Efficient Fault-Tolerant Transactions for Distributed Graph Database

2019 ◽  
Vol 1 (2) ◽  
pp. 14-20
Author(s):  
Ray Neiheiser ◽  
Roland Schmitz ◽  
Luciana Rech ◽  
Manfredo Manfredini
Keyword(s):  
Social Networks ◽  
Fault Tolerance ◽  
Linked Data ◽  
Fault Tolerant ◽  
Graph Database ◽  
Graph Databases ◽  
Massive Growth ◽  
Atomic Broadcast ◽  
A Performance

Through the ongoing trend in graph technologies due to the massive growth of linked data produced by social networks graph databases gained popularity. Replication, a common approach to increase availability in databases, is also used by diverse graph database solutions. Few approaches implementing fault-tolerance in graph databases have been proposed yet.This paper considers deferred update replication using atomic broadcast in order to implement fault-tolerance in distributed graph databases. The main contribution of this paper is a deferred update algorithm adapted to graph databases offering a more scalable and faster solution, showing a performance advantage of over 30\% compared to existing approaches.

Designing Graph Databases With GRAPHED

2019 ◽  
Vol 30 (1) ◽  
pp. 41-60 ◽  
Author(s):  
Gustavo Cordeiro Galvão Van Erven ◽  
Rommel Novaes Carvalho ◽  
Waldeyr Mendes Cordeiro da Silva ◽  
Sergio Lifschitz ◽  
Harley Vera-Olivera ◽  
...  
Keyword(s):  
Social Networks ◽  
Data Model ◽  
Biological Network ◽  
Database Systems ◽  
Graph Database ◽  
Graph Databases ◽  
Database Modeling ◽  
Schema Design ◽  
Conceptual Data ◽  
The Relationship

In recent years, graph database systems have become very popular and been deployed mainly in situations where the relationship between data is significant, such as in social networks. Although they do not require a particular schema design, a data model contributes to their consistency. Designing diagrams is an approach to satisfying this demand for a conceptual data model. While researchers and companies have been developing concepts and notations for graph database modeling, their notations focus on their specific implementations. In this article, the authors propose a diagram to address this lack of a generic and comprehensive notation for graph databases modeling, named GRAPHED (Graph Description Diagram for Graph Databases). The authors verified the effectiveness and compatibility of GRAPHED in two case studies: fraud identification, and a biological network model.

Technical Survey Graph Databases and Applications

2015 ◽  
Vol 09 (04) ◽  
pp. 523-545 ◽  
Author(s):  
Shao-Ting Wang ◽  
Jennifer Jin ◽  
Pete Rivett ◽  
Atsushi Kitazawa
Keyword(s):  
Social Networks ◽  
Relational Databases ◽  
Query Languages ◽  
The Internet ◽  
Complex Data ◽  
Graph Database ◽  
Graph Databases ◽  
Amount Of Information ◽  
Related Application ◽  
Fast Access

Graph databases can be defined as databases that use graph structures with nodes, edges and properties to store data. Semantic queries and graph-oriented operations are used to access them. With a rapidly growing amount of information on the Internet in recent years, relational databases suffer performance degradation as a large number of nodes are added due to the number of entries in join tables. Therefore, based on the network nature of Internet activities, graph databases are designed for fast access to complex data found in social networks, recommendation engines and networked system. The main objective of this survey is to present the work that has been done in the area of graph database, including query languages, processing, and related application.

Fault Tolerant Guidance of Under-Actuated Satellite Formation Flying Using Inter-Vehicle Coulomb Force

2019 ◽  
Vol 2 (1) ◽  
pp. 43-52
Author(s):  
Alireza Alikhani ◽  
Safa Dehghan M ◽  
Iman Shafieenejad
Keyword(s):  
Fault Tolerance ◽  
Formation Flying ◽  
Fault Tolerant ◽  
Coulomb Force ◽  
Control Law ◽  
Triangular Form ◽  
Satellite Formation Flying ◽  
Satellite Formation ◽  
Guidance Law ◽  
Tolerance Approach

In this study, satellite formation flying guidance in the presence of under actuation using inter-vehicle Coulomb force is investigated. The Coulomb forces are used to stabilize the formation flying mission. For this purpose, the charge of satellites is determined to create appropriate attraction and repulsion and also, to maintain the distance between satellites. Static Coulomb formation of satellites equations including three satellites in triangular form was developed. Furthermore, the charge value of the Coulomb propulsion system required for such formation was obtained. Considering Under actuation of one of the formation satellites, the fault-tolerance approach is proposed for achieving mission goals. Following this approach, in the first step fault-tolerant guidance law is designed. Accordingly, the obtained results show stationary formation. In the next step, tomaintain the formation shape and dimension, a fault-tolerant control law is designed.

