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- W2337796539 abstract "Load balancing technology can effectively exploit potential enormous compute power available on distributed systems and achieve scalability. Communication delay overhead on distributed system, which is time-varying and is usually ignored or assumed to be deterministic for traditional load balancing strategies, can greatly degrade the load balancing performance. Considering communication delay overhead and its time-varying feature, a hierarchical load balancing strategy based on generalized neural network (HLBSGNN) is presented for large distributed systems. The novelty of the HLBSGNN is threefold: (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M1><mml:mrow><mml:mn fontstyle=italic>1</mml:mn></mml:mrow></mml:math>) the hierarchy with optimized communication is employed to reduce load balancing overhead for large distributed computing systems, (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M2><mml:mrow><mml:mn fontstyle=italic>2</mml:mn></mml:mrow></mml:math>) node computation rate and communication delay randomness imposed by the communication medium are considered, and (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M3><mml:mrow><mml:mn fontstyle=italic>3</mml:mn></mml:mrow></mml:math>) communication and migration overheads are optimized via forecasting delay. Comparisons with traditional strategies, such as centralized, distributed, and random delay strategies, indicate that the HLBSGNN is more effective and efficient." @default.
- W2337796539 created "2016-06-24" @default.
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- W2337796539 date "2016-01-01" @default.
- W2337796539 modified "2023-10-18" @default.
- W2337796539 title "A Hierarchical Load Balancing Strategy Considering Communication Delay Overhead for Large Distributed Computing Systems" @default.
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- W2337796539 doi "https://doi.org/10.1155/2016/5641831" @default.
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