Consistency rationing in the cloud

Kraska, Tim; Hentschel, Martin; Alonso, Gustavo; Kossmann, Donald

doi:10.14778/1687627.1687657

Cited by 155 publications

(97 citation statements)

References 15 publications

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“…However, these work differentiate from ours in the sense that they focus on data whereas we concentrate on service. [11,22,28,46] are the closest work to our work. In particular, [22] propose an approach for trading consistency and scalability of transactional processes in the cloud, based on the needs of an application.…”

Section: Replication and Consistency In The Gridmentioning

confidence: 71%

“…[11,22,28,46] are the closest work to our work. In particular, [22] propose an approach for trading consistency and scalability of transactional processes in the cloud, based on the needs of an application. The notion of category they proposed is similar to the region policies, but they mainly aim for storage levels.…”

Section: Replication and Consistency In The Gridmentioning

confidence: 71%

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Scalable service-oriented replication with flexible consistency guarantee in the cloud

Chen

Bahsoon

Tawil

2014

Information Sciences

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a b s t r a c tReplication techniques are widely applied in and for cloud to improve scalability and availability. In such context, the well-understood problem is how to guarantee consistency amongst different replicas and govern the trade-off between consistency and scalability requirements. Such requirements are often related to specific services and can vary considerably in the cloud. However, a major drawback of existing service-oriented replication approaches is that they only allow either restricted consistency or none at all. Consequently, service-oriented systems based on such replication techniques may violate consistency requirements or not scale well. In this paper, we present a Scalable Service Oriented Replication (SSOR) solution, a middleware that is capable of satisfying applications' consistency requirements when replicating cloud-based services. We introduce new formalism for describing services in service-oriented replication. We propose the notion of consistency regions and relevant service oriented requirements policies, by which trading between consistency and scalability requirements can be handled within regions. We solve the associated sub-problem of atomic broadcasting by introducing a Multi-fixed Sequencers Protocol (MSP), which is a requirements aware variation of the traditional fixed sequencer approach. We also present a Region-based Election Protocol (REP) that elastically balances the workload amongst sequencers. Finally, we experimentally evaluate our approach under different loads, to show that the proposed approach achieves better scalability with more flexible consistency constraints when compared with the state-of-the-art replication technique.

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Section: Replication and Consistency In The Gridmentioning

confidence: 71%

Section: Replication and Consistency In The Gridmentioning

confidence: 71%

Scalable service-oriented replication with flexible consistency guarantee in the cloud

Chen

Bahsoon

Tawil

2014

Information Sciences

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“…There is often a non-trivial trade-off between cost, consistency, and availability [Kraska et al, 2009]. Weak consistency is often considered sufficient for applications deployed in public clouds [Fetai and Schuldt, 2012].…”

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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“…Investigated the consistency properties provided by commercial clouds and made several useful opinions [12]. Existing commercial clouds generally limit strong consistency promises to small datasets (Google's Megastore and Microsoft's SQL Data Services), or provide only eventual consistency (Amazon's simpleDB and Google's BigTable) [13]. The consistency requirements differ over time depending on tangible accessibility of the data, and the authors deliver techniques that make the system dynamically adjust to the consistency level by monitoring the state of the data.…”

Section: Related Workmentioning

confidence: 99%

Overview of Auditing Cloud Consistency

Hemant¹

2015

IJRITCC

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-Cloud storage services have become very popular due to their infinite advantages. To provide always-on access, a cloud service provider (CSP) maintains multiple copies for each piece of data on geographically distributed servers. A major disadvantage of using this technique in clouds is that it is very expensive to achieve strong consistency on a worldwide scale. In this system, a novel consistency as a service (CaaS) model is presented, which involves a large data cloud and many small audit clouds. In the CaaS model we are presented in our system, a data cloud is maintained by a CSP. A group of users that participate an audit cloud can verify whether the data cloud provides the promised level of consistency or not. The system proposes a two level auditing architecture, which need a loosely synchronize clock in the audit cloud. Then design algorithms to measure the severity of violations with two metrics: the commonality of violations, and the oldness value of read. Finally, heuristic auditing strategy (HAS) is devised to find out as many violations as possible. Many experiments were performed using a combination of simulations and a real cloud deployment to validate HAS.

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Consistency rationing in the cloud

Cited by 155 publications

References 15 publications

Scalable service-oriented replication with flexible consistency guarantee in the cloud

Scalable service-oriented replication with flexible consistency guarantee in the cloud

Resource management of replicated service systems provisioned in the cloud

Overview of Auditing Cloud Consistency

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