Quantifying the Impact of Replication on the Quality-of-Service in Cloud Databases

Osman, Rasha; Pérez, Juan F.; Casale, Giuliano

doi:10.1109/qrs.2016.40

Cited by 3 publications

(1 citation statement)

References 23 publications

(26 reference statements)

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“…An proposed an architecture [12] that provides better security to the cloud and fulfill Quality of Service (QoS) requirements, using Software Defined Networking (SDN) and Hadoop.…”

Section: Related Workmentioning

confidence: 99%

To Analyze Power Consumption and Quality of Service using Map Reduce on Hadoop: A Survey

Rai¹,

Namdev²

2018

IJCA

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Data is growing at a rate which cannot be handled by the traditional methods of computing. To store and process such data new data analysis and storage techniques have emerged over the last few years. Hadoop is one such parallel processing open source framework which provides distributed storage and processing of Big data. Big Data analytics has emerged as an attractive domain of research these days. For handling big data cloud computing has been used and back end of thetechnology is cluster of resources. Cluster of resources can be formed using a framework like Apache Hadoop. In this paper a survey is performed on big data analysis using Apache Hadoop and other utility tools. For better performance of cloud Quality of service and power consumption should be optimal. So in this survey is discuss resolves around Quality of Service and energy consumption.

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“…An proposed an architecture [12] that provides better security to the cloud and fulfill Quality of Service (QoS) requirements, using Software Defined Networking (SDN) and Hadoop.…”

Section: Related Workmentioning

confidence: 99%

To Analyze Power Consumption and Quality of Service using Map Reduce on Hadoop: A Survey

Rai¹,

Namdev²

2018

IJCA

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An Energy Efficient and QoS Achieved Through MapReduce in Cloud Environment

Rai¹,

Namdev²,

Saurabh

et al. 2019

First International Conference on Sustainable Technologies for Computational Intelligence

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Architectural Design of Cloud Applications: A Performance-Aware Cost Minimization Approach

Ciavotta¹,

Gibilisco²,

Ardagna³

et al. 2022

IEEE Trans. Cloud Comput.

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Cloud Computing has assumed a relevant role in the ICT, profoundly influencing the life-cycle of modern applications in the manner they are designed, developed, and operated. The Cloud market offers highly diversified services upon which developers and operators can rely. Yet, its full adoption requires specific and rare expertise. Actually, such services are characterized by a steep learning curve and, among the other aspects, by significantly different Quality of Service (QoS). In this paper, we tackle the problem of supporting the design-time performance analysis of Cloud applications and the identification of the optimal strategy for allocating components onto Cloud resources. In particular, the final goal is to set the basis to overcome the limitations of current design-alternatives search tools proposing (i) a mathematical formulation for the underlying optimization problem, i.e., determine the Cloud configuration that minimizes the execution costs of the application over a daily time horizon, fulfilling at once QoS and service allocation constraints, and (ii) a software solution able to efficiently solve the resource allocation problem. The tool, codenamed SPACE4Cloud, embodies a hybrid two-level search meta-heuristic for the efficient exploration of the design-alternatives space. The benefits of this approach are demonstrated in the context of an industrial case study. Furthermore, this work also presents results where SPACE4Cloud leads to a cost reduction up to 60%, when compared to a first-principle technique based on utilization thresholds, like the ones typically used in practice. Finally, an extensive scalability analysis indicates that our solution is able to solve large problem instances within a time frame compatible with a fast-paced design process (less than half an hour in the worst case).

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Quantifying the Impact of Replication on the Quality-of-Service in Cloud Databases

Cited by 3 publications

References 23 publications

To Analyze Power Consumption and Quality of Service using Map Reduce on Hadoop: A Survey

To Analyze Power Consumption and Quality of Service using Map Reduce on Hadoop: A Survey

An Energy Efficient and QoS Achieved Through MapReduce in Cloud Environment

Architectural Design of Cloud Applications: A Performance-Aware Cost Minimization Approach

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