MCPF: Fault-Tolerant Scheduling of Scientific Workflow on Cloud Computing DOI Creative Commons
Zain Ulabedin, Pervez Khan,

Burhan Uddin

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Март 28, 2024

Abstract Scientific workflow applications entail extensive amounts of tasks and data-sets necessitating systematic processing. Cloud platform is utilized for executing these which provide access to scalable on demand resources. Running scientific cloud computing experiences a huge amount failure, i.e., hardware failures, software network etc., due the large scale heterogeneity distributed nature. That affects overall execution time, monitory cost, resource utilization. Numerous fault-tolerance methods are used resolve handle failures in environment. In this paper, we MCPF (Multiple Critical Partitions with Failure) technique. The proposed technique has two phases. first phase, rank all calculated by summing ranks, downward upward rank. And then, second phase scheduled based their ranking VMs, lower failure rate. We evaluated performance our under different conditions using parameters, makespan cost. have compared results well-known existing HEFT, RDEARP algorithms. Simulation obtained through experiments comparison techniques lead us conclusion that yields better than

Язык: Английский

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

и другие.

IEEE Transactions on Parallel and Distributed Systems, Год журнала: 2023, Номер 34(4), С. 1343 - 1361

Опубликована: Фев. 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.

Язык: Английский

Процитировано

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, Год журнала: 2023, Номер 34(6)

Опубликована: Апрель 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.

Язык: Английский

Процитировано

28
Eel and grouper optimizer: a nature-inspired optimization algorithm DOI
Ali Mohammadzadeh, Seyedali Mirjalili

Cluster Computing, Год журнала: 2024, Номер unknown

Опубликована: Июнь 17, 2024

Язык: Английский

Процитировано

13
Energy-aware workflow scheduling in fog computing using a hybrid chaotic algorithm DOI
Ali Mohammadzadeh,

Mahdi Akbari Zarkesh,

Pouria Haji Shahmohamd

и другие.

The Journal of Supercomputing, Год журнала: 2023, Номер 79(16), С. 18569 - 18604

Опубликована: Май 16, 2023

Язык: Английский

Процитировано

17
Use of whale optimization algorithm and its variants for cloud task scheduling: a review DOI
Ali Mohammadzadeh, Amit Chhabra, Seyedali Mirjalili

и другие.

Elsevier eBooks, Год журнала: 2024, Номер unknown, С. 47 - 68

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

6
AI-based & heuristic workflow scheduling in cloud and fog computing: a systematic review DOI
Navid Khaledian,

Marcus Voelp,

Sadoon Azizi

и другие.

Cluster Computing, Год журнала: 2024, Номер 27(8), С. 10265 - 10298

Опубликована: Май 8, 2024

Язык: Английский

Процитировано

5
HICA: A Hybrid Scientific Workflow Scheduling Algorithm for Symmetric Homogeneous Resource Cloud Environments DOI Open Access
Liang Hu,

Xianwei Wu,

Xilong Che

и другие.

Symmetry, Год журнала: 2025, Номер 17(2), С. 280 - 280

Опубликована: Фев. 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.

Язык: Английский

Процитировано

0
Multi-strategy Improved Seagull Optimization Algorithm DOI Creative Commons
Yancang Li, Weizhi Li, Qiuyu Yuan

и другие.

International Journal of Computational Intelligence Systems, Год журнала: 2023, Номер 16(1)

Опубликована: Сен. 21, 2023

Abstract Aiming at the shortcomings of seagull optimization algorithm in process searching for optimization, such as slow convergence speed, low precision, easy falling into local optimal, and performance dependent on selection parameters, this paper proposes an improved gull based multi-strategy fusion analysis population characteristics. Firstly, L–C cascade chaotic mapping is used to initialize so that seagulls are more evenly distributed initial solution space. Secondly, improve algorithm’s global exploration ability early stage, nonlinear factor incorporated adjust position migration stage. At same time, group learning strategy was introduced after update quality accuracy further. Finally, late stage algorithm, golden sine Levy flight guidance mechanism population’s diversity enhance development To verify CEC2017 CEC2022 test suites selected simulation experiments, box graphs drawn. The results show proposed has apparent accuracy, stability advantages. engineering case demonstrate advantages solving complex problems with unknown search spaces.

Язык: Английский

Процитировано

10
A Comprehensive Survey on Seagull Optimization Algorithm and Its Variants DOI
Vimal Kumar Pathak, Swati Gangwar, Mithilesh K. Dikshit

и другие.

Archives of Computational Methods in Engineering, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Multi‐Criteria Optimization of Scientific Workflow Schedules for Improved Energy Efficiency in Cloud Infrastructures DOI
Nadia Dahmani, Hatem Aziza, Hajer Ben-Romdhane

и другие.

Concurrency and Computation Practice and Experience, Год журнала: 2025, Номер 37(9-11)

Опубликована: Апрель 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.

Язык: Английский

Процитировано

0