Fault Tolerant Reliable Protocol (FTRP) Performance Evaluation in Wireless Sensor Networks: An Extensitive Study

2019 ◽  
pp. 1-36
Keyword(s):  
Wireless Sensor Networks ◽  
Fault Tolerance ◽  
Sensor Networks ◽  
Fault Tolerant ◽  
Cluster Head ◽  
Biological Data ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Good Performer ◽  
Wide Range

Fault Tolerant Reliable Protocol (FTRP) is proposed as a novel routing protocol designed for Wireless Sensor Networks (WSNs). FTRP offers fault tolerance reliability for packet exchange and support for dynamic network changes. The key concept used is the use of node logical clustering. The protocol delegates the routing ownership to the cluster heads where fault tolerance functionality is implemented. FTRP utilizes cluster head nodes along with cluster head groups to store packets in transient. In addition, FTRP utilizes broadcast, which reduces the message overhead as compared to classical flooding mechanisms. FTRP manipulates Time to Live values for the various routing messages to control message broadcast. FTRP utilizes jitter in messages transmission to reduce the effect of synchronized node states, which in turn reduces collisions. FTRP performance has been extensively through simulations against Ad-hoc On-demand Distance Vector (AODV) and Optimized Link State (OLSR) routing protocols. Packet Delivery Ratio (PDR), Aggregate Throughput and End-to-End delay (E-2-E) had been used as performance metrics. In terms of PDR and aggregate throughput, it is found that FTRP is an excellent performer in all mobility scenarios whether the network is sparse or dense. In stationary scenarios, FTRP performed well in sparse network; however, in dense network FTRP’s performance had degraded yet in an acceptable range. This degradation is attributed to synchronized nodes states. Reliably delivering a message comes to a cost, as in terms of E-2-E. results show that FTRP is considered a good performer in all mobility scenarios where the network is sparse. In sparse stationary scenario, FTRP is considered good performer, however in dense stationary scenarios FTRP’s E-2-E is not acceptable. There are times when receiving a network message is more important than other costs such as energy or delay. That makes FTRP suitable for wide range of WSNs applications, such as military applications by monitoring soldiers’ biological data and supplies while in battlefield and battle damage assessment. FTRP can also be used in health applications in addition to wide range of geo-fencing, environmental monitoring, resource monitoring, production lines monitoring, agriculture and animals tracking. FTRP should be avoided in dense stationary deployments such as, but not limited to, scenarios where high application response is critical and life endangering such as biohazards detection or within intensive care units.

scholarly journals Fault Analysis and Non-Redundant Fault Tolerance in 3-Level Double Conversion UPS Systems Using Finite-Control-Set Model Predictive Control

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2210
Author(s):  
Luís Caseiro ◽  
André Mendes
Keyword(s):  
Fault Tolerance ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Fault Tolerant ◽  
Finite Control ◽  
Control Set ◽  
Corrective Actions ◽  
Uninterruptible Power ◽  
Hardware Reconfiguration ◽  
Redundant Fault

Fault-tolerance is critical in power electronics, especially in Uninterruptible Power Supplies, given their role in protecting critical loads. Hence, it is crucial to develop fault-tolerant techniques to improve the resilience of these systems. This paper proposes a non-redundant fault-tolerant double conversion uninterruptible power supply based on 3-level converters. The proposed solution can correct open-circuit faults in all semiconductors (IGBTs and diodes) of all converters of the system (including the DC-DC converter), ensuring full-rated post-fault operation. This technique leverages the versatility of Finite-Control-Set Model Predictive Control to implement highly specific fault correction. This type of control enables a conditional exclusion of the switching states affected by each fault, allowing the converter to avoid these states when the fault compromises their output but still use them in all other conditions. Three main types of corrective actions are used: predictive controller adaptations, hardware reconfiguration, and DC bus voltage adjustment. However, highly differentiated corrective actions are taken depending on the fault type and location, maximizing post-fault performance in each case. Faults can be corrected simultaneously in all converters, as well as some combinations of multiple faults in the same converter. Experimental results are presented demonstrating the performance of the proposed solution.

