Fault Tolerance In Cloud Computing Research Articles

A New Hybrid COA-OOA Based Task Scheduling and Fuzzy Logic Approach to Increase Fault Tolerance in Cloud Computing

INTRODUCTION: Technology is made available to customers worldwide through a distributed computing architecture called cloud computing. In the cloud paradigm, there is a risk of single-point failures, in order to prevent errors and gain confidence from consumers in their cloud services, one problem facing cloud providers is efficiently scheduling tasks.OBJECTIVES: High availability and fault tolerance must be offered to clients by these services. Fuzzy logic and hybrid COA-OOA are used in this study proposed fault-tolerant work scheduling algorithm. Jobs given by users and virtual machines are considered as input for this proposed approach. METHODS: The given tasks are initially scheduled utilizing the FIFO order. Then, it is rescheduled utilizing the Hybrid Coati Optimization Algorithm (COA) - Osprey Optimization Algorithm (OOA) for scheduling the task based on priority.RESULTS: This scheduled job is assigned to the VM for further execution. If the jobs are not executed successfully, then fault tolerant mechanism is carried out. Faults are recognized by employing fuzzy logic in this proposed approach. CONCLUSION: This proposed approach attains 62 sec response time, 61 sec of makespan and 98% success rate. Thus, this proposed approach is the best choice for efficient task scheduling with fault tolerant mechanism.

Intelligent Fault-Tolerant Mechanism for Data Centers of Cloud Infrastructure

Fault tolerance in cloud computing is considered as one of the most vital issues to deliver reliable services. Checkpoint/restart is one of the methods used to enhance the reliability of the cloud services. However, many existing methods do not focus on virtual machine (VM) failure that occurs due to the higher response time of a node, byzantine fault, and performance fault, and existing methods also ignore the optimization during the recovery phase. This paper proposes a checkpoint/restart mechanism to enhance reliability of cloud services. Our work is threefold: (1) we design an algorithm to identify virtual machine failure due to several faults; (2) an algorithm to optimize the checkpoint interval time is designed; (3) lastly, the asynchronous checkpoint/restart with log-based recovery mechanism is used to restart the failed tasks. The valuation results obtained using a real-time dataset shows that the proposed model reduces power consumption and improves the performance with a better fault tolerance solution compared to the nonoptimization method.

A Distributed Fault Tolerant Algorithm for Load Balancing in Cloud Computing Environments

Cloud computing is a promising paradigm that provides users with higher computing benefits in terms of cost, availability and flexibility. Nevertheless, with potentially thousands of connected machines, faults become more frequent and may have an adverse effect on the application. Consequently, fault-tolerant load balancing becomes necessary in order to optimize resource utilization while ensuring the reliability of the system. Different approaches have been proposed in the literature for fault tolerance in cloud computing. However, they suffer from several shortcomings: some fault tolerance techniques use task replication which reduce the cloud’s efficiency in terms of resource utilization. While other models rely on checkpoint recovery to tolerate failures, resulting in an increase in the mean response time. To address these shortcomings, an efficient and adaptive fault tolerant algorithm for load balancing is proposed. Based on the CloudSim simulator, some series of test-bed scenarios are considered to assess the behavior of the proposed algorithm.

Fault-Tolerance in the Scope of Cloud Computing

Fault-tolerance methods are required to ensure high availability and high reliability in cloud computing environments. In this survey, we address fault-tolerance in the scope of cloud computing. Recently, cloud computing-based environments have presented new challenges to support fault-tolerance and opened new paths to develop novel strategies, architectures, and standards. We provide a detailed background of cloud computing to establish a comprehensive understanding of the subject, from basic to advanced. We then highlight fault-tolerance components and system-level metrics and identify the needs and applications of fault-tolerance in cloud computing. Furthermore, we discuss state-of-the-art proactive and reactive approaches to cloud computing fault-tolerance. We further structure and discuss current research efforts on cloud computing fault-tolerance architectures and frameworks. Finally, we conclude by enumerating future research directions specific to cloud computing fault-tolerance development.

Adaptive Workflow Scheduling to Increase Fault Tolerance in Cloud Computing

Cloud computing in the field of high-performance distributed computing has emerged as a new development in which the demand for access to resources via the Internet is presented in distributed servers that dynamically scale Are acceptable. One of the important research issues that must be considered to achieve efficient performance is fault tolerance. Fault tolerance is a way to find faults and failures in a system. Predicting and reducing errors play an important role in increasing the performance and popularity of cloud computing. In this study, an adaptive workflow scheduling approach is presented to increase fault tolerance in cloud computing. The present approach calculates the probability of failure for each resource according to the execution time of tasks on the resources. In the present method, a deadline is set for each of the tasks. If the task is not completed within the specified time, the probability of failure in the source increases and subsequent tasks are not sent to the desired source. The simulation results of the proposed method show that the proposed idea can work well on workflows and improve service quality factors.

