performance Portability of GPU Tensor Operations;unified and Scalable Incremental Recommenders with Consumed Item Packs;Declarative Big Data Analysis for High-Energy Physics: TOTEM Use Case;clustering as Approximation Method to Optimize Hydrological Simulations;accelerating Data-Dependence Profiling with Static Hints;YOLO: Speeding Up VM and Docker Boot Time by Reducing I/O Operations;celerity: High-Level C++ for Accelerator Clusters;dataflow Execution of Hierarchically Tiled Arrays;Scalable FIFO Channels for Programming via Communicating Sequential Processes;TWA – Ticket Locks Augmented with a Waiting Array;enabling Resilience in Asynchronous Many-Task Programming Models;avoiding Scalability Collapse by Restricting Concurrency;Graph Coloring Using GPUs;featherlight Speculative Task parallelism;one Table to Count Them All: parallel Frequency Estimation on Single-Board Computers;multi-valued Expression Analysis for Collective Checking;Fine-Grained MPI+OpenMP Plasma Simulations: Communication Overlap with Dependent Tasks;parallel Adaptive Sampling with Almost No Synchronization;parallel Streaming Random Sampling;Cholesky and Gram-Schmidt Orthogonalization for Tall-and-Skinny QR Factorizations on Graphics Processors;automatic Exploration of Reduced Floating-Point Representations in Iterative Methods;Linear Systems Solvers for distributed-Memory Machines with GPU Accelerators;Radio-Astronomical Imaging: FPGAs vs GPUs;Towards Portable Online Prediction of Network Utilizatio

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SrSpark: Skew-resilient Spark based on Adaptive parallel Processing 26

SrSpark: Skew-resilient Spark based on Adaptive Parallel Pro...

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26th IEEE international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Shen, Yijie Xiong, Jin Jiang, Dejun Chinese Acad Sci Inst Comp Technol SKL Comp Architecture Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781728190747

MapReduce-based SQL processing systems, e.g., Hive and Spark SQL, are widely used for big data analytic applications due to automatic parallel processing on large-scale machines. They provide high processing performance when loads are balanced across the machines. However, skew loads are not rare in real applications. Although many efforts have been made to address the skew issue in MapReduce-based systems, they can neither fully exploit all available computing resources nor handle skews in SQL processing. Moreover, none of them can expedite the processing of skew partitions in case of failures. In this paper, we present SrSpark, a MapReduce-based SQL processing system that can make full use of all computing resources for both non-skew loads and skew loads. To achieve this goal, SrSpark introduces fine-grained processing and work-stealing into the MapReduce framework. More specifically, SrSpark is implemented based on Spark SQL. In SrSpark, partitions are further divided into sub-partitions and processed in sub-partition granularity. Moreover, SrSpark adaptively uses both intra-node and inter-node parallel processing for skew loads according to available computing resources in real-time. Such adaptive parallel processing increases the degree of parallelism and reduces the interaction overheads among the cooperative worker threads. In addition, SrSpark checkpoints sub-partition's processing results periodically to ensure fast recovery from failures during skew partition processing. Our experiment results show that for skew loads, SrSpark outperforms Spark SQL by up to 3.5x, and 2.2x on average, while the performance overhead is only about 4% under non-skew loads.

关键词： MapReduce-based SQL engine Skew handling Adaptive processing

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Windsurfing with APPA: Automating Computational Fluid Dynamics Simulations of Wind Flow using Cloud computing 28

Windsurfing with APPA: Automating Computational Fluid Dynami...

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28th Euromicro international conference on parallel, distributed and Network-Based Processing (PDP)

作者： Jindal, Anshul Strahm, Benedikt Podolskiy, Vladimir Gerndt, Michael Tech Univ Munich Chair Comp Architecture & Parallel Syst Garching Germany

ISBN: (纸本)9781728165820

Computational fluid dynamics (CM) can serve as a complementary approach to conventional wind tunnel testing to assess the wind flow around tall buildings. Being a clear High Performance computing (HPC) task, CM simulations conventionally run on supercomputers and compute clusters using specialized software such as OpenFOAM. The limited availability and high maintenance costs of supercomputers and clusters force small and medium companies to search for the cost-efficient infrastructure to conduct their simulations with the appropriate performance. The on-demand offer of compute capacity by cloud service providers are well suited this task. However, engineers and researchers require extensive expertise and experience in working with cloud computing in order to benefit from running CFD simulations on a cloud. The contribution of the paper to the outlined problem is two-fold: 1) a unique Automated parallel Processing Application (APPA) tool that hides the cloud management details from the wind engineer and provides an intuitive user interface;2) the estimation of the optimal number of cores (vCPUs) for virtual machine instances provided by AWS and Google Cloud based on average run time and total cost metrics for a given number of cells of a CM-simulation. nl-highcpu-96 Google Cloud VM met both goals: low cost and low runtime per timestep. For the number of vCPUs below 16, the *** AWS VM type has the least nmtime per timestep in all the cases. Google Cloud instances with high vCPUs are recommended to run the simulations if budget is a big concern.

关键词： cloud computing wind flow simulation computational fluid dynamics domain-specific performance analysis OpenFOAM Google Cloud AWS containers Docker

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