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A Scalable Privacy Preserving distributed parallel Optimization for a Large-Scale Aggregation of Prosumers With Residential PV-Battery systems

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IEEE ACCESS 2020年 8卷 210950-210960页

作者： Dolatabadi, Mohammad Siano, Pierluigi Vali E Asr Univ Rafsanjan Dept Math Rafsanjan *** Iran Univ Salerno Dept Management & Innovat Syst I-84084 Fisciano Italy

A novel scalable and privacy-preserving distributed parallel optimization that allows the participation of large-scale aggregation of prosumers with residential PV-battery systems in the market for the ancillary service (ASM) is proposed in this paper. To consider both reserve capacity and energy, day-ahead and real-time stages in the ASM are considered. A method based on hybrid Variable Neighborhood Search (VNS) and distributed parallel optimization is designed for the day ahead and real-time optimization. Different distributed optimization methods are compared and designed and a new distributed optimization method based on Linear Programming (LP) is proposed that outperforms previous methods based on integer and Quadratic programming (QP). The proposed LP-based optimization can be easily coded up and implemented on microcontrollers and connected to a designed Internet of Things (IoT) based architecture. As confirmed by simulation results, carried out considering different realistic case studies, both day-ahead and real-time proposed optimization methods, by allocating the computational effort among local resources, are highly scalable and fulfil the privacy of prosumers.

关键词： Aggregator PV-battery systems battery energy storage systems up and down-regulation ancillary services market linear programming quadratic programming distributed optimization alternating direction method of multipliers (ADMM)

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SYNCHRONOUS HIGH-FREQUENCY distributed READOUT FOR EDGE PROCESSING AT THE FERMILAB MAIN INJECTOR AND RECYCLER

arXiv

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arXiv 2022年

作者： Berlioz Rivera, Jose Rene Austin, M.R. Arnold, J.M. Hazelwood, K.J. Hanlet, P. Ibrahim, M.A. Narayanan, A. Nicklaus, D.J. Praudhan, G. Saewert, A.L. Schupbach, B.A. Seiya, K. Thurman-Keup, R.M. Tran, N.V. Jang, J. Liu, H. Memik, S. Shi, R. Thieme, M. Ulusel, D. Fermi National Accelerator Laboratory BataviaIL United States Northwestern University EvanstonIL United States Northern Illinois University DeKalbIL United States

The Main Injector (MI) was commissioned using data acquisition systems developed for the Fermilab Main Ring in the 1980s. New VME-based instrumentation was commissioned in 2006 for beam loss monitors (BLM)[2], which provided a more systematic study of the machine and improved displays of routine operation. However, current projects are demanding more data and at a faster rate from this aging hardware. One such project, real-time Edge AI for distributed systems (READS), requires the high-frequency, low-latency collection of synchronized BLM readings from around the approximately two-mile accelerator complex. Significant work has been done to develop new hardware to monitor the VME backplane and broadcast BLM measurements over Ethernet, while not disrupting the existing operations-critical functions of the BLM system. This paper will detail the design, implementation, and testing of this parallel data pathway. © 2022, CC BY.

关键词： Data acquisition

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Guest Editorial Special Issue on parallel and distributed Processing for Computational Social systems

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2019年第1期6卷 176-177页

作者： Santos, Eunice E. Korah, John IIT Dept Comp Sci Chicago IL 60616 USA

Great strides have been made in computational methods for social systems. However, real-world modeling problems require novel computational techniques to support modeling and analyses with time and resource constraints. The emergence of parallel architectures, in the form of multicore/manycore processors, and distributed platforms, have led to the formulation of new approaches for large-scale information processing, modeling and simulation, and new tools for analysis. Due to the inherent interdisciplinary nature of the research in computational social systems, techniques that utilize parallel and distributed algorithms, systems, and methodologies continue to evolve in diverse disciplines. This special issue provides a platform to bring together these researchers to showcase innovative research in computational social systems that leverage the emerging trends in parallel and distributed processing, algorithms, computational modeling, and high-performance computing. The call for papers was issued in 2017, with the submission deadline of December 29, *** received a number of strong submissions. The papers went through a rigorous review process and six high-quality papers were selected. The special issue papers are distributed across multiple issues of the TRANSACTIONS, specifically the last two issues of 2018 and this issue. We provide brief descriptions of the papers below.

关键词： Special issues and sections parallel processing distributed processing Computational modeling Multicore processing Program processors Sociotechnical systems

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parallel and distributed processing of big data streams and scheduling algorithms

Parallel and distributed processing of big data streams and ...

