The increasing presence of distributed Energy Resources (DER) across distribution (D) networks, along with the integration of inverter-based transmission (T) connected generation, particularly PV solar generation comb...
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ISBN:
(纸本)9798350361018;9798350361001
The increasing presence of distributed Energy Resources (DER) across distribution (D) networks, along with the integration of inverter-based transmission (T) connected generation, particularly PV solar generation combined with energy storage, and the rapid progress in information and communication technologies, has opened up new avenues for regulating both real and reactive power in power transmission and distribution (T& D) networks. Nevertheless, these advancements also bring unprecedented operational challenges. This will introduce operational and market changes that require developing many real-time operational tools to seamlessly integrate a large amount of DER and others, including behind-the-meter (BTM) DERs (primarily distributed PV), into the power grid operation. Those real-time DER operation tools must be fully tested and validated before being integrated into the existing SCADA and EMS control center platforms. As system operations are siloed in transmission and distribution, the impacts of the DER and the effects of transmission events on distribution networks have necessitated the integrated study of the transmission and distribution networks. Thus, this paper addresses the challenges of developing a real-time integrated Transmission and Distribution framework for modeling inverter-based Resources (IBRs) in OPAL-RT. Finally, the need for an EMTP-based modeling approach is addressed with the results of a co-simulated integrated T&D approach.
Modern distributedsystems are complex. They include hundreds of components that implement complex protocols such as scheduling, replication, and access control. These systems are expected to offer high availability a...
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ISBN:
(纸本)9798331531317;9798331531300
Modern distributedsystems are complex. They include hundreds of components that implement complex protocols such as scheduling, replication, and access control. These systems are expected to offer high availability and preserve their data even in the face of external environmental faults. Testing is the primary approach for improving system reliability. Testing against environmental faults such as hardware failures, memory corruption, and network problems is complicated since they can happen at any step in the protocol and affect any component. We present Slicify, a generic framework to test the network partition resilience of distributedsystems. Slicify injects network partitions during unit tests to analyze system behavior in their presence. Slicify reduces the test space in an application-agnostic fashion with its novel connection tracking mechanism. We verify Slicify's capabilities by reproducing previously documented failures in two production systems. In addition, we demonstrate its effectiveness by uncovering new failures in three popular distributedsystems.
Voltage reactive power control (VVC) plays a vital role in future-oriented smart grids, which not only ensures the stable operation of the power system but also optimizes energy distribution and consumption. However, ...
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ISBN:
(纸本)9798350361018;9798350361001
Voltage reactive power control (VVC) plays a vital role in future-oriented smart grids, which not only ensures the stable operation of the power system but also optimizes energy distribution and consumption. However, with the widespread access to distributed renewable power generation resources, the structure and operation mode of the power grid, especially the distribution network, are becoming more and more complex. The traditional VVC method is difficult to cope with this new situation due to its inherent limitations. challenge. These limitations include, but are not limited to, the static nature of the control strategy, lack of adaptability to dynamic changes in the grid, and computational inefficiency when dealing with large-scale networks. With the widespread use of artificial intelligence in smart grids, some deep-reinforcement learning algorithms have been used to solve this problem. However, because the algorithm is not good enough for controlling complex environments, in order to overcome these challenges, this paper proposes innovative methods based on deep reinforcement learning (DRL) and graph neural networks (GNN). GNN is used to extract graphical representations from topological maps of power systems and is trained with data from the VVC environment. Improve the efficiency and reliability of VVC by improving algorithms and optimization strategies.
The proceedings contain 5 papers. The topics discussed include: parallel and distributed frugal tracking of a quantile;defining the boundaries for endpoint congestion management in networks for high-performance comput...
ISBN:
(纸本)9798400706486
The proceedings contain 5 papers. The topics discussed include: parallel and distributed frugal tracking of a quantile;defining the boundaries for endpoint congestion management in networks for high-performance computing;accelerating application bulk synchronous writes in HPC environments;flying base station channel capacity;and eGossip: optimizing resource utilization in gossip-based clusters through eBPF.
With advances in technology, the issue of object detection and recognition has gained significant recognition in the field of computer vision. There are currently several algorithms that address this growing demand, n...
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ISBN:
(纸本)9798350371291;9798350371284
With advances in technology, the issue of object detection and recognition has gained significant recognition in the field of computer vision. There are currently several algorithms that address this growing demand, namely region-based convolutional neural networks (R-CNN) and the You Only Look Once (YOLO) technique. The R-CNN technique encompasses a range of methodologies designed to address object localization and recognition tasks. In addition, the YOLO technique is a distinct set of methodologies that focuses primarily on real-time object recognition and fast performance. The R-CNN and YOLO techniques, in particular, have undergone subsequent improvements, resulting in higher levels of accuracy and performance than their predecessors. The aim of this article is to review these various object detection methods based on CNN.
