DCCWOA: A multi-heuristic fault tolerant scheduling technique for cloud computing environment

Liakath, Javid Ali; Pradeep, K.; Natesan, Gobalakrishnan

doi:10.1007/s12083-022-01445-x

Cited by 7 publications

(5 citation statements)

References 24 publications

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“…Most of the articles reviewed in fault tolerance focused on recovery or prevention methods. Fault detection 159 is a challenging issue that needs to be focused on along with fault recovery. By identifying nodes that are more likely to fail or cause failures, proactive measures can be taken to mitigate their impact and improve system reliability.…”

Section: Future Research Directionsmentioning

confidence: 99%

Fault‐tolerance approaches for distributed and cloud computing environments: A systematic review, taxonomy and future directions

Kirti,

Maurya,

Yadav

2024

Concurrency and Computation

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Fault tolerance is crucial in ensuring smooth working of distributed and cloud computing. It is challenging to implement because of the constantly changing infrastructure and complex configurations in distributed and cloud computing. Implementation of various fault tolerance methods require domain‐specific knowledge as well as in‐depth understanding of the existing techniques and approaches. Recent surveys on fault tolerance in cloud and distributed environments exist, but they have limitations. This article systematically reviews fault tolerance approaches in distributed and cloud computing and discusses their taxonomy. Based on the taxonomy provided, fault‐tolerance approaches are divided into four types, that is, reactive approaches, proactive approaches, adaptive approaches, and hybrid approaches. Reactive approaches provide a preventive measure after the occurrence of faults in the system. Proactive approaches prevent the system or minimize failure effects by predicting in advance. The adaptive approaches predict, learn, and adapt the changes to deal with new faults in the system. The hybrid approaches combine reactive, proactive, and adaptive approaches. The objective of this article is to give a better understanding of handling faults using suitable approaches and further compare them on various parameters. The paper also presents a promising research direction based on the challenges and issues in multiple approaches.

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Section: Future Research Directionsmentioning

confidence: 99%

Fault‐tolerance approaches for distributed and cloud computing environments: A systematic review, taxonomy and future directions

Kirti,

Maurya,

Yadav

2024

Concurrency and Computation

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“…In this technique, the assertions based on the system's response are used to manage failures. However, The Checkpointed League Championship Algorithm (CPLCA) scheduling technique was suggested in [23] as a fault-tolerance conscious task scheduling method. This approach offers task migration and fault tolerance by employing the checkpointing strategy.…”

Section: B Fault Tolerance Approachesmentioning

confidence: 99%

“…The proposed HFSLM is compared with four different approaches based on two main parameters i.e., makespan and average utilization. HFSLM is evaluated by comparing it with FTHRM [22], OLB [23], MIN-MIN [24], and MAX-MIN [25] for less than 1000 tasks. Also, compared with ELISA and MELISA with greater than 10,000 tasks.…”

Section: B Fault-tolerancementioning

confidence: 99%

Next-Gen Cloud Efficiency: Fault-Tolerant Task Scheduling With Neighboring Reservations for Improved Resource Utilization

Umar Mushtaq,

Sheikh,

Idrees

2024

IEEE Access

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One of the main goals in any computational system like the cloud is to effectively allocate resources proficiently for task scheduling. However, the dynamic characteristics of the cloud make it more prone to faults and failures. The flexible and responsive changes are made to redistribute virtual machines (VMs) to address these faults and failures for maintaining continuous services. However, it may inadvertently lead to uneven load distribution. Therefore, thorough attention is required to ensure carefully monitored load equilibrium following fault tolerance. Addressing all these issues simultaneously with optimized Quality of Service (QoS) parameters is a good need of time. In this paper, a novel hybrid model: the Hybrid Faulttolerant Scheduling and Load balancing Model (HFSLM) has been proposed to optimize the makespan of the dynamically arriving tasks and efficiently utilize the available VMs. Moreover, the model also provides solutions for several crucial concerns in cloud systems including VM failure, and VM/task heterogeneity. In the consequence of a VM failure, the approach offers a Neighbouring VM as a substitute for the corresponding task to complete its execution. Furthermore, the model is escorted by a load-balancing algorithm to maintain the equilibrium of load distribution after fault handling for further optimization of the considered QoS parameters. HFSLM is evaluated by comparing it with FTHRM, MAX-MIN, MIN-MIN, and OLB on a small task scale over diverse task and machine heterogeneities and with ELISA and MELISA on an extremely large task scale. The evaluation results show that the recommended HFSLM tops the compared approaches in all the considered cases and heterogeneities.INDEX TERMS cloud computing, task allocation, fault tolerance, resource reservation, load balancing I. INTRODUCTION

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“…In Reference 46, a multi‐heuristic fault tolerant scheduling algorithm for cloud computing is presented. The name of this algorithm is Dynamic Clustering Cuckoo Whale Optimization Algorithm (DCCWOA) that for efficient task scheduling in the cloud by paying equal attention to the fault tolerance parameter.…”

Section: Classification Of Workflow Scheduling Algorithmsmentioning

confidence: 99%

“…According to the above explanations, the classification of workflow scheduling methods has been shown in Figure 4. In the first part, the classification of methods is based on the nature of scheduling algorithms, which includes super-heuristic 9 Meta Heuristic methods [5], [16], [21], [35], [36], [37], [50], [51], [52], [54], [55], [56], [57], [58], [61], [62], [63], [64], [65], [66], [67] 9 Heuristic methods [1], [2], [13], [17], [18], [19], [22], [25], [26], [28], [29], [30], [31], [32], [33], [34], [42], [46], [47], [48], [49] 9 F I G U R E 4 Classification of workflow scheduling methods. 12 methods and heuristic methods.…”

Section: Classification Of Workflow Scheduling Algorithmsmentioning

confidence: 99%

A review on workflow scheduling and resource allocation algorithms in distributed mobile clouds

Golmohammadi

Tabbakh

Ghaemi

2023

Trans Emerging Tel Tech

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The advent of distributed computing and mobile clouds made it possible to transfer and distribute the heavy processes of complex workflows to the cloud. Managing and with the help of the mobile cloud, virtualization and shared resources managing the executing large‐scale workflows is possible. Since virtual resources are used, scheduling and resource allocation are important and key research topics in public cloud environment and mobile clouds. The cloud model of mobile devices with public or virtual cloud, which consists of temporary mobile devices, is an interesting topic to be investigated. Workflow scheduling and availability of resources in mobile clouds by high mobility and Energy efficient, it is one of the challenges and problems that must be investigated one of the main challenges in this research area. The purpose of scheduling algorithms is to improve service quality criteria by observing the constraints. In this article, the main goal is to extensively review the scheduling algorithms for the complex scientific workflow in public and mobile clouds. Furthermore, a review of the use of heuristic and meta‐heuristic techniques in dynamic and static states, with various constraints for task scheduling in cloud and mobile computing has been performed. This article accomplishes a review of using existing techniques for scheduling tasks in mobile clouds. We also present a comprehensive analysis and systematic comparison between these scheduling algorithms.

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DCCWOA: A multi-heuristic fault tolerant scheduling technique for cloud computing environment

Cited by 7 publications

References 24 publications

Fault‐tolerance approaches for distributed and cloud computing environments: A systematic review, taxonomy and future directions

Fault‐tolerance approaches for distributed and cloud computing environments: A systematic review, taxonomy and future directions

Next-Gen Cloud Efficiency: Fault-Tolerant Task Scheduling With Neighboring Reservations for Improved Resource Utilization

A review on workflow scheduling and resource allocation algorithms in distributed mobile clouds

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