Learning Multi-Objective Network Optimizations

Hoon Lee, Sang Hyun Lee, Tony Q.S. Quek

研究成果: Conference contribution

摘要

This paper studies a deep learning approach for multi-objective network optimizations. Heterogeneous performance measures are maximized simultaneously to identify complete Pareto-optimal tradeoffs. To this end, a multi-objective optimization (MOO) problem is first reformulated as a collection of constrained single objective optimization (SOO) problems, each associated with a Pareto-optimal point. A novel MOO learning mechanism is developed to address multiple instances of such SOO problems concurrently. A constrained optimization technique is parameterized with neural networks to find an individual solution of the Pareto boundary points. The developed scheme proves efficient in characterizing the optimal tradeoffs of conflicting performance metrics in interfering networks.

原文English
主出版物標題2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
發行者Institute of Electrical and Electronics Engineers Inc.
頁面91-96
頁數6
ISBN(電子)9781665426718
DOIs
出版狀態Published - 2022
事件2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022 - Seoul, Korea, Republic of
持續時間: 2022 5月 162022 5月 20

出版系列

名字2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022

Conference

Conference2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
國家/地區Korea, Republic of
城市Seoul
期間22-05-1622-05-20

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦網路與通信
  • 訊號處理
  • 控制和優化

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