Geographically-distributed wide-area networks (WANs) offer expansive distributed and parallel computing capabilities. This includes the ability to advance Wide-Area Big Data (WABD). As data streaming traverses foreign...
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Geographically-distributed wide-area networks (WANs) offer expansive distributed and parallel computing capabilities. This includes the ability to advance Wide-Area Big Data (WABD). As data streaming traverses foreign networks, intrusion detection systems (IDSs) and intrusion prevention systems (IDSs) play an important role in securing information. The authors anticipate that securing WAN network topology with IDSs/IPSs can significantly impact wide-area data streaming performance. In this paper, the researchers develop and implement a geographically distributed big data streaming application using the Python programming language to benchmark IDS/IPS placement in hub-and-spoke, custom-mesh, and full-mesh network topologies. The results of the experiments illustrate that custom-mesh WANs allow IDS/IPS placements that maximize data stream packet transfers while reducing overall WAN latency. Hub-and-spoke network topology produces the lowest combined WAN latency over competing network designs but at the cost of single points of failure within the network. IDS/IPS placement in full-mesh designs is less efficient than custom-mesh yet offers the greatest opportunity for highly available data streams. Testing is limited by specific big data systems, WAN topologies, and IDS/IPS technology.
With the advancements in power and size reduction of integrated circuits, millimeter-scale self-powered systems can be seamlessly integrated into textiles or a single fiber strand, revolutionizing body sensor network ...
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ISBN:
(纸本)9798350387186;9798350387179
With the advancements in power and size reduction of integrated circuits, millimeter-scale self-powered systems can be seamlessly integrated into textiles or a single fiber strand, revolutionizing body sensor network applications. Energy harvesting and power management units (EHPMUs) face new design requirements for in-fabric systems including full autonomy, ultra-low quiescent power, high efficiency, and mm-scale footprint. Additionally, they must efficiently coordinate energy across distributed subsystems for enhanced system viability and scalability in a fiber or fabric network. This article examines current trends and innovative techniques for sub-mu A EHPMUs. It presents two case studies of sub-mu A distributed EHPMU designs: the first explores a switched-capacitor EHPMU featuring one-rail power sharing and cooperative dynamic-voltage-and-frequency-scaling;the second discusses a triple-input hybrid-inductor-capacitor multi-output EHPMU that offers improved efficiency, reduced size, multi-rail power sharing for heterogeneous fiber networks. We summarize the tradeoffs and key design considerations necessary for mm-scale EHPMUs designed for self-powered distributed fiber networks.
The proceedings contain 3 papers. The topics discussed include: mapping parallel matrix multiplication in GotoBLAS2 to the AMD versal ACAP for deep learning;exploring post quantum cryptography with quantum key distrib...
ISBN:
(纸本)9798400706448
The proceedings contain 3 papers. The topics discussed include: mapping parallel matrix multiplication in GotoBLAS2 to the AMD versal ACAP for deep learning;exploring post quantum cryptography with quantum key distribution for sustainable mobile network architecture design;and energy efficiency: a lattice Boltzmann study.
The growing developments of HPC systems used in a plethora of domains (healthcare, financial services, government and defense, energy) triggers an urgent demand for simulation frameworks that can simulate, in an integ...
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ISBN:
(纸本)9798400704130
The growing developments of HPC systems used in a plethora of domains (healthcare, financial services, government and defense, energy) triggers an urgent demand for simulation frameworks that can simulate, in an integrated manner, both processing and network components of an HPC system-under-design (SuD). The main problem, however, is that, currently, there is a shortage of simulation frameworks that can handle the simulation of actual HPC systems, including the hardware, complete software stack and network dynamics in an integrated manner. In this work we start from the first known, open-source, fully-distributed Cloud simulation framework, COSSIM, and, as part of the RED-SEA1 and Vitamin-V2 European projects, we extend it so as to be able to accurately simulate HPC systems. The extended simulator has been evaluated when executing the very-widely used HPCG & LAMMPS benchmarks on both ARM & RISC-V architectures;the results demonstrate that the presented approach has up to 95% accuracy in the reported SuD aspects.
We present a comprehensive empirical study of the impact partial network partitions have on cluster managers in data analysis frameworks. Our study shows that modern scheduling approaches are vulnerable to partial net...
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ISBN:
(纸本)9798350329100
We present a comprehensive empirical study of the impact partial network partitions have on cluster managers in data analysis frameworks. Our study shows that modern scheduling approaches are vulnerable to partial network partitions. Partial partitions can lead to a complete cluster pause or a significant loss of performance. To overcome the shortcomings of the state-of-the-art schedulers, we design CASPR, a connectivity-aware scheduler. CASPR incorporates the current network connectivity information when making scheduling decisions to allocate fully connected nodes for a given application. CASPR effectively hides partial partitions from applications. Our evaluation of a CASPR prototype shows that it can tolerate partial network partitions, as well as eliminate application halting or significant loss of performance.
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