Next-Gen Cloud Efficiency: Fault-Tolerant Task Scheduling With Neighboring Reservations for Improved Resource Utilization

IEEE Access, Год журнала: 2024, Номер 12, С. 75920 - 75940

Опубликована: Янв. 1, 2024

One of the main goals in any computational system like cloud is to effectively allocate resources proficiently for task scheduling. However, dynamic characteristics make it more prone faults and failures. The flexible responsive changes are made redistribute virtual machines (VMs) address these failures maintaining continuous services. may inadvertently lead uneven load distribution. Therefore, thorough attention required ensure carefully monitored equilibrium following fault tolerance. Addressing all issues simultaneously with optimized Quality Service (QoS) parameters a good need time. In this paper, novel hybrid model: Hybrid Fault-tolerant Scheduling Load balancing Model (HFSLM) has been proposed optimize makespan dynamically arriving tasks efficiently utilize available VMs. Moreover, model also provides solutions several crucial concerns systems including VM failure, VM/task heterogeneity. consequence approach offers Neighbouring as substitute corresponding complete its execution. Furthermore, escorted by load-balancing algorithm maintain distribution after handling further optimization considered QoS parameters. HFSLM evaluated comparing FTHRM, MAX-MIN, MIN-MIN, OLB on small scale over diverse machine heterogeneities ELISA MELISA an extremely large scale. evaluation results show that recommended tops compared approaches cases heterogeneities.

Язык: Английский

---

Enhancing virtual machine placement efficiency in cloud data centers: a hybrid approach using multi-objective reinforcement learning and clustering strategies

Computing, Год журнала: 2024, Номер 106(9), С. 2897 - 2922

Опубликована: Июль 2, 2024

Язык: Английский

---

A Sequential Hybrid Optimization Algorithm (SHOA) to Solve the Hybrid Flow Shop Scheduling Problems to Minimize Carbon Footprint

Processes, Год журнала: 2024, Номер 12(1), С. 143 - 143

Опубликована: Янв. 6, 2024

In today’s world, a situational awareness of sustainability is becoming increasingly important. Leaving better world for future generations the main interest many studies. It also puts pressure on managers to change production methods in most industries. Reducing carbon emissions industry today crucial saving our planet. Theoretical research and practical requirements diverge, even though numerous researchers have tackled various strategies handle emission problems. Therefore, this work considers problem furniture manufacturing Hosur, Tamilnadu, India. The case study company has system that resembles hybrid flow shop (HFS) environment. As HFS scheduling problems are NP-hard nature, exact solution techniques could not be used solve Hence, sequential optimization algorithm (SHOA) been developed paper minimize footprint. SHOA, pigeon-inspired (PIOA) hybridized sequentially with firefly (FA). A computational experimental design proposed analyze efficiency introduced strategy, solutions indicate approach reduce footprint by up 9.82%. results motivate us implement

Язык: Английский

---

Optimization of fault tolerance for iterative graph algorithm in spark GraphX based on high performance computing cluster

CCF Transactions on High Performance Computing, Год журнала: 2025, Номер unknown

Опубликована: Апрель 18, 2025

Язык: Английский

---

Proactive self‐healing techniques for cloud computing: A systematic review

Concurrency and Computation Practice and Experience, Год журнала: 2024, Номер 36(24)

Опубликована: Авг. 19, 2024

Summary Ensuring the seamless operation of cloud computing services is paramount for meeting user demands and ensuring business continuity. Fault‐tolerant self‐healing techniques play a crucial role in enhancing reliability availability platforms, minimizing downtime uninterrupted service delivery. This article systematically categorizes analyzes existing research on fault‐tolerant published between 2005 2024. We provide comprehensive technical taxonomy organizing based fault tolerance processes, encompassing considerations both availability. Additionally, we evaluate applications proactive techniques, highlighting their achievements, limitations Strategies to address identified weaknesses are discussed, alongside future challenges open issues domain resilience. Through this analysis, contributes understanding computing, offering insights into effectiveness The findings aim guide efforts developing more robust resilient infrastructures, ultimately overall By emphasizing importance lays foundation advancing state‐of‐the‐art computing.

