FACO: a hybrid fuzzy ant colony optimization algorithm for virtual machine scheduling in high-performance cloud computing

Ragmani, Awatif; Elomri, Amina; Abghour, Noreddine; Moussaid, Khalid; Rida, Mohamed

doi:10.1007/s12652-019-01631-5

Cited by 47 publications

(22 citation statements)

References 29 publications

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“…Therefore, a fine-grained cloud computing model was used for quality of service by using reinforcement learning to balance cluster nodes in cloud computing. Ragmani et al [41] proposed a combination algorithm called Fuzzy Ant Colony Improvement Algorithm Rule (FACO) for scheduling virtual hosts to increase efficiency in a cloud. The fuzzy module evaluates historical data to calculate the value of the pheromone .…”

Section: E Dynamic Load Balancing Frameworkmentioning

confidence: 99%

Cloud Dynamic Load Balancing and Reactive Fault Tolerance Techniques: A Systematic Literature Review (SLR)

et al. 2022

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The computational cloud aims to move traditional computing from personal computers to cloud providers on the internet. Cloud security represents an important research area. Confidentiality, integrity, and availability are the main cloud security characteristics addressed. Cloud providers apply dynamic load balancing and reactive fault tolerance techniques to build secure cloud services to achieve high service availability. Dynamic cloud load balancing approaches distribute submitted tasks to virtual machines during tasks execution and the load of virtual machines is updated based on the system's state. Reactive cloud fault tolerance is activated for system process failures after failure effectively happens. Reactive cloud fault tolerance handles failure after the fault has occurred. Despite the significance of dynamic load balancing and reactive fault tolerance techniques and mechanisms, few reviews focus on these approaches in a systematic, unbiased method focusing on integrating cloud dynamic load balancing and reactive fault tolerance techniques. This paper conducts a systematic literature review of the existing literature concerning reactive fault tolerance, dynamic load balancing, and their integration in their basic approaches, types, frameworks, and future directions.

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Section: E Dynamic Load Balancing Frameworkmentioning

confidence: 99%

Cloud Dynamic Load Balancing and Reactive Fault Tolerance Techniques: A Systematic Literature Review (SLR)

et al. 2022

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“…The authors in [18] have introduced a predictive fault module based on the analysis of the available data in the Cloud infrastructure. This module works in correlation with the other modules dedicated to load balancing and scheduling which have been introduced in a previous work of the same authors [19]. In addition, they have studied the correlations between the values of smart attributes and the probability of failure of a hard disk relative to a given server.…”

Section: Fault Tolerance Approaches In the Cloud Computingmentioning

confidence: 99%

Fault Tolerance for Composite Cloud Services: A MAS-based Novel Approach

Hioual

Hemam

et al. 2022

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Several Cloud services may be composed in order to respond quickly to the needs of users. Unfortunately, when running such a service some faults may occur. The outcome of fault control is a big challenge. In this paper, the authors propose a new approach based back recovery and multi-agent planning methods. The proposed architecture based MAS (Multi-Agent System) is composed of two main types of Agents : a Composition Manager Agent (CMA) and a Supervisor Agent (SA). The role of the CMA is to create a set of plans as an oriented graph where the nodes are the Cloud services and the valued arcs represent the composition order of these services. This agent saves checkpoints (nodes) in a stable memory so that there are at least one possible path. However, the SA ensures that the running plan is working properly; otherwise, it informs the CMA to select another sub-plan. Experimental results show the performance and effectiveness of the proposed approach.

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“…A. Ragmani, et al [39] suggested an algorithm to define the optimal configuration for virtual machine placement in such a way that it optimizes the use of cloud computing resources. In their study, two algorithms are used to assign virtual machines to servers.…”

Section: Ant System Asmentioning

confidence: 99%

A Review of Implementing Ant System Algorithms on Scheduling Problems

Kashef

Elshaer

2021

The Egyptian International Journal of Engineering Sciences and

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The ant system (AS) and scheduling problem are well-known concepts in literature. Ant algorithms have been known to be an effective tool for solving combinatorial optimization problems. Elitist AS (EAS), rank-based AS (RAS), ant colony system (ACS), and max-min AS (MMAS) are the variants of the AS algorithm; they are triggered by the different ways of updating the pheromone trail τ, computing the visibility η, and/or other parameters in the basic AS model. The main contribution of this article is twofold. First, the basic AS and its controlled parameters are presented, the key variants of the ant algorithms are explained, and major changes of each variant from the basic model are tracked. Second, sixty papers are collected between 2015 and 2020 based on a search strategy for tracking the implementation of different AS variants in solving scheduling problems. Numerous findings based on a statistical analysis of the collected papers are reported and discussed. This study will allow the researcher to understand the essence of the ant algorithm, recognize the fundamental differences in its five systems, and determine how each of them can be implemented. Tracking a sample of articles that apply an ant algorithm for a specific case study gives researchers new ideas on how to adjust the original model to fit their problem.

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FACO: a hybrid fuzzy ant colony optimization algorithm for virtual machine scheduling in high-performance cloud computing

Cited by 47 publications

References 29 publications

Cloud Dynamic Load Balancing and Reactive Fault Tolerance Techniques: A Systematic Literature Review (SLR)

Cloud Dynamic Load Balancing and Reactive Fault Tolerance Techniques: A Systematic Literature Review (SLR)

Fault Tolerance for Composite Cloud Services: A MAS-based Novel Approach

A Review of Implementing Ant System Algorithms on Scheduling Problems

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