WSLC: Weighted semi-local centrality to identify influential nodes in complex networks DOI Creative Commons
Xiaofeng Wang, Marini Othman, Deshinta Arrova Dewi

и другие.

Journal of King Saud University - Computer and Information Sciences, Год журнала: 2023, Номер 36(1), С. 101906 - 101906

Опубликована: Дек. 27, 2023

Identifying and ranking influential nodes in complex networks is a critical aspect to study the survival robustness of networks. Many ongoing researches have proposed centrality metrics address this problem, so that performance each attributed specific scenarios. For example, based on local structure low accuracy due use limited information, global suffer from high complexity. Meanwhile, semi-local are amazingly well, but an efficient for identifying still not available differences scale In addition, most only consider one node's their development faces serious challenges. This paper develops Weighted Semi-Local Centrality (WSLC) identify extended neighborhood concept. Here, several different weights investigated find best WSLC. We concept select nearest neighbors, which considers information network way calculate ranks. distributed approach presented can cut subgraph entire node with contains neighbors hops, used maintain efficiency when facing large-scale addition importance itself, WSLC also combines hops ranking. Therefore, defining as well using edge weighting policy differentiates other existing metrics. The evaluation has been done through real-world Kendall's correlation. effectiveness under SIR infection spreading model verified by extensive simulations compared state-of-the-art

Язык: Английский

A novel virtual machine placement algorithm based on grey wolf optimization DOI Creative Commons
Hao Feng, Haoyu Li, Yuming Liu

и другие.

Journal of Cloud Computing Advances Systems and Applications, Год журнала: 2025, Номер 14(1)

Опубликована: Фев. 13, 2025

Язык: Английский

Процитировано

0
An energy-aware virtual machine placement method in cloud data centers based on improved Harris Hawks optimization algorithm DOI

Zahra Karimi Mehrabadi,

Mehdi Fartash, Javad Akbari Torkestani

и другие.

Computing, Год журнала: 2025, Номер 107(6)

Опубликована: Май 23, 2025

Язык: Английский

Процитировано

0
An efficient dynamic service provisioning mechanism in fog computing environment: A learning automata approach DOI
Meysam Tekiyehband, Mostafa Ghobaei‐Arani, Ali Shahidinejad

и другие.

Expert Systems with Applications, Год журнала: 2022, Номер 198, С. 116863 - 116863

Опубликована: Март 18, 2022

Язык: Английский

Процитировано

14
An Efficient Policy-Based Scheduling and Allocation of Virtual Machines in Cloud Computing Environment DOI Creative Commons

S Supreeth,

Kiran Kumari Patil, Shantala Devi Patil

и другие.

Journal of Electrical and Computer Engineering, Год журнала: 2022, Номер 2022, С. 1 - 12

Опубликована: Сен. 24, 2022

Cloud computing has become the most challenging research field in current information technology scenario. In this, a set of user tasks are scheduled and allocated to numerous kinds heterogeneous virtual machines (VMs) cloud data centers (CDCs), these VMs hosted by diverse types physical (PMs). It extends several features, encompassing elasticity, safety, sustainability, even adequate maintenance compared traditional centers. There techniques available for VM scheduling allocation. However, it still requires existence new mechanisms that can reduce execution time (ET) tasks, improve optimization energy usage resource utilization (RU), consumption. Along with optimization, (VMS) allocation (VMA) two-level issues need be considered essential policies govern mechanisms. Hence, executing optimal VMS VMA center, methodologies, such as enhanced shark smell algorithm (ESSOA) at first level Brownian movement-centered gravitation search (BMGSA) second level, proposed this work define policies. Firstly, requests reserved on appropriate PM ESSOA, which lowest cost within deadline limits, BMGSA decides chosen limitations level. To demonstrate algorithm’s efficiency, simulations carried out using Java language-based CloudSim simulator, mechanism outcomes acquired existing approaches. The simulation results show suggested is efficient terms cost, degree imbalance (DOI), make span (MS), (RU).

Язык: Английский

Процитировано

13
WSLC: Weighted semi-local centrality to identify influential nodes in complex networks DOI Creative Commons
Xiaofeng Wang, Marini Othman, Deshinta Arrova Dewi

и другие.

Journal of King Saud University - Computer and Information Sciences, Год журнала: 2023, Номер 36(1), С. 101906 - 101906

Опубликована: Дек. 27, 2023

Identifying and ranking influential nodes in complex networks is a critical aspect to study the survival robustness of networks. Many ongoing researches have proposed centrality metrics address this problem, so that performance each attributed specific scenarios. For example, based on local structure low accuracy due use limited information, global suffer from high complexity. Meanwhile, semi-local are amazingly well, but an efficient for identifying still not available differences scale In addition, most only consider one node's their development faces serious challenges. This paper develops Weighted Semi-Local Centrality (WSLC) identify extended neighborhood concept. Here, several different weights investigated find best WSLC. We concept select nearest neighbors, which considers information network way calculate ranks. distributed approach presented can cut subgraph entire node with contains neighbors hops, used maintain efficiency when facing large-scale addition importance itself, WSLC also combines hops ranking. Therefore, defining as well using edge weighting policy differentiates other existing metrics. The evaluation has been done through real-world Kendall's correlation. effectiveness under SIR infection spreading model verified by extensive simulations compared state-of-the-art

Язык: Английский

Процитировано

8