REAPS: Quasi-active Fault Tolerance for Big Data Publish-Subscribe Systems

2021 ◽  
Author(s):  
Hang Nguyen ◽  
MYS Uddin ◽  
Nalini Venkatasubramanian
Keyword(s):  
Big Data ◽  
Fault Tolerance ◽  
Active Fault

scholarly journals Sensor-fault tolerance using robust MPC with set-based state estimation and active fault isolation

2016 ◽  
Vol 27 (8) ◽  
pp. 1260-1283 ◽  
Author(s):  
Feng Xu ◽  
Sorin Olaru ◽  
Vicenc Puig ◽  
Carlos Ocampo-Martinez ◽  
Silviu-Iulian Niculescu
Keyword(s):  
Fault Tolerance ◽  
State Estimation ◽  
Active Fault ◽  
Fault Isolation ◽  
Sensor Fault

scholarly journals Big Data using Cloud Computing - Opportunities for Small and Medium-sized Enterprises

2016 ◽  
Vol 4 (1) ◽  
pp. 129 ◽  
Author(s):  
Narasimha Rao Vajjhala ◽  
Ervin Ramollari
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Fault Tolerance ◽  
Competitive Advantage ◽  
Computer Architecture ◽  
Financial Resources ◽  
Future Research ◽  
Current Trends ◽  
Low Performance ◽  
Research Frontiers

Big Data has been listed as one of the current and future research frontiers by Gartner. Large-sized companies are already investing on and leveraging big data. Small-sized and medium-sized enterprises (SMEs) can also leverage big data to gain a strategic competitive advantage but are often limited by the lack of adequate financial resources to invest on the technology and manpower. Several big data challenges still exist especially in computer architecture that is CPU-heavy but I/O poor. Cloud computing eliminates the need to maintain expensive computing hardware and software. Cloud computing resources and techniques can be leveraged to address the traditional problems associated with fault tolerance and low performance causing bottlenecks to using big data. SMEs can take advantage of cloud computing techniques to avail the advantages of big data without significant investments in technology and manpower. This paper explores the current trends in the area of big data using cloud resources and how SMEs can take advantage of these technological trends. The results of this study will benefit SMEs in identifying and exploring possible opportunities and also understanding the challenges in leveraging big data.

Active fault tolerance control system of fuel cell hybrid city bus

2010 ◽  
Vol 35 (22) ◽  
pp. 12510-12520 ◽  
Author(s):  
Liangfei Xu ◽  
Jianqiu Li ◽  
Minggao Ouyang ◽  
Jianfeng Hua ◽  
Xiangjun Li
Keyword(s):  
Control System ◽  
Fuel Cell ◽  
Fault Tolerance ◽  
Cell Hybrid ◽  
Active Fault ◽  
City Bus ◽  
Tolerance Control ◽  
Fuel Cell Hybrid

scholarly journals Active versus passive fault-tolerant control of a redundant multirotor UAV

2019 ◽  
Vol 124 (1273) ◽  
pp. 385-408
Author(s):  
M. Saied ◽  
B. Lussier ◽  
I. Fantoni ◽  
H. Shraim ◽  
C. Francis
Keyword(s):  
Fault Tolerance ◽  
Fault Detection ◽  
Active Fault ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Fault Detection And Isolation ◽  
Detection Scheme ◽  
Redundancy Management ◽  
Model Free

ABSTRACTThis paper considers actuator redundancy management for a redundant multirotor Unmanned Aerial Vehicle (UAV) under actuators failures. Different approaches are proposed: using robust control (passive fault tolerance), and reconfigurable control (active fault tolerance). The robust controller is designed using high-order super-twisting sliding mode techniques, and handles the failures without requiring information from a Fault Detection scheme. The Active Fault-Tolerant Control (AFTC) is achieved through redistributing the control signals among the healthy actuators using reconfigurable multiplexing and pseudo-inverse control allocation. The Fault Detection and Isolation problem is also considered by proposing model-based and model-free modules. The proposed techniques are all implemented on a coaxial octorotor UAV. Different experiments with different scenarios were conducted for the validation of the proposed strategies. Finally, advantages, disadvantages, application considerations and limitations of each method are examined through quantitative and qualitative studies.

Database Sharding

2015 ◽  
Vol 5 (2) ◽  
pp. 36-52 ◽  
Author(s):  
Sikha Bagui ◽  
Loi Tang Nguyen
Keyword(s):  
Big Data ◽  
Fault Tolerance ◽  
Distributed Database ◽  
Database System ◽  
High Availability ◽  
Effective Management ◽  
Large Databases ◽  
Distributed Database System ◽  
Horizontal Partitioning

In this paper, the authors present an architecture and implementation of a distributed database system using sharding to provide high availability, fault-tolerance, and scalability of large databases in the cloud. Sharding, or horizontal partitioning, is used to disperse the data among the data nodes located on commodity servers for effective management of big data on the cloud.

scholarly journals Evaluation of Seismic Performance of Reinforced Concrete Frame Structures in the Context of Big Data

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Du Guangqian ◽  
Zheng Meng ◽  
Wang Shijie
Keyword(s):  
Big Data ◽  
Reinforced Concrete ◽  
Fault Tolerance ◽  
Seismic Performance ◽  
Frame Structures ◽  
Cloud Platform ◽  
Reinforced Concrete Frame ◽  
Concrete Frame ◽  
High Scalability ◽  
Reinforced Concrete Frame Structures

In the era of big data, the efficient use of idle data in reinforced concrete structures has become a key issue in optimizing seismic performance evaluation methods for building structures. In this paper, based on the evaluation method of structural displacement seismic performance and based on the characteristics of high scalability and high fault tolerance of the cloud platform, the open source distributed and storage features of the Hadoop architecture cloud platform are introduced as a subproject of Apache Nutch project, Hadoop cloud platform. With features such as high scalability, high fault tolerance, and flexible deployment, the storage platform is secure, stable, and reliable. From the evaluation of the seismic performance of newly-built buildings and existing damaged buildings, according to the structural strength-ductility theory of the structure, the building structure resists earthquakes with its strength and ductility and buildings are divided into four categories. Due to the influence of time or seismic damage on the structure of reinforced concrete frame structures, their material properties are often deteriorating. Using the distributed computing design concept to efficiently process big data, a dynamic evaluation model for the seismic performance of reinforced concrete frame structures is established. A project of a 10-story reinforced concrete frame structure was selected for calculation and analysis; the engineering example was used to verify the accuracy and efficiency of the model, and the seismic performance of the floor was analyzed. It can be seen that the initial stiffness index of the structure is not sensitive to the damage location of the structure. The platform based on the concept of distributed computing big data processing can effectively improve the efficiency and accuracy of the evaluation of reinforced concrete frame structures.

Current Sensor Active Fault Tolerance Control Based on Feedback Gain Reconfiguration

2014 ◽  
Vol 511-512 ◽  
pp. 1012-1016 ◽  
Author(s):  
Zhi Qiang Wang ◽  
Xiao Long Li ◽  
Qing Zhen Wang
Keyword(s):  
Fault Tolerance ◽  
Fault Diagnosis ◽  
Control Strategy ◽  
Active Fault ◽  
State Observer ◽  
Current Sensor ◽  
Feedback Gain ◽  
Maglev Train ◽  
Tolerance Strategy ◽  
Tolerance Control

For the failure of current sensor on maglev train, an active fault tolerance control strategy based on feedback gain reconfiguration is proposed. Fault diagnosis unit based on state observer is designed to detect the output of current sensor, the diagnosis result is used to switch the control strategy. Simulation result indicates that the fault tolerance strategy meets the demands of the system.

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