Efficient Fault Tolerance Research Articles

Designing an efficient fault tolerance D-latch based on quantum-dot cellular automata nanotechnology

Recently, Complementary Metal-Oxide-Semiconductor (CMOS) technology is limited by many barriers such as short channel effects and high power dissipation. Therefore, many alternatives are proposed to solve these shortages. One of the potential alternatives to CMOS is Quantum-dot Cellular Automaton (QCA) where binary information is encoded by using the electron location in a square cell. However, three types of fault (cell misalignment, cell missing, and cell dislocation) may cause the failure of the QCA-based designs. On the other hand, D-latch is one of the basic circuits in designing larger components such as counters and memories. Therefore, in this paper, a new fault-tolerance QCA-based D-latch is proposed and its performance is evaluated. The obtained results using QCADesigner have revealed that the proposed design produce correct output and thereby can tolerate 86% single-cell omission defects. Also, it has acceptable performance regarding the two and three cellular defects.

Fuzzy Informer Homed Routing Protocol for Wireless Sensor Network

A wireless sensor network consists of several sensor nodes. Sensor nodes collaborate to collect meaningful environmental information and send them to the base station. During these processes, nodes are prone to failure, due to the energy depletion, hardware or software failure, etc. Therefore, fault tolerance and energy efficiency are two important objectives for reliable packet delivery. To address these objectives a novel method called fuzzy informer homed routing protocol is introduced. The proposed method tries to distribute the workload between every sensor node. A fuzzy logic approach is used to handle uncertainties in cluster head communication range estimation. The simulation results show that the proposed method can significantly reduce energy consumption as compared with IHR and DHR protocols. Furthermore, results revealed that it performs better than IHR and DHR protocols in terms of first node dead and half of the nodes alive, throughput and total remaining energy. It is concluded that the proposed protocol is a stable and energy efficient fault tolerance algorithm for wireless sensor networks.

Fuzzy Informer Homed Routing Protocol for Wireless Sensor Network

A wireless sensor network consists of several sensor nodes. Sensor nodes collaborate to collect meaningful environmental information and send them to the base station. During these processes, nodes are prone to failure, due to the energy depletion, hardware or software failure, etc. Therefore, fault tolerance and energy efficiency are two important objectives for reliable packet delivery. To address these objectives a novel method called fuzzy informer homed routing protocol is introduced. The proposed method tries to distribute the workload between every sensor node. A fuzzy logic approach is used to handle uncertainties in cluster head communication range estimation. The simulation results show that the proposed method can significantly reduce energy consumption as compared with IHR and DHR protocols. Furthermore, results revealed that it performs better than IHR and DHR protocols in terms of first node dead and half of the nodes alive, throughput and total remaining energy. It is concluded that the proposed protocol is a stable and energy efficient fault tolerance algorithm for wireless sensor networks.

Review on failure forecast in cloud for a fault tolerant system

Cloud Computing is an increasingly popular computer paradigm constituting a large infrastructure involving storage, memory, servers and applications accessible via computer network. The cloud system design aims to provide on-demand services with scalability on diverse resources to ensure efficient resource utilization in addition to effectiveness. As cloud is a service-oriented infrastructure, it is critically imperative that the system is highly reliable to meet the Service Level Agreement (SLA). To achieve reliability, cloud requires a very efficient fault tolerance mechanism. Serviceability and reliability is impacted by any failure in the system. Prior prediction of faults in the system helps in overcoming failures. The Fault Tolerance in cloud involves ascertaining the resource fitness to execute scheduled task. The process involves prior screening of resources against various tasks as part of scheduling process. The scheduling process relies significantly on the virtualization of resources to maintain high efficiency.

Versionized process based on non-volatile random-access memory for fine-grained fault tolerance

Non-volatile random-access memory (NVRAM) technology is maturing rapidly and its byte-persistence feature allows the design of new and efficient fault tolerance mechanisms. In this paper we propose the versionized process (VerP), a new process model based on NVRAM that is natively non-volatile and fault tolerant. We introduce an intermediate software layer that allows us to run a process directly on NVRAM and to put all the process states into NVRAM, and then propose a mechanism to versionize all the process data. Each piece of the process data is given a special version number, which increases with the modification of that piece of data. The version number can effectively help us trace the modification of any data and recover it to a consistent state after a system crash. Compared with traditional checkpoint methods, our work can achieve fine-grained fault tolerance at very little cost.

Fault Detection and Fault Tolerance Mechanism for DC/DC Converters in Microgrids

Abstract A solution for modelling and controlling the operation of DC/DC converters, both in normal and in fault regime, is proposed. The proposed converter model is based on ARX structure with variable coefficients. Feedforward fully connected neural network are used in order to generate the appropriate model coefficients for variable duty cycle. A control structure that can be used both to detect the faults and to reject their effect is introduced. The proposed structure contains a compensator whose action assures the avoidance of the unstable regime when the converter parameters change from their nominal values, acting as an efficient fault tolerance mechanism. The proposed approach is directed toward developing algorithms suitable for real-time implementation on 32 bit ARM processors.

