ADAPTLOAD: effective balancing in clustered web servers under transient load conditions

Riska, Alma; Sun, Wei; Smirni, Evgenia; Ciardo, Gianfranco

doi:10.1109/icdcs.2002.1022247

Cited by 37 publications

(47 citation statements)

References 11 publications

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“…Zhang et al [Zhang et al, 2005] expands on the earlier work [Riska et al, 2002]. Dejun et al [Dejun et al, 2011] benchmark individual VMs obtained from cloud providers such as Amazon [EC2, 2014].…”

Section: ¾º º½ äó ð ò ò ó øóñ ë öú ×mentioning

confidence: 90%

“…There is a large body of related studies of load balancing for various conventional service systems [Cardellini et al, 1999;Cherkasova and Ponnekanti, 2000;Riska et al, 2002;Zhang et al, 2005] and modern cloud systems [Dejun et al, 2011]. Cardellini et al [Cardellini et al, 1999] qualitatively classified existing load balancing schemes at web server systems into four approaches, namely clientbased, DNS-based, dispatcher-based, and server-based.…”

Section: ¾º º½ äó ð ò ò ó øóñ ë öú ×mentioning

confidence: 99%

“…Riska et al [Riska et al, 2002] proposed a load balancing scheme where incoming requests are sent to replicated server back-ends based on the request size. Zhang et al [Zhang et al, 2005] expands on the earlier work [Riska et al, 2002].…”

Section: ¾º º½ äó ð ò ò ó øóñ ë öú ×mentioning

confidence: 99%

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Resource management of replicated service systems provisioned in the cloud

Björkqvist

Birke

Binder

2016

NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium

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I certify that except where due acknowledgement has been given, the work presented in this thesis is that of the author alone; the work has not been submitted previously, in whole or in part, to qualify for any other academic award; and the content of the thesis is the result of work which has been carried out since the official commencement date of the approved research program. Lugano, 11 February 2015 ×ØÖ Ø Service providers seek scalable and cost-effective cloud solutions for hosting their applications. Despite significant recent advances facilitating the deployment and management of services on cloud platforms, a number of challenges still remain. Service providers are confronted with time-varying requests for the provided applications, inter-dependencies between different components, performance variability of the procured virtual resources, and cost structures that differ from conventional data centers. Moreover, fulfilling service level agreements, such as the throughput and response time percentiles, becomes of paramount importance for ensuring business advantages. Mathias BjörkqvistIn this thesis, we explore service provisioning in clouds from multiple points of view. The aim is to best provide service replicas in the form of VMs to various service applications, such that their tail throughput and tail response times, as well as resource utilization, meet the service level agreements in the most cost effective manner. In particular, we develop models, algorithms and replication strategies that consider multi-tier composed services provisioned in clouds. We also investigate how a service provider can opportunistically take advantage of observed performance variability in the cloud. Finally, we provide means of guaranteeing tail throughput and response times in the face of performance variability of VMs, using Markov chain modeling and large deviation theory. We employ methods from analytical modeling, event-driven simulations and experiments. Overall, this thesis provides not only a multi-faceted approach to exploring several crucial aspects of hosting services in clouds, i.e., cost, tail throughput, and tail response times, but our proposed resource management strategies are also rigorously validated via trace-driven simulation and extensive experiments.

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Section: ¾º º½ äó ð ò ò ó øóñ ë öú ×mentioning

confidence: 90%

Section: ¾º º½ äó ð ò ò ó øóñ ë öú ×mentioning

confidence: 99%

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Resource management of replicated service systems provisioned in the cloud

Björkqvist

Birke

Binder

2016

NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium

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“…In the traditional distributed computing setting, the computing facilities are located together or connected by fast local area networks, such as computing clusters. Within a DGIS, it is also relatively easy to implement the associated loading sharing strategies, such as LSF (Zhou, 1988), dynamic loading sharing (Eager, et al, 1986;Riska, et al, 2002;Chen, et al, 2001;, virtual reconfigurations Xiao, et al, 2004), and network ram (Xiao, et al, 2000).. The nature and characteristics of geospatial computing will also affect the performance of the system.…”

Section: Computing Challenges In Dgismentioning

confidence: 99%

Evolution and Computing Challenges of Distributed GIS

2005

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“…ADAPTLOAD [18] developed by Riska, A., et al models clustered web server as a front-end dispatcher and back-end nodes. They use an online algorithm to decide the share of the total workload for each node to achieve load balance.…”

Section: Bmentioning

confidence: 99%

Automated cluster-based web service performance tuning

Chung¹,

Hollingsworth²

Proceedings. 13th IEEE International Symposium on High Performance Distributed Computing, 2004.

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-In this paper, we apply the Active Harmony system to improve the performance of a cluster-based web service system. The performance improvement cannot easily be achieved by tuning individual components for such a system. The experimental results show that there is no single configuration for the system that performs well for all kinds of workloads. By tuning the parameters, the Active Harmony helps the system adapt to different workloads and improve the performance up to 16%. For scalability, we demonstrate how to reduce the time when tuning a large system with many tunable parameters. Finally an algorithm is proposed to automatically adjust the structure of cluster-based web systems, and the system throughput is improved up to 70% using this technology.

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ADAPTLOAD: effective balancing in clustered web servers under transient load conditions

Cited by 37 publications

References 11 publications

Resource management of replicated service systems provisioned in the cloud

Resource management of replicated service systems provisioned in the cloud

Evolution and Computing Challenges of Distributed GIS

Automated cluster-based web service performance tuning

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