On a Feedback Control-based Mechanism of Bidding for Cloud Spot Service
(2015) 7th IEEE International Conference on Cloud Computing Technology and Science p.290-297- Abstract
- As a cost-effective option for Cloud consumers, spot service has been considered to be a significant supplement for building a full-fledged market economy for the Cloud ecosystem. However, unlike the static and straightforward way of trading on-demand and reserved Cloud services, the market-driven regulations of employing spot service could be too complicated for Cloud consumers to comprehensively understand. In particular, it would be both difficult and tedious for potential consumers to determine suitable bids from time to time. To reduce the complexity in applying spot resources, we propose to use a feedback control to help make bidding decisions. Based on an arccotangent-function-type system model, our novel bidding mechanism imitates... (More)
- As a cost-effective option for Cloud consumers, spot service has been considered to be a significant supplement for building a full-fledged market economy for the Cloud ecosystem. However, unlike the static and straightforward way of trading on-demand and reserved Cloud services, the market-driven regulations of employing spot service could be too complicated for Cloud consumers to comprehensively understand. In particular, it would be both difficult and tedious for potential consumers to determine suitable bids from time to time. To reduce the complexity in applying spot resources, we propose to use a feedback control to help make bidding decisions. Based on an arccotangent-function-type system model, our novel bidding mechanism imitates fuzzy and intuitive human activities to refine and issue new bids according to previous errors. The validation is conducted by using Amazon’s historical spot price trace to perform a set of simulations and comparisons. The result shows that the feedback control-based mechanism obtains a better trade-off between bidding rationality and success rate than the other five comparable strategies. Although this mechanism is only for black-box bidding (price prediction) at this current stage, it can be conveniently and gradually upgraded to take into account external constraints in the future. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8171467
- author
- Li, Zheng LU ; Kihl, Maria LU and Robertsson, Anders LU
- organization
- publishing date
- 2015-12-03
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proceedings of the IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom 2015)
- pages
- 8 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 7th IEEE International Conference on Cloud Computing Technology and Science
- conference location
- Vancouver, Canada
- conference dates
- 2015-11-30 - 2015-12-03
- external identifiers
-
- scopus:84964403206
- wos:000380458100039
- DOI
- 10.1109/CloudCom.2015.76
- project
- EIT_VR CLOUD Cloud Control
- LCCC
- language
- English
- LU publication?
- yes
- id
- aa140728-e7ea-4b93-8f19-b79848b6a3f8 (old id 8171467)
- date added to LUP
- 2016-04-04 11:00:51
- date last changed
- 2022-05-17 03:49:43
@inproceedings{aa140728-e7ea-4b93-8f19-b79848b6a3f8,
abstract = {{As a cost-effective option for Cloud consumers, spot service has been considered to be a significant supplement for building a full-fledged market economy for the Cloud ecosystem. However, unlike the static and straightforward way of trading on-demand and reserved Cloud services, the market-driven regulations of employing spot service could be too complicated for Cloud consumers to comprehensively understand. In particular, it would be both difficult and tedious for potential consumers to determine suitable bids from time to time. To reduce the complexity in applying spot resources, we propose to use a feedback control to help make bidding decisions. Based on an arccotangent-function-type system model, our novel bidding mechanism imitates fuzzy and intuitive human activities to refine and issue new bids according to previous errors. The validation is conducted by using Amazon’s historical spot price trace to perform a set of simulations and comparisons. The result shows that the feedback control-based mechanism obtains a better trade-off between bidding rationality and success rate than the other five comparable strategies. Although this mechanism is only for black-box bidding (price prediction) at this current stage, it can be conveniently and gradually upgraded to take into account external constraints in the future.}},
author = {{Li, Zheng and Kihl, Maria and Robertsson, Anders}},
booktitle = {{Proceedings of the IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom 2015)}},
language = {{eng}},
month = {{12}},
pages = {{290--297}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{On a Feedback Control-based Mechanism of Bidding for Cloud Spot Service}},
url = {{https://lup.lub.lu.se/search/files/7608124/CloudCom2015_CameraReady.pdf}},
doi = {{10.1109/CloudCom.2015.76}},
year = {{2015}},
}