The paper designed a method using grid oriented multi-objective particle swarm optimization (GOMPSO) for optimally placing and sizes the distributed generators (DG) to achieve objective of reduction in the loss of act...
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In view of the high-speed data transmission requirements of the new generation of power line carrier communication in distributed photovoltaic information access, data compression sensing is required to improve. In th...
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In distributed neural network training with multiple machines and devices, communication limitations often create efficiency bottlenecks due to the frequent exchange of model parameters and gradient information betwee...
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Most power companies are undergoing a critical period of digital transformation, and information systems are an important carrier of digital transformation. The success of digitalization depends on whether the support...
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Power grid line fault diagnosis is a key task to ensure the reliability and stability of the power system. Traditional fault diagnosis methods rely on centralized data collection and processing, which are often constr...
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distributed power sources can reduce transmission and network losses, improve grid stability and reliability, and lower system operation costs, which are of great significance for improving the economy and environment...
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We describe the engineering of the distributed-memory multilevel graph partitioner dKaMinPar. It scales to (at least) 8192 cores while achieving partitioning quality comparable to widely used sequential and shared-mem...
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ISBN:
(纸本)9783031396977;9783031396984
We describe the engineering of the distributed-memory multilevel graph partitioner dKaMinPar. It scales to (at least) 8192 cores while achieving partitioning quality comparable to widely used sequential and shared-memory graph partitioners. In comparison, previous distributed graph partitioners scale only in more restricted scenarios and often induce a considerable quality penalty compared to non-distributed partitioners. When partitioning into a large number of blocks, they even produce infeasible solution that violate the balancing constraint. dKaMinPar achieves its robustness by a scalable distributed implementation of the deep-multilevel scheme for graph partitioning. Crucially, this includes new algorithms for balancing during refinement and coarsening.
With the large quantity of access to distributed power sources and flexible loads, there will be many stakeholders in the traditional EPS, such as power grid companies, owners of distributed power sources and flexible...
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Traditionally, distributed machine learning takes the guise of (i) different nodes training the same model (as in federated learning), or (ii) one model being split among multiple nodes (as in distributed stochastic g...
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ISBN:
(纸本)9781665416474
Traditionally, distributed machine learning takes the guise of (i) different nodes training the same model (as in federated learning), or (ii) one model being split among multiple nodes (as in distributed stochastic gradient descent). In this work, we highlight how fog- and IoT-based scenarios often require combining both approaches, and we present a framework for flexible parallel learning (FPL), achieving both data and model parallelism. Further, we investigate how different ways of distributing and parallelizing learning tasks across the participating nodes result in different computation, communication, and energy costs. Our experiments, carried out using state-of-the-art deep-network architectures and large-scale datasets, confirm that FPL allows for an excellent trade-off among computational (hence energy) cost, communication overhead, and learning performance.
The proceedings contain 115 papers. The topics discussed include: traffic processing and fingerprint generation for smart home device event;Fingersound: a low-cost and deployable authentication system with fingertip s...
ISBN:
(纸本)9781665473156
The proceedings contain 115 papers. The topics discussed include: traffic processing and fingerprint generation for smart home device event;Fingersound: a low-cost and deployable authentication system with fingertip sliding sound;a distributed method to form UAV swarm based on moncular vision;time-frequency analysis-based transient harmonic feature extraction for load monitoring;hierarchical computing network collaboration architecture for industrial Internet of things;an improved spray and wait algorithm based on the node social tree;Melanlysis: a mobile deep learning approach for early detection of skin cancer;causal ordering in the presence of byzantine processes;Nuwa: a receiver-driven congestion control framework to achieve high-throughput and controlled delay over dynamic wireless networks;relationship between g-extra connectivity and G-restricted connectivity in networks;and tunable causal consistency: specification and implementation.
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