A Heuristic Approach to the Consecutive Ones Submatrix Problem

Abo-Alsabeh, Rewayda; Daham, Hajem Ati; Salhi, Abdellah

doi:10.21123/bsj.2022.6373

Cited by 1 publication

(1 citation statement)

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“…Mobile devices are capitalizing on the benefits that continuum computing has to offer in 2024, 21(2 Special Issue): 0740-0754 https://doi.org /10.21123/bsj.2024.10084 P-ISSN: 2078-8665 -E-ISSN: 2411 Baghdad Science Journal appropriate distribution of resources to tasks. The problem of task scheduling in such environment is referred to as NP-hard 4 . This is as a result of the fact that the amount of computational time required to solve a specific instance of tasks or applications increases in polynomial time 5 .…”

Section: Introductionmentioning

confidence: 99%

Efficient Task Scheduling Approach in Edge-Cloud Continuum based on Flower Pollination and Improved Shuffled Frog Leaping Algorithm

Dankolo,

Radzi,

Mustaffa

et al. 2024

Baghdad Sci.J

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The rise of edge-cloud continuum computing is a result of the growing significance of edge computing, which has become a complementary or substitute option for traditional cloud services. The convergence of networking and computers presents a notable challenge due to their distinct historical development. Task scheduling is a major challenge in the context of edge-cloud continuum computing. The selection of the execution location of tasks, is crucial in meeting the quality-of-service (QoS) requirements of applications. An efficient scheduling strategy for distributing workloads among virtual machines in the edge-cloud continuum data center is mandatory to ensure the fulfilment of QoS requirements for both customer and service provider. Existing research used metaheuristic algorithm to solve tak scheduling problem, however, must of the existing metaheuristics used suffers from falling into local mina due to their inefficiency to avoid unfeasible region in the solution search space. Therefore, there is a dire need for an efficient metaheuristic algorithm for task scheduling. This study proposed an FPA-ISFLA task scheduling model using hybrid flower pollination and improved shuffled frog leaping algorithms. The simulation results indicate that the FPA-ISFLA algorithm is superior to the PSO algorithm in terms of makespan time, resource utilization, and execution cost reduction, especially with an increasing number of tasks.

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Section: Introductionmentioning

confidence: 99%