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Conference Paper: Probabilistic best-fit multi-dimensional range query in Self-Organizing Cloud

TitleProbabilistic best-fit multi-dimensional range query in Self-Organizing Cloud
Authors
KeywordsAllocation problems
Cloud systems
Computing resource
Different distributions
Fine granularity
Issue Date2011
PublisherIEEE, Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000540
Citation
The 40th International Conference on Parallel Processing (ICPP-2011), Taipei City, Taiwan, 13-16 September 2011. In Proceedings of the 40th ICPP, 2011, p. 763-772 How to Cite?
AbstractWith virtual machine (VM) technology being increasingly mature, computing resources in modern Cloud systems can be partitioned in fine granularity and allocated on demand with 'pay-as-you-go' model. In this work, we study the resource query and allocation problems in a Self- Organizing Cloud (SOC), where host machines are connected by a peer-to-peer (P2P) overlay network on the Internet. To run a user task in SOC, the requester needs to perform a multi-dimensional range search over the P2P network for locating host machines that satisfy its minimal demand on each type of resources. The multi-dimensional range search problem is known to be challenging as contentions along multiple dimensions could happen in the presence of the uncoordinated analogous queries. Moreover, low resource matching rate may happen while restricting query delay and network traffic. We design a novel resource discovery protocol, namely Proactive Index Diffusion CAN (PID-CAN), which can proactively diffuse resource indexes over the nodes and randomly route query messages among them. Such a protocol is especially suitable for the range query that needs to maximize its best-fit resource shares under possible competition along multiple resource dimensions. Via simulation, we show that PID-CAN could keep stable and optimized searching performance with low query delay and traffic overhead, for various test cases under different distributions of query ranges and competition degrees. It also performs satisfactorily in dynamic node-churning situation. © 2011 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/152017
ISBN
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorDi, Sen_US
dc.contributor.authorWang, CLen_US
dc.contributor.authorZhang, Wen_US
dc.contributor.authorCheng, Len_US
dc.date.accessioned2012-06-26T06:32:28Z-
dc.date.available2012-06-26T06:32:28Z-
dc.date.issued2011en_US
dc.identifier.citationThe 40th International Conference on Parallel Processing (ICPP-2011), Taipei City, Taiwan, 13-16 September 2011. In Proceedings of the 40th ICPP, 2011, p. 763-772en_US
dc.identifier.isbn978-076954510-3-
dc.identifier.issn0190-3918en_US
dc.identifier.urihttp://hdl.handle.net/10722/152017-
dc.description.abstractWith virtual machine (VM) technology being increasingly mature, computing resources in modern Cloud systems can be partitioned in fine granularity and allocated on demand with 'pay-as-you-go' model. In this work, we study the resource query and allocation problems in a Self- Organizing Cloud (SOC), where host machines are connected by a peer-to-peer (P2P) overlay network on the Internet. To run a user task in SOC, the requester needs to perform a multi-dimensional range search over the P2P network for locating host machines that satisfy its minimal demand on each type of resources. The multi-dimensional range search problem is known to be challenging as contentions along multiple dimensions could happen in the presence of the uncoordinated analogous queries. Moreover, low resource matching rate may happen while restricting query delay and network traffic. We design a novel resource discovery protocol, namely Proactive Index Diffusion CAN (PID-CAN), which can proactively diffuse resource indexes over the nodes and randomly route query messages among them. Such a protocol is especially suitable for the range query that needs to maximize its best-fit resource shares under possible competition along multiple resource dimensions. Via simulation, we show that PID-CAN could keep stable and optimized searching performance with low query delay and traffic overhead, for various test cases under different distributions of query ranges and competition degrees. It also performs satisfactorily in dynamic node-churning situation. © 2011 IEEE.en_US
dc.languageengen_US
dc.publisherIEEE, Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000540-
dc.relation.ispartofProceedings of the International Conference on Parallel Processingen_US
dc.rightsInternational Conference on Parallel Processing. Copyright © IEEE, Computer Society.-
dc.rights©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectAllocation problems-
dc.subjectCloud systems-
dc.subjectComputing resource-
dc.subjectDifferent distributions-
dc.subjectFine granularity-
dc.titleProbabilistic best-fit multi-dimensional range query in Self-Organizing Clouden_US
dc.typeConference_Paperen_US
dc.identifier.emailDi, S: sdi@cs.hku.hken_US
dc.identifier.emailWang, CL: clwang@cs.hku.hk-
dc.identifier.emailZhang, W: wdzhang@cs.hku.hk-
dc.identifier.emailCheng, L: lwcheng@cs.hku.hk-
dc.identifier.authorityWang, CL=rp00183en_US
dc.description.naturepublished_or_final_versionen_US
dc.identifier.doi10.1109/ICPP.2011.13en_US
dc.identifier.scopuseid_2-s2.0-80155191143en_US
dc.identifier.hkuros201879-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80155191143&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage763en_US
dc.identifier.epage772en_US
dc.publisher.placeUnited Statesen_US
dc.description.otherThe 40th International Conference on Parallel Processing (ICPP-2011), Taipei City, Taiwan, 13-16 September 2011. In Proceedings of the 40th ICPP, 2011, p. 763-772-
dc.identifier.scopusauthoridCheng, L=53983802400en_US
dc.identifier.scopusauthoridZhang, W=53986007100en_US
dc.identifier.scopusauthoridWang, CL=7501646188en_US
dc.identifier.scopusauthoridDi, S=22733353300en_US

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