scholarly journals Advantages of using graph databases to explore chromatin conformation capture experiments

2021 ◽  
Vol 22 (S2) ◽  
Author(s):  
Daniele D’Agostino ◽  
Pietro Liò ◽  
Marco Aldinucci ◽  
Ivan Merelli
Keyword(s):  
Web Application ◽  
High Throughput Sequencing ◽  
Cell Types ◽  
Graph Database ◽  
Graph Databases ◽  
Sources Of Information ◽  
Chromosome Conformation ◽  
Wide Scale ◽  
User Friendly ◽  
Different Cell Types

Abstract Background High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of DNA interactions and 3D chromosome folding at the genome-wide scale. Usually, these data are represented as matrices describing the binary contacts among the different chromosome regions. On the other hand, a graph-based representation can be advantageous to describe the complex topology achieved by the DNA in the nucleus of eukaryotic cells. Methods Here we discuss the use of a graph database for storing and analysing data achieved by performing Hi-C experiments. The main issue is the size of the produced data and, working with a graph-based representation, the consequent necessity of adequately managing a large number of edges (contacts) connecting nodes (genes), which represents the sources of information. For this, currently available graph visualisation tools and libraries fall short with Hi-C data. The use of graph databases, instead, supports both the analysis and the visualisation of the spatial pattern present in Hi-C data, in particular for comparing different experiments or for re-mapping omics data in a space-aware context efficiently. In particular, the possibility of describing graphs through statistical indicators and, even more, the capability of correlating them through statistical distributions allows highlighting similarities and differences among different Hi-C experiments, in different cell conditions or different cell types. Results These concepts have been implemented in NeoHiC, an open-source and user-friendly web application for the progressive visualisation and analysis of Hi-C networks based on the use of the Neo4j graph database (version 3.5). Conclusion With the accumulation of more experiments, the tool will provide invaluable support to compare neighbours of genes across experiments and conditions, helping in highlighting changes in functional domains and identifying new co-organised genomic compartments.

scholarly journals Applying graph database technology for analyzing perturbed co-expression networks in cancer

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Claire M Simpson ◽  
Florian Gnad
Keyword(s):  
Relational Databases ◽  
Molecular Mechanisms ◽  
Biological Data ◽  
Database Management System ◽  
Graph Database ◽  
Graph Databases ◽  
Graph Representations ◽  
Rnaseq Data ◽  
Database Technology ◽  
Speed Accuracy

Abstract Graph representations provide an elegant solution to capture and analyze complex molecular mechanisms in the cell. Co-expression networks are undirected graph representations of transcriptional co-behavior indicating (co-)regulations, functional modules or even physical interactions between the corresponding gene products. The growing avalanche of available RNA sequencing (RNAseq) data fuels the construction of such networks, which are usually stored in relational databases like most other biological data. Inferring linkage by recursive multiple-join statements, however, is computationally expensive and complex to design in relational databases. In contrast, graph databases store and represent complex interconnected data as nodes, edges and properties, making it fast and intuitive to query and analyze relationships. While graph-based database technologies are on their way from a fringe domain to going mainstream, there are only a few studies reporting their application to biological data. We used the graph database management system Neo4j to store and analyze co-expression networks derived from RNAseq data from The Cancer Genome Atlas. Comparing co-expression in tumors versus healthy tissues in six cancer types revealed significant perturbation tracing back to erroneous or rewired gene regulation. Applying centrality, community detection and pathfinding graph algorithms uncovered the destruction or creation of central nodes, modules and relationships in co-expression networks of tumors. Given the speed, accuracy and straightforwardness of managing these densely connected networks, we conclude that graph databases are ready for entering the arena of biological data.

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