Machine Learning-Based Two-Stage Task Offloading Optimization for Power Distribution Internet of Things

<div>The impact of the weight <svg height="8.8423pt" id="M335" style="vertical-align:-0.2064009pt" version="1.1" viewbox="-0.0498162 -8.6359 9.35121 8.8423" width="9.35121pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M697 650H468L461 623L492 619C539 613 547 605 518 546C481 471 367 264 278 116H276C239 278 197 500 186 567C180 604 185 613 226 619L252 623L260 650H24L17 623C78 617 92 613 108 533L216 -11H247C365 200 515 462 560 529C616 612 624 615 689 623L697 650Z"></path></g></svg> on total delay and energy efficiency.</div>

Wireless Communications and Mobile Computing

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Figure 6

Figure 6: Machine Learning-Based Two-Stage Task Offloading Optimization for Power Distribution Internet of Things 