A Novel Scheduling Approach for Spark Workflow Tasks With Deadline and Uncertain Performance in Multi-Cloud Networks DOI
Kamran Yaseen Rajput, Xiaoping Li, Jinquan Zhang

et al.

IEEE Transactions on Cloud Computing, Journal Year: 2024, Volume and Issue: 12(4), P. 1145 - 1157

Published: Aug. 26, 2024

Language: Английский

Reliability-Aware Multi-Objective Memetic Algorithm for Workflow Scheduling Problem in Multi-Cloud System DOI
Shuo Qin, Dechang Pi, Zhongshi Shao

et al.

IEEE Transactions on Parallel and Distributed Systems, Journal Year: 2023, Volume and Issue: 34(4), P. 1343 - 1361

Published: Feb. 23, 2023

With the development of cloud computing, multi-cloud systems have become common platforms for hosting and executing workflow applications in recent years. However, complexity scheduling increases exponentially because diversified billing mechanisms, heterogeneous virtual machines, reliability systems. This article focuses on a multi-objective problem (MOWSP-MCS). The makespan, cost, are considered optimization objectives from perspective users. Compared with classical environment, MOWSP-MCS allows users to apply backup technique improve reliability. To solve MOWSP-MCS, this proposes reliability-aware memetic algorithm (RA-MOMA) containing diversification strategy intensification strategy. In strategy, several problem-specific genetic operators introduced construct offspring individuals. four neighborhood designed based critical path resource utilization rate quality individuals archive set. A comprehensive numerical experiment is conducted evaluate effectiveness RA-MOMA. comparisons related algorithms demonstrate superiority RA-MOMA solving MOWSP-MCS.

Language: Английский

Citations

29

Ultra‐reliability and low‐latency communications on the internet of things based on 5G network: Literature review, classification, and future research view DOI
Seyed Salar Sefati, Simona Halunga

Transactions on Emerging Telecommunications Technologies, Journal Year: 2023, Volume and Issue: 34(6)

Published: April 8, 2023

Abstract A new technology known as the Internet of Things (IoT) uses several sensor devices and communication protocols. By implementing cutting‐edge modern equipment, people use IoT to make their lives easier. Home automation is one them, it works with actuators sensors. However, increasing number in network could degrade Quality Service (QoS). Therefore, an appropriate framework software hardware can improve Experience (QoE) QoS for all users. One critical measures called Ultra Reliability Low Latency Communication (URLLC). URLLC essential released from third Generation Partnership Project (3GPP) cellular. a systematic comprehensive investigation practical procedures needs be done. This paper comprehensively investigates existing methodologies this subject. All chosen techniques are separated into four categories obtain complete picture topic: structure‐based, diversity‐based, metaheuristic algorithm‐based, channel state information. In paper, we also investigate more benefits drawbacks other when applied network. highlights challenges networks describes future open issues detail provide efficient way researchers field.

Language: Английский

Citations

28

Eel and grouper optimizer: a nature-inspired optimization algorithm DOI
Ali Mohammadzadeh, Seyedali Mirjalili

Cluster Computing, Journal Year: 2024, Volume and Issue: unknown

Published: June 17, 2024

Language: Английский

Citations

12

Energy-aware workflow scheduling in fog computing using a hybrid chaotic algorithm DOI
Ali Mohammadzadeh,

Mahdi Akbari Zarkesh,

Pouria Haji Shahmohamd

et al.

The Journal of Supercomputing, Journal Year: 2023, Volume and Issue: 79(16), P. 18569 - 18604

Published: May 16, 2023

Language: Английский

Citations

17

Use of whale optimization algorithm and its variants for cloud task scheduling: a review DOI
Ali Mohammadzadeh, Amit Chhabra, Seyedali Mirjalili

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 47 - 68

Published: Jan. 1, 2024

Language: Английский

Citations

6

AI-based & heuristic workflow scheduling in cloud and fog computing: a systematic review DOI
Navid Khaledian,

Marcus Voelp,

Sadoon Azizi

et al.

Cluster Computing, Journal Year: 2024, Volume and Issue: 27(8), P. 10265 - 10298

Published: May 8, 2024

Language: Английский

Citations

4

HICA: A Hybrid Scientific Workflow Scheduling Algorithm for Symmetric Homogeneous Resource Cloud Environments DOI Open Access
Liang Hu,

Xianwei Wu,

Xilong Che

et al.

Symmetry, Journal Year: 2025, Volume and Issue: 17(2), P. 280 - 280

Published: Feb. 12, 2025

With the increasing volume of scientific computation data and advancement computer performance, is becoming more dependent on powerful computing capabilities cloud computing. On platforms, tasks in workflows are assigned to computational resources executed according specific strategies. Therefore, workflow scheduling has become a key factor affecting efficiency. This paper proposes hybrid algorithm, HICA, address problem symmetric homogeneous environments with optimization goals makespan cost. HICA combines Imperialist Competitive Algorithm (ICA) HEFT integrating into initial population ICA accelerate convergence ICA. Experimental results show that proposed approach outperforms other algorithms real-world applications. Specifically, when scale 100, average improvements cost 133.89 273.33, respectively; 1000, 371.62 9178.98. The for Earth System Model parameter tuning compared scenario without using were improved by 13% 21%, respectively.

Language: Английский

Citations

0

A Comprehensive Survey on Seagull Optimization Algorithm and Its Variants DOI
Vimal Kumar Pathak, Swati Gangwar, Mithilesh K. Dikshit

et al.

Archives of Computational Methods in Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

0

Multi‐Criteria Optimization of Scientific Workflow Schedules for Improved Energy Efficiency in Cloud Infrastructures DOI
Nadia Dahmani, Hatem Aziza, Hajer Ben-Romdhane

et al.

Concurrency and Computation Practice and Experience, Journal Year: 2025, Volume and Issue: 37(9-11)

Published: April 9, 2025

ABSTRACT Rising global dependence on cloud services has become crucial for enterprises, aiming to guarantee continuous data accessibility while pursuing enhanced energy efficiency and minimized carbon emissions from centers. However, the persistent challenge of high‐energy consumption in these facilities necessitates a concentrated approach toward reduction. This paper introduces an innovative multi‐objective scheduling strategy scientific workflows, tailored heterogeneous computing environments. Our method employs hybrid genetic algorithm, incorporating Hill Climbing generate initial population chromosomes. Subsequently, algorithm optimizes task assignments most suitable virtual machines, utilizing meticulously designed fitness function evaluate each chromosome's suitability solving problem. Through extensive experimentation, we demonstrate that our proposed outperforms other techniques terms solution quality, contributing reduced consumption, processing duration, cost. We contend this holds substantial potential mitigating footprint associated with centers, offering sustainable environmentally conscious workflow scheduling.

Language: Английский

Citations

0

AI-driven job scheduling in cloud computing: a comprehensive review DOI Creative Commons
Yousef Sanjalawe, Salam Al-E’mari, F.M.A. Salam

et al.

Artificial Intelligence Review, Journal Year: 2025, Volume and Issue: 58(7)

Published: April 11, 2025

Language: Английский

Citations

0