Less Carbon Footprint in Edge Computing by Joint Task Offloading and Energy Sharing

Zhanwei Yu*, Yi Zhao, Tao Deng, Lei You, Di Yuan

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

We address reducing carbon footprint (CF) in the context of edge computing. The carbon intensity of electricity supply largely varies spatially as well as temporally. We consider optimal task scheduling and offloading, as well as battery charging to minimize the total CF. We formulate this optimization problem as a mixed integer linear programming model. However, we demonstrate that, via a graph-based reformulation, the problem can be cast as a minimum-cost flow problem, and global optimum can be admitted in polynomial time. Numerical results using real-world data show that optimization can reduce up to 83.3% of the total CF.
Original languageEnglish
JournalIEEE Networking Letters
Volume5
Issue number4
Pages (from-to)245-249
Number of pages5
ISSN2576-3156
DOIs
Publication statusPublished - 2023

Keywords

  • Carbon footprint
  • Scheduling
  • Edge computing

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