Adaptive Framework for Reliable Cloud Computing Environment

Amoon, Mohammed

doi:10.1109/access.2016.2623633

Cited by 43 publications

(19 citation statements)

References 23 publications

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“…Adaptive framework for reliable cloud computing environment [10] has developed an adaptive model/framework to handle the faults in the cloud environment. This adaptive model enable the fault tolerance support using both check pointing and replication techniques.…”

Section: Fault Tolerancementioning

confidence: 99%

DLFT: Data and Layout Aware Fault Tolerance Framework for Big Data Transfer Systems

2021

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Various scientific research organizations generate several petabytes of data per year through computational science simulations. These data are often shared by geographically distributed data centers for data analysis. One of the major challenges in distributed environments is failure; hardware, network, and software might fail at any instant. Thus, high-speed and fault tolerant data transfer frameworks are vital for transferring such large data efficiently between the data centers. In this study, we proposed a bloom filter-based data aware probabilistic fault tolerance (DAFT) mechanism that can handle such failures. We also proposed a data and layout aware mechanism for fault tolerance (DLFT) to effectively handle the false positive matches of DAFT. We evaluated the data transfer and recovery time overheads of the proposed fault tolerance mechanisms on the overall data transfer performance. The experimental results demonstrated that the DAFT and DLFT mechanisms exhibit a maximum of 10% and a minimum of 2% recovery time overhead at 80% and 20% fault points respectively. However, we observed minimum to negligible overhead with respect to the overall data transfer rate.

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Section: Fault Tolerancementioning

confidence: 99%

DLFT: Data and Layout Aware Fault Tolerance Framework for Big Data Transfer Systems

2021

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“…More chances of failures arise because of the dynamic behavior of cloud or distributed environments. To overcome such effects of these failures, the cloud should implement fault tolerance aggressively, which is always a crucial target objective to be considered while choosing or developing a replication strategy [122]. Replication increases the fault-tolerant by introducing a balance between consistency and performance during update scenarios.…”

Section: Fault Tolerancementioning

confidence: 99%

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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“…We propose the use of an active non-synchronized replication and the determination of the FT approach based on each task characteristics (a single task could employ one or both approaches). In contrast, related works often choose the approach based on machine availability only [1]. Future works include the use of proactive FT methods using, for instance, cloud node monitoring (e.g.…”

Section: Background and Related Workmentioning

confidence: 99%

A Fault Tolerant Scheduling Model for Directed Acyclic Graphs in Cloud

Rosso¹,

Francesquini²

2020

Anais Da XI Escola Regional De Alto Desempenho De São Paulo (ERAD-SP 2020)

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Many High Performance Computing (HPC) and resource intensive applications have been tested and migrated to the Cloud. These applications may have high data input size, which often has a high correlation to execution performance and time. Migration to the Cloud demands adaptation of the fault tolerance (FT) and scheduling approaches. Although those topics are well connected, they are often treated separately. This work proposes a novel integrated scheduling and FT model which takes into account the characteristics of the tasks and the target execution nodes. Preliminary results indicate good potential to improve system reliability and execution makespan of scientific workflows.

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Adaptive Framework for Reliable Cloud Computing Environment

Cited by 43 publications

References 23 publications

DLFT: Data and Layout Aware Fault Tolerance Framework for Big Data Transfer Systems

DLFT: Data and Layout Aware Fault Tolerance Framework for Big Data Transfer Systems

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

A Fault Tolerant Scheduling Model for Directed Acyclic Graphs in Cloud

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