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.

By switching the computational load from mobile devices to the cloud, Mobile Cloud Computing (MCC) allows mobile devices to offer a wider range of functionalities. There are several issues in using mobile devices as resource providers, including unstable wireless connections, limited energy capacity, and frequent location changes. Fault tolerance and reliable resource allocation are among the challenges encountered by mobile service providers in MCC. In this paper, a new reliable resource allocation and Fault tolerance mechanism is proposed in order to apply a fully distributed resource allocation algorithm without exploiting any central component. The objective is to improve the reliability of mobile resources. The proposed approach involves two steps: (1) Predicting device status by gathering contextual information and applying TOPSIS to prevent Faults caused by volatility of mobile devices, and (2) Adapting replication and checkpointing methods to Fault tolerance. A context-aware reliable offloading middleware is developed to collect contextual information and manage the offloading process. To evaluate the proposed method, several experiments are run in a real environment. The results indicate improvements in success rates, completion time, and energy consumption for tasks with high computational loads.

Unmanned aerial vehicles, particularly quadcopters, have gained widespread popularity across various applications. However, their operation is susceptible to Faults, which can compromise stability and performance. This paper introduces a novel Multidimensional Sliding Mode Control (MSMC) strategy for quadcopters, designed to enhance Fault tolerance and overall system robustness. The proposed approach incorporates advanced Fault detection and isolation algorithms, enabling real-time identification and mitigation of diverse Fault scenarios. Extensive simulations and experimental evaluations demonstrate the MSMC strategy's superiority over several existing Fault-tolerant control techniques, achieving at least 18.47% higher accuracy in Fault damping. Additionally, the sliding mode control system exhibits improved stability characteristics, with a response time reduction of at least 6.45% compared to conventional methods. The robustness and adaptability of the MSMC make it a promising solution for ensuring safe and reliable quadcopter operations under various Fault conditions, paving the way for enhanced performance and increased operational safety across a wide range of applications.

In this paper, an efficient Fault-tolerant routing algorithm for Mobile Ad-hoc Networks (MANETs) is presented. The proposed algorithm increases the network Fault-tolerance using natural redundancy of Ad-hoc networks. This algorithm is carried out in two stages; 1) the selection of backup nodes 2) the selection of backup route(s). In the first stage, the proposed algorithm chooses nodes with the same path as backup nodes. Prediction and diagnosis of nodes paths is performed through backup tables. Since the selection of backup nodes is fulfilled, the proposed algorithm begins Fault-tolerance routing. For this purpose, initially the proposed algorithm provides the main route between each pair of source & destination nodes based on DSR routing algorithm. Then, from a destination node towards a source node, the backup route(s) is established between the chosen backup nodes in the first stage. Experimental results taken from NS-2 simulator demonstrate that in comparison with previous methods the proposed increases; 1) 10% the package delivery ratio against the percentages of Faulty nodes and, 2) 22% package delivery ratio against the pause time of various mobile nodes.

Cloud computing is the latest technology that involves distributed computation over the Internet. It meets the needs of users through sharing resources and using virtual technology. The workflow user applications refer to a set of tasks to be processed within the cloud environment. Scheduling algorithms have a lot to do with the efficiency of cloud computing environments through selection of suitable resources and assignment of workflows to them. Given the factors affecting their efficiency, these algorithms try to use resources optimally and increase the efficiency of this environment. The palbimm algorithm provides a scheduling method that meets the majority of the requirements of this environment and its users. In this article, we improved the efficiency of the algorithm by adding Fault tolerance capability to it. Since this capability is used in parallel with task scheduling, it has no negative impact on the makespan. This is supported by simulation results in CloudSim environment.

Nowadays, the world of communication and information has undergone many changes, the rapidly growing trend of computer systems in terms of computing and storage and retrieval methods on the one hand and on the other hand a slow or almost constant trend in computer networks and non-response to The current needs of companies, organizations, telecommunication service providers as well as network designers face a series of limitations such as complexity, lack of scalability and lack of coordination between market needs and network capabilities and the introduction of cloud services and virtual servers. Network designers have taken a big step forward in the development of networks, and the solution to achieve this progress in networks is the use of software-based networks. In recent years, despite much research in the field of this type of network, there is still a need for optimizations in this area. One of the challenges that currently needs work and development is the issue of Fault tolerance and failure in these networks. In this paper, various failure tolerance methods in software-defined networks are introduced.