Edge Computing Offloading Strategy Based on Particle Swarm Algorithm for Power Internet of Things

Li, Wenjing; Deng, Wei; She, Rui; Zhang, Ningchi; Wang, Yanru; Ma, Wenjie

doi:10.1109/icbaie52039.2021.9389919

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“…Both edge and cloud solutions can be beneficial for applications running on smart things [6]. Such devices are characterized by limited resources, and transferring part of the computation to the edge or to the cloud allows them to run applications that would otherwise exceed their computational capacity [7,8,9]. In addition, smart things are typically battery-powered, thus, offloading part of the computation to other devices may bring benefits in terms of spent energy.…”

Section: Introductionmentioning

confidence: 99%

Edge Computing vs Centralized Cloud: Impact of Communication Latency on the Energy Consumption of LTE Terminal Nodes

Caiazza¹,

Giordano²,

Luconi³

et al. 2021

Preprint

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Edge computing brings several advantages, such as reduced latency, increased bandwidth, and improved locality of traffic. One aspect that is not sufficiently understood is the impact of the different communication latency experienced in the edge-cloud continuum on the energy consumption of clients. We studied how a request-response communication scheme is influenced by different placements of the server, when communication is based on LTE. Results show that by accurately selecting the operational parameters a significant amount of energy can be saved.

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