Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/99470
Title: | QoS-aware revenue-cost optimization for latency-sensitive services in IaaS Clouds | Authors: | Duong, Ta Nguyen Binh Li, Xiaorong Goh, Rick Siow Mong Tang, Xueyan Cai, Wentong |
Issue Date: | 2012 | Conference: | IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (16th : 2012 : Dublin, Ireland) | Abstract: | 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. | URI: | https://hdl.handle.net/10356/99470 http://hdl.handle.net/10220/12912 |
DOI: | 10.1109/DS-RT.2012.11 | Schools: | School of Computer Engineering | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | SCSE Conference Papers |
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