Open AccessBilevel Fee-Setting Optimization for Cloud Monitoring Service Under Uncertainty
Author(s) -
Chaoan Lai,
Liang Xu
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2807370
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
We introduce a new paradigm for the cooperation of cloud monitoring and study the annual fee-setting problem under uncertainty. First, a value network of cloud monitoring and different monitoring service modes are studied. Second, we express the fee-setting problem for cloud monitoring as a chanceconstrained bilevel optimization model, where the fee-setter acts as a leader, and all the clients act as followers who make decisions based on the price they receive. Third, optimal fee-setting and the interaction between the platform and clients are analyzed. Finally, numerical experiments are designed and implemented on a monitoring platform, and pricing policy and decision-making under uncertainty on unplanned downtime rate are analyzed. The proposed paradigm and model do not only target a specific cloud service, and thus they can be applied to other similar public platforms provided as services.
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