Reducing waiting and idle time for a group of jobs in the grid computing

Almhanna, Mahdi S.; Al-Turaihi, Firas Sabah; Murshedi, Tariq A.

doi:10.11591/eei.v12i5.4729

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…Accordingly, only three resources can be satisfied to represent the resources of the replication, and the first three are the best of these resources, due to the high possibility of carrying out this task. The possibility of achieving the task increases in the event of increased resources, but this option is not good, because it causes resource consumption, network fall, and instability of the network [27]. Figure 2 represents the response time of all resources before any of them are excluded, while Figure 3 represents those with a higher response time.…”

Section: Case Studymentioning

confidence: 99%

Customizing the minimum number of replicas for achieving fault tolerance in a cloud/grid environment

S. Almhanna,

A. Murshedi,

Al-Turaihi

et al. 2024

Bulletin EEI

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Networks consist of numerous resources; it is crucial not to overlook fault tolerance and consider it during planning. This is because errors during implementation can result in wasted time and effort, thereby squandering these resources. One solution to address this issue effectively is to implement the task on multiple resources to minimize the occurrence of failed tasks. However, employing an unspecified or fixed number of resources can lead to the depletion of network resources and the overall failure of the network. Replication plays a pivotal role in enhancing data availability in distributed systems. By storing data in multiple locations, users can still access it even if some copies are unavailable due to site failure. Many replication-based algorithms utilize a predetermined number of iterations per function, which may consume excessive network resources, even if the ongoing task does not require such abundant resources. This paper proposes task replication as a viable mechanism for an efficient and fault-tolerant scheduling system. We introduce an algorithm that dynamically selects the optimal and minimal number of replicas based on the network's failure history. This approach aims to minimize the failure rate during task execution.

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Section: Case Studymentioning

confidence: 99%

Customizing the minimum number of replicas for achieving fault tolerance in a cloud/grid environment

S. Almhanna,

A. Murshedi,

Al-Turaihi

et al. 2024

Bulletin EEI

View full text Add to dashboard Cite

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Dynamic Weight Assignment with Least Connection Approach for Enhanced Load Balancing in Distributed Systems

Almhanna

Murshedi

Al-Turaihi

et al. 2023

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Load balancing is a critical aspect of managing server resources efficiently and ensuring optimal performance in distributed systems. The Weighted Round Robin (WRR) algorithm is commonly used to allocate incoming requests among servers based on their assigned weights. However, static weights may not reflect the changing demands of servers, leading to imbalanced workloads. To address this issue, this study proposes a dynamic mechanism for assigning weights to servers in the WRR algorithm based on the data rate and incorporates the Least Connection approach for the best result. The dynamic mechanism takes into account the real-time data rate of each server, representing its current load. Servers with higher data rates are assigned higher weights to attract a larger share of incoming requests, while those with lower data rates receive lower weights to manage their loads effectively. This dynamic weight assignment allows the algorithm to adapt to varying workloads and achieve better load balancing across servers. To further refine the distribution of requests, the Least Connection approach is employed to handle tie-breaking situations and for more fairness in distributing the loads. The proposed algorithm is a hybrid of data rate and the Least Connection, it is evaluated through simulations and real-world experiments. The results demonstrate its superiority in achieving improved load balance compared to traditional static-weight WRR algorithms. By dynamically adjusting weights based on data rate and employing the Least Connection approach, the algorithm optimizes server resource usage, minimizes response times, and enhances overall system performance in distributed environments.

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Reducing waiting and idle time for a group of jobs in the grid computing

Cited by 2 publications

References 22 publications

Customizing the minimum number of replicas for achieving fault tolerance in a cloud/grid environment

Customizing the minimum number of replicas for achieving fault tolerance in a cloud/grid environment

Dynamic Weight Assignment with Least Connection Approach for Enhanced Load Balancing in Distributed Systems

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