An Efficient Fault Tolerance Technique for Through-Silicon-Vias in 3-D ICs

Three-dimensional integrated circuits (3D-ICs) based on Through-Silicon-Vias (TSVs) interconnection technology appeared as a viable solution to overcome problems of cost, reliability, yield and stacking area. In order to be commercially feasible, the 3D-IC yield must be as high as possible, which requires a tested and reparable TSVs. To overpass this challenge, an integration of interconnect built-in self-test (IBIST) methodology for 3D-IC is given in the aims to test the defectives TSVs. Once the interconnection has been tested, the result extracted from IBIST initiate the repairing defectives TSVs based on the built-in self-repair (BISR) structure. This paper superposed two fault tolerance techniques in particularly the redundant TSV and the time division multiplexing access (TDMA) in case of multi defectives TSV. This novel repair architecture increase the yield of 3D-ICs in a high failure rate. It leads to 100% reparability for 30% failure rate. A parallel processing approach of the proposed structure is presented to accelerate the test and repair operations. Achieved experimental results with the proposed methodology scheme show a good performance in terms of repair rate and yield.

RP2: a high-performance data center network architecture using projective planes

A data center network (DCN) plays a crucial role in data center communications and provides the infrastructure for cloud computing services and data-intensive applications in a cloud data center. Network performance is determined by DCN architecture, whose effective design critically depends on ensuring low cost, high availability, and high scalability. Currently, DCNs face undesirable trade-off between high availability, scalability and performance. In this paper, first, we propose a hybrid projective plane-based DCN architecture called the recursive projective plane (RP2). RP2 is underlain by the use of multi-port servers and mini-switches in DCN development and the application of a recursive method for scaling up a data center. It deals with the construction and properties of combinatorial designs with arrangements that satisfy the concepts of an efficient DCN. Then, we propose single-path and multi-path routing algorithms for RP2. Theoretical analysis indicates that RP2 provides a scalable architecture with a low diameter, wherein the maximum shortest distance between any pair of servers can be limited by level of extension. An empirical simulation that compares BCube, DCell, and RP2 indicates that under 0–20% server failure, RP2 exhibits efficient fault tolerance. Despite the higher cost and wiring complexity of RP2, it constitutes a high-performance and highly scalable DCN architecture.

Angel: a new large-scale machine learning system

Abstract Machine Learning (ML) techniques now are ubiquitous tools to extract structural information from data collections. With the increasing volume of data, large-scale ML applications require an efficient implementation to accelerate the performance. Existing systems parallelize algorithms through either data parallelism or model parallelism. But data parallelism cannot obtain good statistical efficiency due to the conflicting updates to parameters while the performance is damaged by global barriers in model parallel methods. In this paper, we propose a new system, named Angel, to facilitate the development of large-scale ML applications in production environment. By allowing concurrent updates to model across different groups and scheduling the updates in each group, Angel can achieve a good balance between hardware efficiency and statistical efficiency. Besides, Angel reduces the network latency by overlapping the parameter pulling and update computing and also utilizes the sparseness of data to avoid the pulling of unnecessary parameters. We also enhance the usability of Angel by providing a set of efficient tools to integrate with application pipelines and provisioning efficient fault tolerance mechanisms. We conduct extensive experiments to demonstrate the superiority of Angel.

Proactive Fault Tolerance Algorithm for Job Scheduling in Computational Grid

Grid use huge number of dynamic, distributed & heterogeneous resources under different organizations domain to executing user applications. Working with these resources, applications face problems due to occurrence of faults. There are number of different faults that occur due to many problems. Therefore grid computing needs an efficient fault tolerance mechanism. This fault tolerance makes the grid system capable to work correctly even in the presence of faults. In this paper we have study various kinds of faults and reasons for occurrence. With this, also study various kinds of existing fault tolerance techniques. We devise a strategy, based on proactive fault tolerance and take appropriate step, if any possibility for fault occurrence. Scheduling of task on available resources, which is provided by GIS consider previous history of these resources. This will decrease the probability of faults, execution time, and increase the execution rate. Proposed strategy also uses technique of check pointing to reduce execution cost. To implement proposed strategy GridSim toolkit is used for simulation

Fault Tolerance Approach Based on Checkpointing towards Dependable Business Processes

The Business Process Execution Language (BPEL) has become one of the predominant standards for Web services compositions oriented to business processes. An important capability of BPEL is that it allows processes to interact synchronously/asynchronously with other BPEL processes and/or choreographies at large-scale. However, it is a well-known fact that a greater system complexity leads to a greater probability of software/hardware failures. To attack the problem of failures for interactive business processes more efficient fault tolerance mechanisms are need. Nowadays there exist sophisticated solutions that tackle business processes fault tolerance, however, present drawbacks such as they affect the systems performance, they have a high implementation costs, they can jeopardize the scalability of the system and/or they do not support asynchronous BPEL communication among processes. In this paper, we propose to attack the dependability problem in a distributed manner, a fault tolerant solution based on communication-induced checkpointing (CiC) for interactive BPEL processes.

