QoS-aware revenue-cost optimization for latency-sensitive services in IaaS Clouds
Recently, application service providers have been employing Infrastructure-as-a-Service (IaaS) clouds such as Amazon EC2 to scale their computing resources on-demand to adapt to dynamic workloads. Existing research has been focusing more on cloud resource scaling in batch processing, non latency-sen...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10356/99470 http://hdl.handle.net/10220/12912 |
| _version_ | 1824457000758542336 |
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| author | Duong, Ta Nguyen Binh Li, Xiaorong Goh, Rick Siow Mong Tang, Xueyan Cai, Wentong |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Duong, Ta Nguyen Binh Li, Xiaorong Goh, Rick Siow Mong Tang, Xueyan Cai, Wentong |
| author_sort | Duong, Ta Nguyen Binh |
| collection | NTU |
| description | Recently, application service providers have been employing Infrastructure-as-a-Service (IaaS) clouds such as Amazon EC2 to scale their computing resources on-demand to adapt to dynamic workloads. Existing research has been focusing more on cloud resource scaling in batch processing, non latency-sensitive applications. In this paper, we consider the problem of revenue-cost optimization in cloud-based application service providers with stringent QoS requirements, e.g., online gaming services. We propose an integrated approach which combines resource provisioning algorithms and request scheduling disciplines. The main goal is to maximize the service provider's revenue via satisfying pre-defined QoS requirements, and at the same time, to minimize cloud resource cost. We have implemented the proposed resource provisioning algorithms and scheduling disciplines into a cloud scaling framework developed in our previous work. Extensive experiments have been conducted with a fully functional implementation and realistic workloads modeled after real traces of popular online game servers. The results demonstrated the effectiveness of our proposed approach. |
| first_indexed | 2025-02-19T04:03:02Z |
| format | Conference Paper |
| id | ntu-10356/99470 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T04:03:02Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/994702020-05-28T07:18:35Z QoS-aware revenue-cost optimization for latency-sensitive services in IaaS Clouds Duong, Ta Nguyen Binh Li, Xiaorong Goh, Rick Siow Mong Tang, Xueyan Cai, Wentong School of Computer Engineering IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (16th : 2012 : Dublin, Ireland) Recently, application service providers have been employing Infrastructure-as-a-Service (IaaS) clouds such as Amazon EC2 to scale their computing resources on-demand to adapt to dynamic workloads. Existing research has been focusing more on cloud resource scaling in batch processing, non latency-sensitive applications. In this paper, we consider the problem of revenue-cost optimization in cloud-based application service providers with stringent QoS requirements, e.g., online gaming services. We propose an integrated approach which combines resource provisioning algorithms and request scheduling disciplines. The main goal is to maximize the service provider's revenue via satisfying pre-defined QoS requirements, and at the same time, to minimize cloud resource cost. We have implemented the proposed resource provisioning algorithms and scheduling disciplines into a cloud scaling framework developed in our previous work. Extensive experiments have been conducted with a fully functional implementation and realistic workloads modeled after real traces of popular online game servers. The results demonstrated the effectiveness of our proposed approach. 2013-08-02T06:21:21Z 2019-12-06T20:07:51Z 2013-08-02T06:21:21Z 2019-12-06T20:07:51Z 2012 2012 Conference Paper https://hdl.handle.net/10356/99470 http://hdl.handle.net/10220/12912 10.1109/DS-RT.2012.11 en |
| spellingShingle | Duong, Ta Nguyen Binh Li, Xiaorong Goh, Rick Siow Mong Tang, Xueyan Cai, Wentong QoS-aware revenue-cost optimization for latency-sensitive services in IaaS Clouds |
| title | QoS-aware revenue-cost optimization for latency-sensitive services in IaaS Clouds |
| title_full | QoS-aware revenue-cost optimization for latency-sensitive services in IaaS Clouds |
| title_fullStr | QoS-aware revenue-cost optimization for latency-sensitive services in IaaS Clouds |
| title_full_unstemmed | QoS-aware revenue-cost optimization for latency-sensitive services in IaaS Clouds |
| title_short | QoS-aware revenue-cost optimization for latency-sensitive services in IaaS Clouds |
| title_sort | qos aware revenue cost optimization for latency sensitive services in iaas clouds |
| url | https://hdl.handle.net/10356/99470 http://hdl.handle.net/10220/12912 |
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