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作者： Tantalaki, Nicoleta Aegean University

Worldwide streams of data are expanding continuously, resulting in an accelerating need to efficiently and timely handle these large amounts of data that arrive continuously. In-memory computing is used to meet performance related requirements like latency and throughput that are extremely important in Data Stream Processing (DSP) applications. Several different technologies have emerged specifically to address the challenges of processing high-volume, real-time data, exploiting on-the-fly computations. distributed Stream Processing systems (DSPSs) assign applications’ processing tasks to the available resources and route streaming data between them. Efficient scheduling of processing tasks can reduce application latencies and eliminate network congestions. However, the available in-built scheduling techniques of DSPSs are far from optimal. In this thesis, we need to solve the task scheduling problem which focuses on which tasks to be allocated on which resources, and controls the order of job execution. An overview of the available DSPSs is presented and a classification of the existing scheduling policies is provided. In this way, useful information about the matters to consider when designing an effective scheduling policy is revealed. Then, a general formulation of the task scheduling problem is presented and a matrix-based, linear scheme is provided. Differently from existing research efforts, that rarely consider memory utilization in their analysis, the derived scheme is performed in a memory-efficient and well-balanced manner. It takes advantage of pipelines to efficiently handle applications, where there is need for heavy communication (all-to-all) between tasks, assigned to pairs of components. The scheme proposed in this thesis is static. However, when it comes to streams of data, the input load usually fluctuates drastically over time. Dynamic schemes use run-time adaptations and task re-scheduling to handle possible changes in the cluster but this usual

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Faster parallel Core Maintenance Algorithms in Dynamic Graphs

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IEEE TRANSACTIONS ON parallel AND distributed systems 2020年第6期31卷 1287-1300页

作者： Hua, Qiang-Sheng Shi, Yuliang Yu, Dongxiao Jin, Hai Yu, Jiguo Cai, Zhipen Cheng, Xiuzhen Chen, Hanhua Huazhong Univ Sci & Technol Sch Comp Sci & Technol Natl Engn Res CtrKey Lab Cluster & Grid Comp Key Lab Serv Comp Technol & SystBig Data Technol Wuhan 430074 Peoples R China Shandong Univ Sch Comp Sci & Technol Qingdao 266237 Peoples R China Shandong Acad Sci Sch Comp Sci & Technol Jinan 250353 Shandong Peoples R China Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA

This article studies the core maintenance problem for dynamic graphs which requires to update each vertex's core number with the insertion/deletion of vertices/edges. Previous algorithms can either process one edge associated with a vertex in each iteration or can only process one superior edge associated with the vertex (an edge < u, v > is a superior edge of vertex u if v' core number is no less than u's core number) in each iteration. Thus for high superior-degree vertices (the vertices associated with many superior edges) insertions/deletions, previous algorithms become very inefficient. In this article, we discovered a new structure called joint edge set whose insertions/deletions make each vertex's core number change at most one. The joint edge set mainly contains all the superior edges associated with the high superior-degree vertices as long as these vertices are 3(+)-hop independent. Based on this discovery, faster parallel algorithms are devised to solve the core maintenance problems. In our algorithms, we can process all edges in the joint edge set in one iteration and thus can greatly increase the parallelism and reduce the processing time. The results of extensive experiments conducted on various types of real-world, temporal, and synthetic graphs illustrate that the proposed algorithms achieve good efficiency, stability and scalability. Specifically, the new algorithms can outperform the single-edge processing algorithms by up to four orders of magnitude. Compared with the matching based algorithm and the superior edge based algorithm, our algorithms show a significant speedup up to 60x in the processing time.

关键词： Graph analysis core maintenance problem parallel algorithm

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Concept of Energy Efficient ESP32 Chip for Industrial Wireless Sensor Network 24

Concept of Energy Efficient ESP32 Chip for Industrial Wirele...

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24th IEEE International Conference on Intelligent Engineering systems (INES)

作者： Gatial, Emil Balogh, Zoltan Hluchy, Ladislav Slovak Acad Sci Dept Parallel & Distributed Comp Inst Informat Bratislava Slovakia

ISBN: (纸本)9781728110592

This paper proposes a concept of low-cost industrial wireless sensor network integrating the power consumption efficient ESP32 chip. The main focus is given on best practices of various sensors integration into real-time Operating System (RTOS) of ESP32 devices. The work proposes an architecture for data collection, security and possibility of data analysis. Energy effectiveness is estimated for battery usage in different modes of the chip. The last part of this work presents the conclusions and guidelines for future work. Road map of a distributed modeling

关键词： Industrial Wireless Sensor Network power efficiency Message Queue Transport and Telemetry

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parallel simulation of stochastic reward nets using theatre 21

Parallel simulation of stochastic reward nets using theatre

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Proceedings of the 2021 IEEE/ACM 25th International Symposium on distributed Simulation and real time Applications

作者： Franco Cicirelli Libero Nigro CNR - National Research Council of Italy Italy University of Calabria Italy

ISBN: (纸本)9781665433266

This work aims at the development of tools for supporting modelling and analysis of timed systems by Stochastic Reward Nets (SRN). In a first approach it was proposed and experimented a formal reduction of SRN over timed Automata (TA) in the context of the Uppaal popular toolbox. The reduction has the merit to allow both exhaustive model checking of an SRN model, useful for the assessment of qualitative properties (e.g., absence of deadlocks, occurrence of particular event sequences etc.), and quantitative analysis through the statistical model checker, which is based on simulations. However, although Uppaal enabled formal reasoning on the semantics of SRN, its practical usage suffers of scalability problems, that is it can introduce severe limitations in time and space when studying complex models. To cope with this problem, this paper describes a Java implementation of the SRN operational core engine, using the lock-free and efficient Theatre actor system which permits the parallel simulation of large models. The realization can be used for functional property checking on an untimed version of a source SRN model, and quantitative estimation of measurables through simulations. The paper discusses the design and implementation of the core engine of SRN on top of Theatre, together with supported intuitive configuration process of an SRN model, and reports some experimental results using a scalable grid computing model. The experiments confirm Theatre/SRN are capable of exploiting the potential of modern multi-core machines and can deliver good execution performances on large models.