Online Fault Tolerance Technique for TSV-Based 3-D-IC

This brief presents the design, validation, and evaluation of an efficient online fault tolerance technique for fault detection and recovery in presence of three through-silicon-vias (TSV) defects: 1) voids; 2) delamination between TSV and landing pad; and 3) TSV short-to-substrate. The technique employs transition delay test for TSV fault detection. Fault recovery is achieved by employing redundant TSVs and rerouting signals to fault-free TSVs. This technique is efficient because it requires a small ( $2\times $ number of TSVs per group) number of clock cycles for fault detection and recovery. Synthesis results using 130-nm design library show that 100% repair capability can be achieved with low area overhead (4% for the best case).

CDMCR: multi‐level fault‐tolerant system for distributed applications in cloud

AbstractCloud provides users with a new model of utilizing the computing infrastructure with the ability to perform parallel and distributed computations using elastic virtual cluster. However, the multi‐level and complex features make cloud computing system more prone to failure. In this paper, we present a multi‐level fault‐tolerant system for distributed applications in cloud named Distributed‐application oriented Multi‐level Checkpoint/Restart for Cloud (CDMCR). The CDMCR system backups the complete state of applications periodically with a snapshot‐based distributed checkpointing protocol, including file system state. Thus, we cannot only recover processes but also rollback data. A multi‐level recovery strategy is proposed, which includes process‐level recovery, virtual machine recreation, and host rescheduling, enabling comprehensive and efficient fault tolerance for different components in cloud. We deploy CDMCR as PaaS, so that users can be liberated from node management and system configuration and get access to fault‐tolerant service conveniently. We have implemented this system based on the Xen virtualization platform and the OpenNebula cloud platform. Experiments on the prototype demonstrate the correctness of the system. Analysis shows that CDMCR does not cause message loss or data loss, and the backup time remains nearly constant as the number of nodes increases on virtual cluster. Copyright © 2015 John Wiley & Sons, Ltd.

English

Cloud computing is upcoming a mainstream feature of information technology. More progressively enterprises deploy their software systems in the cloud environment. The applications in cloud are usually large scale and containing a lot of distributed cloud components. Building cloud applications is highly reliable for challenging and critical research issues. Information processing systems has increased the significance of its correct and continuous operation even in the presence of faulty components. To address this issue, proposes a cloud framework to build fault-tolerant cloud applications. We first propose fault detection algorithms to identify significant components from the huge amount of cloud components. Then, we present an efficient fault-tolerance strategy selection algorithm to determine the most suitable fault-tolerance strategy for each significant component. Software fault tolerance is widely adopted to increase the overall system reliability in critical applications. System reliability can be enhanced by employing functionally equivalent components to tolerate component failures. Fault-tolerance strategies introduced a three well- known techniques are in the following with formulas for calculating the failure probabilities of the fault-tolerant modules. Our work will mainly be driven toward the implementation of the framework to measure the strength of fault tolerance service and to make an in-depth analysis of the cost benefits among all the stakeholders. An algorithm is proposed to automatically determine an efficient fault-tolerance strategy for the significant cloud components. Using real failure traces and model, we evaluate the proposed resource provisioning policies to determine their performance, cost as well as cost efficiency. The experimental results show that by tolerating faults of a small part of the most important components, the reliability of cloud applications can be highly improved.

Private reliability environments for efficient fault-tolerance in CGRAs

In the era of platforms hosting multiple applications with variable reliability needs, worst-case platform-wide fault-tolerance decisions are neither optimal nor desirable. As a solution to this problem, designs commonly employ adaptive fault-tolerance strategies that provide each application with the reliability level actually needed. However, in the CGRA domain, the existing schemes either only allow to shift between different levels of modular redundancy (duplication, triplication, etc.) or protect only a particular region of a device (e.g. configuration memory, computation, or data memory). To complement these strategies, we propose private fault-tolerance environments which, in addition to modular redundancy, also provide low cost sub-modular (e.g. residue mod 3) redundancy capable of handling both permanent and temporary faults in configuration memory, computation, communication, and data memory. In addition, we also present adaptive configuration scrubbing techniques which prevent fault accumulation in the configuration memory. Simulation results using a few selected algorithms (FFT, matrix multiplication, and FIR filter) show that the approach proposed is capable of providing flexible protection with energy overhead ranging from 3.125 % to 107 % for different reliability levels. Synthesis results have confirmed that the proposed architecture reduces the area overhead for self-checking (58 %) and fault-tolerant (7.1 %) versions, compared to the state of the art adaptive reliability techniques.

