Proactive load balancing fault tolerance algorithm in cloud computing

Attallah, Salma M.A.; Fayek, Magda B.; Nassar, Salwa M.; Hemayed, Elsayed E.

doi:10.1002/cpe.6172

Cited by 20 publications

(11 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, each request contains 1 to 10 separate tasks. In this paper, the efficiency of the proposed method against FLB [15], FLPT [12] and PLBFT [16] algorithms are compared.…”

Section: Simulation Resultsmentioning

confidence: 99%

A Fuzzy Approach to Fault Tolerant in Cloud using the Checkpoint Migration Technique

Hagshenas¹,

Mojarad²,

Arfaeinia³

2022

IJISA

View full text Add to dashboard Cite

Fault tolerance is one of the most important issues in cloud computing to provide reliable services. It is difficult to implement due to dynamic service infrastructures, complex configurations and different dependencies. Extensive research efforts have been made to implement fault tolerance in the cloud environment. Many studies focus only on fault detection and do not consider fault tolerance. For this reason, in this paper, in addition to recognizing the nature of the fault, a fuzzy logic-based approach is proposed to provide an appropriate response and increase the fault tolerance in the cloud environment. Checkpoint-based migration technique is used to increase fault tolerance. Using a checkpoint during migration can reduce time and processing costs and balance the load between virtual machines in the event of a fault. The simulation is performed according to the data center of Vietnam Telecommunications Company (VDC). The results of the proposed method in a period of 60 minutes show 98.03% fault detection accuracy, which is 4.5% and 4.1% superior to FLPT and PLBFT algorithms, respectively.

show abstract

“…In addition, each request contains 1 to 10 separate tasks. In this paper, the efficiency of the proposed method against FLB [15], FLPT [12] and PLBFT [16] algorithms are compared.…”

Section: Simulation Resultsmentioning

confidence: 99%

A Fuzzy Approach to Fault Tolerant in Cloud using the Checkpoint Migration Technique

Hagshenas¹,

Mojarad²,

Arfaeinia³

2022

IJISA

View full text Add to dashboard Cite

show abstract

“…In the work by Attallah et al [ 26 ], the proposed methodology tolerates VM CPU faults to achieve maximum CC infrastructure reliability and availability. CPU faults can occur during VM operation.…”

Section: Literature Reviewmentioning

confidence: 99%

Achieving Reliability in Cloud Computing by a Novel Hybrid Approach

Shahid

Alam

Su’ud

2023

Sensors

View full text Add to dashboard Cite

Cloud computing (CC) benefits and opportunities are among the fastest growing technologies in the computer industry. Cloud computing’s challenges include resource allocation, security, quality of service, availability, privacy, data management, performance compatibility, and fault tolerance. Fault tolerance (FT) refers to a system’s ability to continue performing its intended task in the presence of defects. Fault-tolerance challenges include heterogeneity and a lack of standards, the need for automation, cloud downtime reliability, consideration for recovery point objects, recovery time objects, and cloud workload. The proposed research includes machine learning (ML) algorithms such as naïve Bayes (NB), library support vector machine (LibSVM), multinomial logistic regression (MLR), sequential minimal optimization (SMO), K-nearest neighbor (KNN), and random forest (RF) as well as a fault-tolerance method known as delta-checkpointing to achieve higher accuracy, lesser fault prediction error, and reliability. Furthermore, the secondary data were collected from the homonymous, experimental high-performance computing (HPC) system at the Swiss Federal Institute of Technology (ETH), Zurich, and the primary data were generated using virtual machines (VMs) to select the best machine learning classifier. In this article, the secondary and primary data were divided into two split ratios of 80/20 and 70/30, respectively, and cross-validation (5-fold) was used to identify more accuracy and less prediction of faults in terms of true, false, repair, and failure of virtual machines. Secondary data results show that naïve Bayes performed exceptionally well on CPU-Mem mono and multi blocks, and sequential minimal optimization performed very well on HDD mono and multi blocks in terms of accuracy and fault prediction. In the case of greater accuracy and less fault prediction, primary data results revealed that random forest performed very well in terms of accuracy and fault prediction but not with good time complexity. Sequential minimal optimization has good time complexity with minor differences in random forest accuracy and fault prediction. We decided to modify sequential minimal optimization. Finally, the modified sequential minimal optimization (MSMO) algorithm with the fault-tolerance delta-checkpointing (D-CP) method is proposed to improve accuracy, fault prediction error, and reliability in cloud computing.

show abstract

“…Cluster computing [64] 2020 Web research [65] 2020 Electrical and computer engineering innovations [66] 2020 Arab journal of information technology [67] 2021 Computing and digital system [69] 2015 Applied engineering research [70] 2017 Research journal of engineering and technology [71] 2020 Computers and applications [72] 2021 Concurrency and computation: practice and experience…”

Section: Researchmentioning

confidence: 99%

“…A proactive fault tolerance model with load balancing has been presented by researchers of [72]. The suggested approach tolerates CPU faults of VMs in order to maximize the reliability and availability of the cloud computing infrastructure.…”

Section: B Review Of Centralized Approachesmentioning

confidence: 99%

Fault-Tolerant Load Balancing in Cloud Computing: A Systematic Literature Review

et al. 2022

View full text Add to dashboard Cite

Nowadays, cloud computing is growing daily and has been developed as an effective and flexible paradigm in solving large-scale problems. It has been known as an Internet-based computing model in which computing and virtual resources, such as services, applications, storage, servers, and networks, are shared among numerous cloud users. Since the number of cloud users and their requests are increasing rapidly, the loads on the cloud systems may be underloaded or overloaded. These situations cause different problems, such as high response time and power consumption. To handle the mentioned problems and improve the performance of cloud servers, load balancing methods have a significant impact. Generally, a load balancing method aims to detect under-loaded and overloaded nodes and balance the load among them. In the recent decade, this problem has attracted a lot of interest among researchers, and several solutions have been proposed. Considering the important role of fault-tolerant in load balancing algorithms, there is a lack of an organized and in-depth study in this field yet. This gap prompted us to provide the current study aimed to collect and review the available papers in the field of fault tolerance load balancing methods in cloud computing. The existing algorithms are divided into two categories, namely, centralized and distributed, and reviewed based on vital qualitative parameters, such as scalability, response time, reliability, availability, throughput, and overhead. In this regard, other criteria such as the type of detected faults and adopted simulation tools are taken into account.

show abstract

Proactive load balancing fault tolerance algorithm in cloud computing

Cited by 20 publications

References 18 publications

A Fuzzy Approach to Fault Tolerant in Cloud using the Checkpoint Migration Technique

A Fuzzy Approach to Fault Tolerant in Cloud using the Checkpoint Migration Technique

Achieving Reliability in Cloud Computing by a Novel Hybrid Approach

Fault-Tolerant Load Balancing in Cloud Computing: A Systematic Literature Review

Contact Info

Product

Resources

About