关键词： theatre Java stochastic reward nets actors high-performance computing performability analysis

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99% of Worker-Master Communication in distributed Optimization Is Not Needed 36

99% of Worker-Master Communication in Distributed Optimizati...

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Conference on Uncertainty in Artificial Intelligence (UAI)

作者： Mishchenko, Konstantin Hanzely, Filip Richtarik, Peter KAUST Thuwal Saudi Arabia

In this paper we discuss sparsification of worker-to-server communication in large distributed systems. We improve upon algorithms that fit the following template: a local gradient estimate is computed independently by each worker, then communicated to a master, which subsequently performs averaging. The average is broadcast back to the workers, which use it to perform a gradient-type step to update the local version of the model. We observe that the above template is fundamentally inefficient in that too much data is unnecessarily communicated from the workers to the server, which slows down the overall system. We propose a fix based on a new update-sparsification method we develop in this work, which we suggest being used on top of existing methods. Namely, we develop a new variant of parallel block coordinate descent based on independent sparsification of the local gradient estimates before communication. We demonstrate that with only m/n blocks sent by each of n workers, where m is the total number of parameter blocks, the theoretical iteration complexity of the underlying distributed methods is essentially unaffected. As an illustration, this means that when n = 100 parallel workers are used, the communication of 99% blocks is redundant, and hence a waste of time. Our theoretical claims are supported through extensive numerical experiments which demonstrate an almost perfect match with our theory on a number of synthetic and real datasets.

关键词： Iterative methods

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Research on active and reactive power coordinated control method of parallel compensator with energy storage

Research on active and reactive power coordinated control me...

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Electrical Engineering and Control Technologies (CEECT), Conference on

作者： Wanlin Guan Mingyu Xu Xiaoguang Chen Hang Su Zhixiong Liu Haoyu Li Electric Power Research Institute State Grid Heilongjiang Electric Power Co. Ltd. Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China

ISBN: (纸本)9781665499002

Due to the high permeability of the distributed energy system under weak grid condition, the existence of line impedance reduces the voltage support capacity of the common coupling point, and the output intermittency of the energy system causes power imbalance during the system operation. To solve the problems mentioned above, this paper proposes a power coordinated control method based on energy-storage parallel compensator. Considering both the state of charge (SOC) of the energy-storage battery and the device capacity limitation, the parallel compensator under proposed control method performs real-time active and reactive power compensation to the grid, effectively solving the power fluctuation of the grid-connected system and ensuring the stability of the common coupling point voltage. The overall performance of the proposed control method is illustrated with the four-quadrant operation principle, the coordination control method mechanism, and the simulation-based performance. Finally, based on RT-BOX hardware-in-the-loop experimental platform, the experimental verification of different working conditions is carried out. The experimental results prove the effectiveness and accuracy of the proposed control method.

关键词： Performance evaluation Couplings Reactive power Fluctuations Voltage fluctuations systems operation Stability analysis

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MEEC: First workshop on Momentary Emotion Elicitation and Capture

MEEC: First Workshop on Momentary Emotion Elicitation and Ca...

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ACM CHI Conference on Human Factors in Computing systems (CHI)

作者： El Ali, Abdallah Perusquia-Hernandez, Monica Denman, Pete Abdelrahman, Yomna Hassib, Mariam Meschtscherjakov, Alexander Ferreira, Denzil Henze, Niels Ctr Wiskunde & Informat CWI Distributed & Interact Syst Grp Amsterdam Netherlands NTT Commun Sci Labs Atsugi Kanagawa Japan Intel Corp Developing Exploratory Prototypes Labs Portland OR USA Bundeswehr Univ Munich Munich Germany Salzburg Univ Ctr Human Comp Interact Salzburg Austria Univ Oulu Oulu Finland Univ Regensburg Media Informat Regensburg Germany

ISBN: (纸本)9781450368193

Recognizing human emotions and responding appropriately has the potential to radically change the way we interact with technology. However, to train machines to sensibly detect and recognize human emotions, we need valid emotion ground truths. A fundamental challenge here is the momentary emotion elicitation and capture (MEEC) from individuals continuously and in real-time, without adversely affecting user experience. In this first edition of the one-day CHI 2020 workshop, we will (a) explore and define novel elicitation tasks (b) survey sensing and annotation techniques (c) create a taxonomy of when and where to apply an elicitation method.

关键词： emotion affective computing elicitation capture momentary

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