A brief survey on replica consistency in cloud environments

Campêlo, Robson A.; Casanova, Marco A.; Guedes, Dorgival; Laender, Alberto H. F.

doi:10.1186/s13174-020-0122-y

Cited by 20 publications

(14 citation statements)

References 49 publications

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“…The requirements of cloud computing are scalability with large data set operations [90], resulting in increasing the performance using over-provisioning of the resources [127]. The data on storage systems needs prompt scale to cover the increasing workload demands by providing the provision to horizontal or vertical expansions [128]. Many of the cloud base applications rely upon data-replication to achieve better performance, availability, scalability, and reliability [129].…”

Section: Scalabilitymentioning

confidence: 99%

“…The available solutions include proactive and reactive approaches [112]. During high workloads, the data storage must be able to expand with increasing load hike and also adjust to shrink during low load by releasing the unutilized cloud resources [128]. Elasticity and scalability objective are two interrelated terms, where the latter allows the shrinking concept of the resources besides the expansion.…”

Section: Elasticity: Challenges and Issuesmentioning

confidence: 99%

“…A consistency model in distributed domain figures out which guarantees can be expected for an update operation and for accessing an updated object. Its open challenges in cloud computing architecture to obtaining the correct balance between higher levels of consistency and availability [128]. However, more replication increases inconsistent replicas and strong replication (traditional synchronous) has its restrictions because of deficient performance and latency.…”

Section: Consistency: Challenges and Issuesmentioning

confidence: 99%

See 2 more Smart Citations

Quantitative Analysis and Performance Evaluation of Target-Oriented Replication Strategies in Cloud Computing

Waseem¹,

Din

Alshamrani

et al. 2021

Electronics

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Data replications effectively replicate the same data to various multiple locations to accomplish the objective of zero loss of information in case of failures without any downtown. Dynamic data replication strategies (providing run time location of replicas) in clouds should optimize the key performance indicator parameters, like response time, reliability, availability, scalability, cost, availability, performance, etc. To fulfill these objectives, various state-of-the-art dynamic data replication strategies has been proposed, based on several criteria and reported in the literature along with advantages and disadvantages. This paper provides a quantitative analysis and performance evaluation of target-oriented replication strategies based on target objectives. In this paper, we will try to find out which target objective is most addressed, which are average addressed, and which are least addressed in target-oriented replication strategies. The paper also includes a detailed discussion about the challenges, issues, and future research directions. This comprehensive analysis and performance evaluation based-work will open a new door for researchers in the field of cloud computing and will be helpful for further development of cloud-based dynamic data replication strategies to develop a technique that will address all attributes (Target Objectives) effectively in one replication strategy.

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Section: Scalabilitymentioning

confidence: 99%

Section: Elasticity: Challenges and Issuesmentioning

confidence: 99%

Section: Consistency: Challenges and Issuesmentioning

confidence: 99%

See 1 more Smart Citation

Quantitative Analysis and Performance Evaluation of Target-Oriented Replication Strategies in Cloud Computing

Waseem¹,

Din

Alshamrani

et al. 2021

Electronics

View full text Add to dashboard Cite

show abstract

“…Load balancing mechanisms used in Web clouds can be divided into three main categories [11,[14][15][16][17]: static, dynamic and adaptive. In static load balancing assignments are conducted with the use of deterministic or probabilistic algorithms that do not take in to account the current state of the system.…”

Section: Related Workmentioning

confidence: 99%

Two-level fuzzy-neural load distribution strategy in cloud-based web system

Zatwarnicki

2020

J Cloud Comp

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Cloud computing Web systems are today the most important part of the Web. Many companies transfer their services to the cloud in order to avoid infrastructure aging and thus preventing less efficient computing. Distribution of the load is a crucial problem in cloud computing systems. Due to the specifics of network traffic, providing an acceptable time of access to the Web content is not trivial. The utilization of the load distribution with adaptive intelligent distribution strategies can deliver the highest quality of service, short service time and reduce the costs. In the article, a new, two-level, intelligent HTTP request distribution strategy is presented. In the process of designing the architecture of the proposed solution, the results of earlier studies and experiments were taken into account. The proposed decision system contains fuzzy-neural models yielding minimal service times in the Web cloud. The article contains a description of the new solution and the test-bed. In the end, the results of the experiments are discussed and conclusions and presented.

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“…An additional and essential challenge that faces multi-cloud storage systems is the heterogeneity of consistency models followed by different providers [11]. Having a strict consistency assumption or atomicity of operations from a cloud storage provider is an impractical assumption that should be avoided.…”

Section: Introductionmentioning

confidence: 99%

Data Consistency in Multi-Cloud Storage Systems With Passive Servers and Non-Communicating Clients

Mhaisen

Malluhi

2020

IEEE Access

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Multi-cloud storage systems are becoming more popular due to the ever-expanding amount of consumer data. This growth is accompanied by increasing concerns regarding security, privacy, and reliability of cloud storage solutions. Ensuring data consistency in such systems is especially challenging due to their architecture and characteristics. Specifically, passive cloud storage cannot run coordination software, and clients cannot communicate directly to reach consensus. Furthermore, the atomicity of operations is not always guaranteed by the clouds' public APIs. In this paper, we formally define data consistency in multi-cloud storage systems, identify how they can be violated, and introduce a new method that provably maintains the data consistency in these systems. The implementation and experiments show that the proposed method can maintain data consistency with a certain delay in data uploading and that it is scalable with respect to the number of used clouds as well as the number of users. Integrating this method into multi-cloud storage systems will enhance their usability and reliability.

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A brief survey on replica consistency in cloud environments

Cited by 20 publications

References 49 publications

Quantitative Analysis and Performance Evaluation of Target-Oriented Replication Strategies in Cloud Computing

Quantitative Analysis and Performance Evaluation of Target-Oriented Replication Strategies in Cloud Computing

Two-level fuzzy-neural load distribution strategy in cloud-based web system

Data Consistency in Multi-Cloud Storage Systems With Passive Servers and Non-Communicating Clients

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