Язык: Английский

---

Virtual Machine Allocation in Cloud Computing Environments using Giant Trevally Optimizer

International Journal of Advanced Computer Science and Applications, Год журнала: 2023, Номер 14(9)

Опубликована: Янв. 1, 2023

Cloud computing has gained prominence due to its potential for computational tasks, but the associated energy consumption and carbon emissions remain significant challenges. Allocating Virtual Machines (VMs) Physical (PMs) in cloud data centers, a known NP-hard problem, offers an avenue enhancing efficiency. This paper presents energy-conscious optimization approach utilizing Giant Trevally Optimizer (GTO) which is inspired by hunting strategies of giant trevally, proficient marine predator. Our study mathematically models trevally's behavior when targeting seabirds. The involves strategic selection optimal locations based on food availability, including pursuing seabird prey air or seizing it from water's surface. Through extensive simulations, our method demonstrates superior performance terms skewness, CPU utilization, memory overall resource allocation research promising addressing challenges centers while optimizing utilization sustainable cost-effective operations.

Язык: Английский

---

Byzantine fault tolerance in distributed machine learning: a survey

Journal of Experimental & Theoretical Artificial Intelligence, Год журнала: 2024, Номер unknown, С. 1 - 59

Опубликована: Сен. 12, 2024

Язык: Английский

---

A Harris Hawk Optimisation system for energy and resource efficient virtual machine placement in cloud data centers

PLoS ONE, Год журнала: 2023, Номер 18(8), С. e0289156 - e0289156

Опубликована: Авг. 11, 2023

Virtualisation is a major technology in cloud computing for optimising the data centre’s power usage. In current scenario, most of services are migrated to cloud, putting more load on centres. As result, center’s size expands resulting increased energy To address this problem, resource allocation optimisation method that both efficient and effective necessary. The optimal utilisation infrastructure algorithms plays vital role. resources rely policy virtual machine resources. A placement technique, based Harris Hawk Optimisation (HHO) model centre presented paper. proposed HHO aims find best place machines suitable hosts with least consumption. PlanetLab’s real-time workload traces used performance evaluation existing PSO (Particle Swarm Optimisation) PABFD (Best Fit Decreasing). done using consumption, SLA, CPU utilisation, RAM Execution time (ms) number VM migrations. two simulation scenarios scaling scenario 1 increasing study underloaded overloaded conditions. Experimental results show algorithm improved execution time(ms) by 4%, had 27% reduction 16% SLA violation an increase 17%. also handling dynamic uncertain environments, making it real-world infrastructures.

Язык: Английский

---

Proceedings of the 3rd Edge Computing Workshop. Zhytomyr, Ukraine, April 7, 2023

Опубликована: Апрель 23, 2023

This article describes the doors-2023: 3rd Edge Computing Workshop, which was held in Zhytomyr, Ukraine, on April 7, 2023.The proceedings of workshop include 9 contributed papers that were carefully peer-reviewed and selected from 12 submissions.

Язык: Английский

---

Investigating the effect of virtual machine migration accounting on reliability using a cluster model

Journal of Edge Computing, Год журнала: 2023, Номер 2(1), С. 37 - 63

Опубликована: Май 6, 2023

The purpose of the article is to develop and verify with help mathematical modeling a software method deploying fault-tolerant computing cluster virtual machine, which consists two physical servers (main backup), on distributed data storage system synchronous replication from source server backup deployed. For this purpose, task conduct computational experiment model cluster, neglects costs during recovery for migration machines by means application Mathcad. Combining resources into clusters way ensure high reliability, fault tolerance, continuity process computer systems. This achieved through virtualization, enables movement resources, services, or applications between while maintaining processes. focus study failover composed (primary backup) connected switch, each has local hard disk. A deployed disks servers, machine running cluster. Markovian processes, flows podias, Kolmogorov's systems differential equations are built tools water To in case failure main server, shadow copy launched server. reliability measured coefficient non-stationary readiness. Markov proposed assess taking account migrating mechanisms that one memory maintains copies different enabling them continue working other event failure. simplified cost provides an upper estimate reliability. shows as availability factor, significantly impacted process. findings can be used inform decisions about technology chosen stability architecture. calculations allow us draw conclusion significant impact accounting calculation was performed under following rates disk, switch: λ0 = 1,115×10-5 1/h, λ1 3,425×10-6 λ2 2,3×10-6 1/h respectively: μ0 0,33 μ1 0,171/h, μ2 1/h. intensity synchronization system: μ3 1 μ4 2 difference coefficients d К2(t) – К1(t) 2.7×10-10

Язык: Английский

---