QoS-aware service replication

You, Kun; Qian, Zhuzhong; Tang, Bin; Lu, Sanglu; Chen, Daoxu

doi:10.1145/1640206.1640214

Cited by 1 publication

(1 citation statement)

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“…They developed a passive replication strategy and validated it on a simulation prototype. In contrast, You et al [You et al, 2009] consider the replication for composed services. They replicate services that have the longest response time and deploy them on the nodes with maximum available capacity.…”

Section: ¾º½ ê ôð ø óò ó ë öú × ò ðóù ×mentioning

confidence: 99%

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: ¾º½ ê ôð ø óò ó ë öú × ò ðóù ×mentioning

confidence: 99%