When Lyapunov Drift Based Queue Scheduling Meets Adversarial Bandit Learning
Author:
Affiliation:
1. Interdisciplinary Information Sciences (IIIS), Tsinghua University, Beijing, China
2. Department of Computer Science, University of Southern California, Los Angeles, CA, USA
Funder
Technology and Innovation Major Project of the Ministry of Science and Technology of China
NSF
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
https://ieeexplore.ieee.org/ielam/90/10640200/10479187-aam.pdf
Reference45 articles.
1. The Nonstochastic Multiarmed Bandit Problem
2. Optimal Scheduling for Unmanned Aerial Vehicle Networks With Flow-Level Dynamics
3. On the Power of Randomization for Scheduling Real-Time Traffic in Wireless Networks
4. Stochastic models of load balancing and scheduling in cloud computing clusters
5. Stochastic modelling and analysis of cloud computing data center
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