A survey of fault tolerance in cloud computing

Kumari, Priti; Kaur, Parmeet

doi:10.1016/j.jksuci.2018.09.021

Cited by 105 publications

(80 citation statements)

References 64 publications

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“…Cloud computing architecture is depicted in Figure 31. Infrastructure, Data storage, resource sharing, and software access are the services offered by service providers [250]. Cloud computing consists of following entities [251]: 1.…”

Section: Cloud Computingmentioning

confidence: 99%

An Empirical Study on System Level Aspects of Internet of Things (IoT)

2020

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Internet of Things (IoT) is an integration of the Sensor, Embedded, Computing, and Communication technologies. The purpose of the IoT is to provide seamless services to anything, anytime at any place. IoT technologies play a crucial role everywhere, which brings the fourth revolution of disruptive technologies after the internet and Information and Communication Technology (ICT). The Research & Development community has predicted that the impact of IoT will be more than the internet and ICT on society, which improves the wellbeing of society and industries. Addressing the predominant system-level design aspects like energy efficiency, robustness, scalability, interoperability, and security issues result in the use of a potential IoT system. This paper presents the current state of art of the functional pillars of IoT and its emerging applications to motivate academicians and researches to develop real-time, energy-efficient, scalable, reliable, and secure IoT applications. This paper summarizes the architecture of IoT, with the contemporary status of IoT architectures. Highlights of the IoT system-level issues to develop more advanced real-time IoT applications have been discussed. Millions of devices exchange information using different communication standards, and interoperability between them is a significant issue. This paper provides the current status of the communication standards and application layer protocols used in IoT with the detailed analysis. The computing paradigms like Cloud, Cloudlet, Fog, and Edge computing facilitate IoT with various services like data offloading, resource and device management, etc. In this paper, an exhaustive analysis of Edge Computing in IoT with different edge computing architectures and existing status are deliberated. The widespread adoption of IoT in society has resulted in privacy and security issues. This paper emphasizes on analyzing the security challenges, privacy and security threats, conventional mitigation techniques, and further scope for IoT security. The features like fewer memory footprints, scheduling, real-time task execution, fewer interrupt, and thread switching latency of Real-Time Operating Systems (RTOS) enables the development of time critical IoT applications. Also, this review offers the analysis of the RTOS's suitable for IoT with the current status and networking stack. Finally, open research issues in IoT system development are discussed.

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Section: Cloud Computingmentioning

confidence: 99%

An Empirical Study on System Level Aspects of Internet of Things (IoT)

2020

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“…-Retry [18], [19]. Performing the same computation with new measurements if the first computation resulted in an undesired system state or in an error.…”

Section: B Mitigationmentioning

confidence: 99%

“…Security or other policies can be applied dynamically based on the type of attack, e. g., DoS or masquerading, that is detected. -Rescue Workflow [18], [19]. A workflow can be used to describe tasks with their dependencies to each other.…”

Section: B Mitigationmentioning

confidence: 99%

REMIND: A Framework for the Resilient Design of Automotive Systems

Rosenstatter

Strandberg

Jolak

et al. 2020

2020 IEEE Secure Development (SecDev)

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In the past years, great effort has been spent on enhancing the security and safety of vehicular systems. Current advances in information and communication technology have increased the complexity of these systems and lead to extended functionalities towards self-driving and more connectivity. Unfortunately, these advances open the door for diverse and newly emerging attacks that hamper the security and, thus, the safety of vehicular systems. In this paper, we contribute to supporting the design of resilient automotive systems. We review and analyze scientific literature on resilience techniques, fault tolerance, and dependability. As a result, we present the REMIND resilience framework providing techniques for attack detection, mitigation, recovery, and resilience endurance. Moreover, we provide guidelines on how the REMIND framework can be used against common security threats and attacks and further discuss the trade-offs when applying these guidelines.

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“…• Rescue workflow: This technique allows the process to continue its execution even after the failure has occurred and this policy continues up to the point where for the process it is no longer possible to proceed further without mending or recovering the task that failed in between [1].…”

Section: User-defined Exception Handlingmentioning

confidence: 99%

“…It provides various features such as connectivity, high performance, reliability, pay-as-you-go, interactivity, ease of programmability, efficiency, scalability, elasticity and management of large amount of data and there by transforming Information Technology from a product to a service. [1] Fault tolerance refers to a technique of system design that lets a system to keep working when one of its parts fails or it can be explained as a capacity of a system to react quickly to an unexpected equipment or programming break down. If the system is not completely operational, fault tolerance solutions may allow a system to continue operating at lower capacity rather than shutting down completely following a failure.…”

Section: Introductionmentioning

confidence: 99%

Reliability of Fault Tolerance in Cloud using Machine Learning Algorithm

Krishna*¹,

Niveditha²,

Mayuri³

2019

IJITEE

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The basic fault tolerance issues seen in cloud computing are identification and recovery. To fight with these issues, so many fault tolerance methods have been designed to decrease the faults. However, due to the reliability and web based service giving behavior, fault tolerance in cloud computing will be a huge challenge. The present model is not just on tolerating faults but also to decrease the possibility of future faults as well[4].The fault tolerance deals with the exact and constant operation of the fault segments. The processing on computing nodes can be done remotely in the real time cloud applications, so there could be more possibilities of errors. Hence there lies an immense necessity for fault tolerance to attain consistency to the real time computing on cloud infrastructure. The “fault tolerance” can be explained through fault processing that have two basic stages. The stages are (i) The effective error processing stage which is used to intended for carrying the “effective error” back to inactive state, i.e., before the error occurred (ii) The latent error processing stage intended for guaranteeing that the fault does not get effective once again.

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A survey of fault tolerance in cloud computing

Cited by 105 publications

References 64 publications

An Empirical Study on System Level Aspects of Internet of Things (IoT)

An Empirical Study on System Level Aspects of Internet of Things (IoT)

REMIND: A Framework for the Resilient Design of Automotive Systems

Reliability of Fault Tolerance in Cloud using Machine Learning Algorithm

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