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Design of dynamic load balancing algorithm for heterogeneous clusters based on energy consumption

Authors: Lunqiang Ye;

Design of dynamic load balancing algorithm for heterogeneous clusters based on energy consumption

Abstract

In order to reduce energy waste and improve the dynamic load balancing of heterogeneous clusters, sensor technology is introduced into the Internet of Things technology to build a channel transmission model for heterogeneous clusters. Then use the dynamic weighting method to configure the output channel to complete the decomposition of the channel characteristics. In addition, based on the establishment of the channel fuzzy recombination structure model, the noise interference suppression method is used to suppress the multipath interference of heterogeneous cluster communication channels, and the equalization of the channel output is controlled by the baud interval equalization sampling method. At the same time, through the fuzzy balance configuration and spatial balance scheduling process, the dynamic load balancing processing of heterogeneous clusters is realized. The simulation results show that the method proposed in this paper has better balance for the load scheduling of heterogeneous clusters and reduces the bit error rate of the output signal. More importantly, the output balance and adaptive control capabilities of heterogeneous clusters have also been improved.

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Keywords

Heterogeneous clusters, Data fusion algorithms, Internet of Things, Node sensors, Balancing algorithms, Electrical engineering. Electronics. Nuclear engineering, Dynamic load, TK1-9971

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold