Adaptable SLA-Aware Consistency Tuning for Quorum-Replicated Datastores

Sidhanta, Subhajit; Golab, Wojciech; Mukhopadhyay, Supratik; Basu, Supratim

doi:10.1109/tbdata.2017.2656121

Cited by 4 publications

(5 citation statements)

References 20 publications

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“…In Algorithm 1, step 1 acts as a proxy node to receive the data write requirement. Corresponding to the minimum latency target, except the weak consistency setting, the remaining replicas are sent to nodes in other DCs and the receipt is not necessary (2)(3). In steps (4-9), the nodes in remote DCs are selected to store the replicas in terms of Alg.2.…”

Section: 𝑎 𝐴 𝑖 𝑗mentioning

confidence: 99%

“…Some existing works focused on the optimization of the replicas synchronization and consistency scheme. In [3], a machine learning-based predictive framework is present, which can select client-centric consistency methods under the limit of latency and staleness thresholds. In [4], the notion of almost strong consistency as an option for the consistency/latency tradeoff is discussed, and the deterministically bounded staleness of data versions is demonstrated.…”

Section: Introductionmentioning

confidence: 99%

“…In step (1), the DC selection is restricted by 𝑑, and the distances are considered in DCs. Then the nearest node is obtained by the infectious scheme in each rack of the decided DC in parallel (2)(3)(4). In step (5), the candidate node is returned for replicas writing in set 𝑆 .…”

mentioning

confidence: 99%

See 2 more Smart Citations

An asynchronous consistency algorithm in smart manufacturing cloud data centers

Yan

Jing

et al. 2022

J. Phys.: Conf. Ser.

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In the smart manufacturing factory, the fresh real-time datas and multiple replications are important for numerically-controlled machine tools. The production datas are stored in distributed cloud data centers (CDCs), so the communication latencies produced by data synchronization may impair the machining performance. In this paper, an asynchronous consistency algorithm (ACA) which is inspired by the nearest infection is proposed to reduce the communication latencies between nodes. The experimental results demonstrate that the proposed algorithm can support lower client-side latencies and increase data stability, thereby improving the production efficiency.

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Section: 𝑎 𝐴 𝑖 𝑗mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An asynchronous consistency algorithm in smart manufacturing cloud data centers

Yan

Jing

et al. 2022

J. Phys.: Conf. Ser.

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“…OptCon [35] is a machine learning-based framework that can automatically predict a matching consistency level that satisfies the latency and staleness thresholds specified in a given service level agreement (SLA). For this reason, OptCon provides the following dynamic parameters as input variables to the learning algorithms: the read proportion in the operation, the number of user threads spawned by the client, and the number of network packets transmitted during the operation in addition to the client-centric consistency level.…”

Section: Optconmentioning

confidence: 99%

“…Many works in the literature addressed the adaptive consistency and the trade-off between consistency and availability [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. The proposed approaches have used different protocols to provide adaptive consistency.…”

Section: Introductionmentioning

confidence: 99%

A comparative analysis of adaptive consistency approaches in cloud storage

Khelaifa

Benharzallah

Kahloul

et al. 2019

Journal of Parallel and Distributed Computing

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NoSQL storage systems are used extensively by web applications and provide an attractive alternative to conventional databases due to their high security and availability with a low cost. High data availability is achieved by replicating data in different servers in order to reduce access time lag, network bandwidth consumption and system unreliability. Hence, the data consistency is a major challenge in distributed systems. In this context, strong consistency guarantees data freshness but affects directly the performance and availability of the system. In contrast, weaker consistency enhances availability and performance but increases data staleness. Therefore, an adaptive consistency strategy is needed to tune, during runtime, the consistency level depending on the criticality of the requests or data items. Although there is a rich literature on adaptive consistency approaches in cloud storage, there is a need to classify as well as regroup the approaches based on their strategies. This paper will establish a set of comparative criteria and then make a comparative analysis of existing adaptive consistency approaches. A survey of this kind not only provides the user/researcher with a comparative performance analysis of the approaches but also clarifies the suitability of these for candidate cloud systems.

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