Improving the dependability of cloud environment for hosting real time applications

Abstract The growing use of cloud computing in various fields makes the dependability of clouds a major concern in both industry and academia, especially for real-time applications. In cloud computing, the processing is done on remote cloud nodes; therefore, the chances of errors occurring are increased because of the loose control over the remote nodes and the unexpected latency. Hence, fault tolerance in cloud computing is important to ensure the reliability and availability of real-time applications. The contribution of this paper is two-fold: first, it proposes a comprehensive framework that adopts a number of fault tolerance techniques to improve the dependability of cloud environments to host real-time applications while achieving reliability and availability requirements. Second, a fault tolerant real-time scheduling algorithm has been developed to minimize the rate of missing deadlines, makespan, and the degree of load imbalance.

A Study on Fault Tolerance Mechanisms in Cloud Computing

Cloud computing is widely popular due to its elasticity, economics, reliability and much more. Cloud computing offers a scalable service without any initial investment in servers, storages, or networks. Fault Tolerance (FT) is the ability of any system to continue performing its function regardless of any unexpected hardware or software failures. Fault Tolerance in Cloud Computing (FTCC) is an important area of research due to its complexity. However, there is a lack of studies in this field. Moreover, recent failures and availability issues in popular cloud providers demonstrates the need for more effective solutions. In this paper, we present a study on FTCC mechanisms and analyze its strength and weakness. Based on the study, a comparison on the main fault tolerance techniques is presented considering the cost, overhead, failure types, performance, and the tools used. Moreover, we study and compare the models that enhance the performance of checkpoint and replication based techniques.

Cost-Efficient Remote Backup Services for Enterprise Clouds

In order to efficiently achieve fault tolerance in cloud computing, large-scale data centers generally leverage remote backups to improve system reliability. Due to long-distance and expensive network transmission, the backups incur heavy communication overheads and potential errors. To address this important problem, we propose an efficient remote communication service, called Neptune. Neptune efficiently transmits massive data between long-distance data centers via a cost-effective filtration scheme. The filtration in Neptune is interpreted as eliminating redundancy and compressing similarity of files, which are generally studied independently in the existing work. In order to bridge their gap, Neptune leverages chunk-level deduplication to eliminate duplicate files and uses approximate delta compression to compress similar files. Moreover, in order to reduce the complexity and overheads, Neptune uses a locality-aware hashing to group similar files and proposes shortcut delta chains for fast remote recovery. We have implemented Neptune between two data centers and their distance is more than 1200 km via a 2 Mb/s network link. We examine the Neptune performance using real-world traces of Los Alamos National Laboratory (LANL), EMC, and Campus collection. Compared with state-of-the-art work, experimental results demonstrate the efficiency and efficacy of Neptune.

A Survey of Fault-tolerance in Cloud Computing: Concepts and Practice

A fault tolerance is an important property in order to achieve performance levels for important attributes for a system’s dependability, reliability, availability and Quality of Service (QoS). In this survey a comprehensive review of representative works on fault tolerance in cloud computing is presented, in which general readers will be provided an overview of the concepts and practices of a fault-tolerance computing. Cloud computing service providers will rise and fall based on their ability to execute and deliver a satisfactory QoS in primary areas such as dependability. Many enterprise users are wary of the public clouds' dependability limitations, but also curious about the possibility of adopting the technologies, designs and best practices of clouds for their own data centers such as private clouds. The situation is evolving rapidly with public, private and hybrid clouds, as vendors and users are struggling to keep up with new developments.

A Migration Approach for Fault Tolerance in Cloud Computing

Cloud computing has become a significant technology and a great solution for providing a flexible, on-demand, and dynamically scalable computing infrastructure for many applications. Cloud computing also presents a significant technology trends. With the cloud computing technology, users use a variety of devices to access programs, storage, and application-development platforms over the Internet, via services offered by cloud computing providers. The probability of failure occur during the execution becomes stronger when the number of node increases; since it is impossible to fully prevent failures, one solution is to implement fault tolerance mechanisms. Fault tolerance has become a major task for computer engineers and software developers because the occurrence of faults increases the cost of using resources. In this paper, the authors have proposed an approach that is a combination of migration and checkpoint mechanism. The checkpoint mechanism minimizes the time lost and reduces the effect of failures on application execution while the migration mechanism guarantee the continuity of application execution and avoid any loss due to hardware failure in a way transparent and efficient. The results obtained by the simulation show the effectiveness of our approaches to fault tolerance in term of execution time and masking effects of failures.

LBVFT: A Load Balancing Technique for Virtualization and Fault Tolerance in Cloud Computing

balancing in cloud computing is a grand challenge problem now a days. The main load balancing issues in cloud computing is load calculation and load distribution. To solve these issues, many load balancing techniques have been designed to distribute tasks properly. In this paper, we have proposed a Load Balancing Technique for Virtualization and Fault Tolerance in Cloud Computing (LBVFT) to assign the tasks to the virtual nodes. A Cloud Manager (CM) module and a Decision Maker (DM) are used in the proposed scheme to manage the virtualization, load balancing and to handle the faults. LBVFT is mainly designed to assign tasks to the virtual nodes depending on the success rates (SR) and the previous load history. In the load assigning technique assignment is done by the load balancer (LB) of cloud manager (CM) module in the basis of higher success rate and lower load of the available nodes.