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Survey on Fault-Tolerance-Aware Scheduling in Cloud Computing

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Information and Communication Technology for Competitive Strategies

https://doi.org/10.1007/978-981-13-0586-3_28
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Abstract

Nowadays, to a large extent, clients look at cloud not just as service provider but also as partner. So, they want cloud to deliver timely and accurate services. Cloud nodes must be reliable in order to provide quality of services as per the customer requirements. Further, physical size of high-performance computing environment is also increasing day by day. Larger the system, more failures are likely to occur that eventually results in the poor reliability of the system which is highly undesirable for the time-critical applications. To deal with the reliability, service provider must know the failure characteristics of the cloud computing nodes in order to better handle the failure using fault-tolerance-aware techniques at the time of scheduling the application tasks. Thus, in this paper, we presented the survey of fault-tolerance-aware techniques which are classified as proactive and reactive fault tolerance. This survey provides the foundation for the researchers to work in the area of fault-tolerance-aware scheduling in order to have better scheduling decisions with the aim to enhance the performance and reliability of application execution. Keywords Reliability ⋅ Fault tolerance ⋅ Virtualization 1 Introduction Cloud is an Internet-based computing paradigm that provides basic services as Infrastructure as a Service (IaaS), Software as a Service (SaaS), Platform as a Service (PaaS) [1]. Different types of cloud providers, i.e., public, private, or hybrids, are responsible for providing above services to user. Nowadays, usage of

FAQs

sparkles

AI

What informs the scheduling of tasks in proactive fault tolerance methods?add

The study reveals that tasks are assigned to reliable virtual machines based on historical failure data. By utilizing prior reliability information, these methods aim to enhance application execution reliability.

How does the Monte Carlo Failure Estimation algorithm improve scheduling reliability?add

This algorithm estimates future failure patterns using Weibull failure distribution, leading to more informed scheduling decisions. It incorporates failure predictions into resource allocation, thus minimizing disruptions during application execution.

What distinguishes heuristic approaches from meta-heuristic approaches in scheduling?add

Heuristic approaches focus on problem-specific solutions and may not yield near-optimal outcomes, while meta-heuristic approaches are designed to escape local optima. For instance, a simulated annealing algorithm outperformed traditional branch-and-bound techniques in reliability maximization.

What role does checkpointing play in reactive fault tolerance strategies?add

Checkpointing allows systems to record state at intervals, facilitating recovery from failures by resuming execution from the last saved state. This method is crucial for minimizing computation loss during task failures in cloud environments.

What are the benefits of replication in enhancing system reliability?add

Replication reduces vulnerability to single point failures by creating redundant task copies across multiple processors. Active replication can successfully execute tasks even if some copies face faults, thus improving overall system resilience.

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