2020
DOI: 10.1016/j.procs.2020.06.085
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Energy-Efficient Data Aggregation Through the Collaboration of Cloud and Edge Computing in Internet of Thing’s Networks

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Cited by 7 publications
(3 citation statements)
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“…In Equation ( 8), the dependable variables for the computation of energy are transmittance energy, E TX , receiving energy, E RX , aggregation energy, E agg , and amplification energy, E amp [60]. Figure 7 showcases that this scheme offers reduced energy consumption compared to other models observed over the entire iteration.…”
Section: Analysis Of Energy Consumptionmentioning
confidence: 99%
See 1 more Smart Citation
“…In Equation ( 8), the dependable variables for the computation of energy are transmittance energy, E TX , receiving energy, E RX , aggregation energy, E agg , and amplification energy, E amp [60]. Figure 7 showcases that this scheme offers reduced energy consumption compared to other models observed over the entire iteration.…”
Section: Analysis Of Energy Consumptionmentioning
confidence: 99%
“…For this purpose, the mobile nodes are assigned with an initial energy of 10 J, while they will consume 50 nJ for forwarding 1 bit of data. This condition is based on the first-order radio energy model [60]. The mathematical expression used for computing total energy, E T , consumption is written in Equation ( 8):…”
Section: Analysis Of Energy Consumptionmentioning
confidence: 99%
“…The preprocessing of data by edge computing is equivalent to the unconditioned reflex of nerve endings to external stimuli. The analysis and mining of data by cloud computing are equivalent to the brain's memory and logical processing function [19]. Figure 6 shows the difference between cloud computing and edge computing.…”
Section: Edge Computing Features and Application Scenariosmentioning
confidence: 99%