Quality-Elasticity: Improved Resource Utilization, Throughput, and Response Times Via Adjusting Output Quality to Current Operating Conditions
(2019) 16th IEEE International Conference on Autonomic Computing- Abstract
- This work addresses two related problems for on-line services, namely poor resource utilization during regular operating conditions, and low throughput, long response times, or poor performance under periods of high system load. To address these problems, we introduce our notion of quality-elasticity as a manner of dynamically adapting response qualities from software services along a fine-grained spectrum. When resources are abundant, response quality can be increased, and when resources are scarce, responses are delivered at a lower quality to prioritize throughput and response times. We present an example of how a complex online shopping site can be made quality-elastic. Experiments show that, compared to state of the art, improvements... (More)
- This work addresses two related problems for on-line services, namely poor resource utilization during regular operating conditions, and low throughput, long response times, or poor performance under periods of high system load. To address these problems, we introduce our notion of quality-elasticity as a manner of dynamically adapting response qualities from software services along a fine-grained spectrum. When resources are abundant, response quality can be increased, and when resources are scarce, responses are delivered at a lower quality to prioritize throughput and response times. We present an example of how a complex online shopping site can be made quality-elastic. Experiments show that, compared to state of the art, improvements in throughput (57% more served queries), lowered response times (8 time reduction for 95th percentile responses), and an estimated 40% profitability increase can be made using our quality-elastic approach. When resources are abundant, our approach may achieve upwards of twice as high resource utilization as prior work in this field. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8ee98fa1-cc61-4b93-8a14-2657a721554b
- author
- Larsson, Lars ; Tärneberg, William LU ; Klein, Cristian and Elmroth, Erik
- organization
- publishing date
- 2019-09-12
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Cloud computing, Resource Allocation, quality-elastic approach, Resource utilization, adaptive software, brownout, Quality elasticity
- host publication
- IEEE International Conference on Autonomic Computing (ICAC)
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 16th IEEE International Conference on Autonomic Computing
- conference location
- Umeå, Sweden
- conference dates
- 2019-06-16 - 2019-06-20
- external identifiers
-
- scopus:85073231355
- ISBN
- 978-1-7281-2412-4
- 978-1-7281-2411-7
- DOI
- 10.1109/ICAC.2019.00017
- project
- LCCC
- Cyber Security for Next Generation Factory (SEC4FACTORY)
- language
- English
- LU publication?
- yes
- id
- 8ee98fa1-cc61-4b93-8a14-2657a721554b
- date added to LUP
- 2019-10-01 12:25:38
- date last changed
- 2025-04-04 14:35:55
@inproceedings{8ee98fa1-cc61-4b93-8a14-2657a721554b,
abstract = {{This work addresses two related problems for on-line services, namely poor resource utilization during regular operating conditions, and low throughput, long response times, or poor performance under periods of high system load. To address these problems, we introduce our notion of quality-elasticity as a manner of dynamically adapting response qualities from software services along a fine-grained spectrum. When resources are abundant, response quality can be increased, and when resources are scarce, responses are delivered at a lower quality to prioritize throughput and response times. We present an example of how a complex online shopping site can be made quality-elastic. Experiments show that, compared to state of the art, improvements in throughput (57% more served queries), lowered response times (8 time reduction for 95th percentile responses), and an estimated 40% profitability increase can be made using our quality-elastic approach. When resources are abundant, our approach may achieve upwards of twice as high resource utilization as prior work in this field.}},
author = {{Larsson, Lars and Tärneberg, William and Klein, Cristian and Elmroth, Erik}},
booktitle = {{IEEE International Conference on Autonomic Computing (ICAC)}},
isbn = {{978-1-7281-2412-4}},
keywords = {{Cloud computing; Resource Allocation; quality-elastic approach; Resource utilization; adaptive software; brownout; Quality elasticity}},
language = {{eng}},
month = {{09}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Quality-Elasticity: Improved Resource Utilization, Throughput, and Response Times Via Adjusting Output Quality to Current Operating Conditions}},
url = {{http://dx.doi.org/10.1109/ICAC.2019.00017}},
doi = {{10.1109/ICAC.2019.00017}},
year = {{2019}},
}