Analyzing, modeling and evaluating dynamic adaptive fault tolerance strategies in cloud computing environments

Failures are normal rather than exceptional in cloud computing environments, high fault tolerance issue is one of the major obstacles for opening up a new era of high serviceability cloud computing as fault tolerance plays a key role in ensuring cloud serviceability. Fault tolerant service is an essential part of Service Level Objectives (SLOs) in clouds. To achieve high level of cloud serviceability and to meet high level of cloud SLOs, a foolproof fault tolerance strategy is needed. In this paper, the definitions of fault, error, and failure in a cloud are given, and the principles for high fault tolerance objectives are systematically analyzed by referring to the fault tolerance theories suitable for large-scale distributed computing environments. Based on the principles and semantics of cloud fault tolerance, a dynamic adaptive fault tolerance strategy DAFT is put forward. It includes: (i) analyzing the mathematical relationship between different failure rates and two different fault tolerance strategies, which are checkpointing fault tolerance strategy and data replication fault tolerance strategy; (ii) building a dynamic adaptive checkpointing fault tolerance model and a dynamic adaptive replication fault tolerance model by combining the two fault tolerance models together to maximize the serviceability and meet the SLOs; and (iii) evaluating the dynamic adaptive fault tolerance strategy under various conditions in large-scale cloud data centers and consider different system centric parameters, such as fault tolerance degree, fault tolerance overhead, response time, etc. Theoretical as well as experimental results conclusively demonstrate that the dynamic adaptive fault tolerance strategy DAFT has high potential as it provides efficient fault tolerance enhancements, significant cloud serviceability improvement, and great SLOs satisfaction. It efficiently and effectively achieves a trade-off for fault tolerance objectives in cloud computing environments.

Modelling and evaluating a high serviceability fault tolerance strategy in cloud computing environments

In this paper, the definitions of fault, error, and failure in a cloud are given and the principles for high fault tolerance objectives are systematically analysed by referring to the fault tolerance theories suitable for large–scale distributed computing environments. Based on the principles and semantics of cloud fault tolerance, a dynamic adaptive fault tolerance strategy DAFT is put forward. It includes: (1) analysing the mathematical relationship between different failure rates and checkpointing fault tolerance strategy; (2) building a dynamic adaptive checkpointing fault tolerance model to maximise the serviceability and meet the SLOs; and (3) evaluating the dynamic adaptive fault tolerance strategy under various conditions in large–scale cloud data centres and consider different system centric parameters, such as fault tolerance degree, fault tolerance overhead, etc. Theoretical as well as experimental results conclusively demonstrate that the dynamic adaptive fault tolerance strategy DAFT has high potential as it provides efficient fault tolerance enhancements.

The Study of Prediction Model Based on Morlet Wavelet Neural Network

Wavelet Neural Network (WNN) is a new form of neural network combined with the wavelet theory and artificial neural network. The wavelet neural network model based on Morlet wavelet and the corresponding learning algorithm were studied in this paper. And through learning the wavelet neural network model is applied to all kinds of engineering examples, it proved that the wavelet neural network prediction model which has a more flexible and efficient function approximation ability and strong fault tolerance, and with high predicting precision.

Minimum-Process Synchronous Checkpointing in Mobile Distributed Systems

Checkpointing is an efficient fault tolerance technique used in distributed systems. Due to the emerging challenges of the mobile distributed system as low bandwidth, mobility, lack of stable storage, frequent disconnections and limited battery life, the fault tolerance technique designed for distributed system can not directly implemented on mobile distributed systems(MDSs). This research paper presents an efficient low cost synchronous checkpointing algorithm which fit into the mobile environment.

Fault-tolerant de-Bruijn graph based multipurpose architecture and routing protocol for wireless sensor networks

As dense Wireless Sensor Networks (WSNs) are increasingly vulnerable to fault, network must continue processing data without affecting the faulty node. Fault aware routing is an effective way to mitigate such a scenario. To this end, we present a de-Bruijn graph based Multipurpose Architecture and Routing Protocol (MARP) which has all the properties of an efficient WSN. The MARP supports multicast routing, broadcasting, fault detection and efficient fault-tolerance. Its unique architecture makes it easily scalable and provides easy three-dimensional to two-dimensional mapping. Furthermore, we show that, depending on the fault-tolerance capability one wants, design requires higher redundancy. A small experiment of de-Bruijn graph based routing protocol is also presented with mica2 motes to check its feasibility in a real-life scenario.