Persistent Storage and Query of Expressive Ontology

2010 ◽  
Author(s):  
Yuxin Ye ◽  
Dantong Ouyang ◽  
Xuchu Dong
Keyword(s):  
Persistent Storage

scholarly journals Anti-Persistence on Persistent Storage

2016 ◽  
Author(s):  
Michael A. Bender ◽  
Jonathan W. Berry ◽  
Rob Johnson ◽  
Thomas M. Kroeger ◽  
Samuel McCauley ◽  
...  
Keyword(s):  
Persistent Storage

Techniques for efficiently allocating persistent storage

2003 ◽  
Vol 68 (2) ◽  
pp. 85-102 ◽  
Author(s):  
Arun Iyengar ◽  
Shudong Jin ◽  
Jim Challenger
Keyword(s):  
Persistent Storage

scholarly journals Design of a Resilient, High-Throughput, Persistent Storage System for the ATLAS Phase-II DAQ System

2021 ◽  
Vol 251 ◽  
pp. 04014
Author(s):  
Adam Abed Abud ◽  
Matias Bonaventura ◽  
Edoardo Farina ◽  
Fabrice Le Goff
Keyword(s):  
Performance Management ◽  
High Performance ◽  
Selection Process ◽  
Storage System ◽  
Event Selection ◽  
Event Filtering ◽  
Record Data ◽  
Detector Activity ◽  
Novel Design ◽  
Persistent Storage

The ATLAS experiment will undergo a major upgrade to take advantage of the new conditions provided by the upgraded High-Luminosity LHC. The Trigger and Data Acquisition system (TDAQ) will record data at unprecedented rates: the detectors will be read out at 1 MHz generating around 5 TB/s of data. The Dataflow system (DF), component of TDAQ, introduces a novel design: readout data are buffered on persistent storage while the event filtering system analyses them to select 10000 events per second for a total recorded throughput of around 60 GB/s. This approach allows for decoupling the detector activity from the event selection process. New challenges then arise for DF: design and implement a distributed, reliable, persistent storage system supporting several TB/s of aggregated throughput while providing tens of PB of capacity. In this paper we first describe some of the challenges that DF is facing: data safety with persistent storage limitations, indexing of data at high-granularity in a highly-distributed system, and high-performance management of storage capacity. Then the ongoing R&D to address each of the them is presented and the performance achieved with a working prototype is shown.

scholarly journals An implementation architecture for crowd network simulations

2020 ◽  
Vol 4 (2) ◽  
pp. 189-207
Author(s):  
Jialin Zou ◽  
Kun Wang ◽  
Hongbo Sun
Keyword(s):  
Large Scale ◽  
General Structure ◽  
Simulation System ◽  
Data Driven ◽  
System Implementation ◽  
Functional Architecture ◽  
Implementation Framework ◽  
Content Type ◽  
Network Simulations ◽  
Persistent Storage

Purpose Crowd network systems have been deemed as a promising mode of modern service industry and future economic society, and taking crowd network as the research object and exploring its operation mechanism and laws is of great significance for realizing the effective governance of the government and the rapid development of economy, avoiding social chaos and mutation. Because crowd network is a large-scale, dynamic and diversified online deep interconnection, its most results cannot be observed in real world, and it cannot be carried out in accordance with traditional way, simulation is of great importance to put forward related research. To solve above problems, this paper aims to propose a simulation architecture based on the characteristics of crowd network and to verify the feasibility of this architecture through a simulation example. Design/methodology/approach This paper adopts a data-driven architecture by deeply analyzing existing large-scale simulation architectures and proposes a novel reflective memory-based architecture for crowd network simulations. In this paper, the architecture is analyzed from three aspects: implementation framework, functional architecture and implementation architecture. The proposed architecture adopts a general structure to decouple related work in a harmonious way and gets support for reflection storage by connecting to different devices via reflection memory card. Several toolkits for system implementation are designed and connected by data-driven files (DDF), and these XML files constitute a persistent storage layer. To improve the credibility of simulations, VV&A (verification, validation and accreditation) is introduced into the architecture to verify the accuracy of simulation system executions. Findings Implementation framework introduces the scenes, methods and toolkits involved in the whole simulation architecture construction process. Functional architecture adopts a general structure to decouple related work in a harmonious way. In the implementation architecture, several toolkits for system implementation are designed, which are connected by DDF, and these XML files constitute a persistent storage layer. Crowd network simulations obtain the support of reflective memory by connecting the reflective memory cards on different devices and connect the interfaces of relevant simulation software to complete the corresponding function call. Meanwhile, to improve the credibility of simulations, VV&A is introduced into the architecture to verify the accuracy of simulation system executions. Originality/value This paper proposes a novel reflective memory-based architecture for crowd network simulations. Reflective memory is adopted as share memory within given simulation execution in this architecture; communication efficiency and capability have greatly improved by this share memory-based architecture. This paper adopts a data-driven architecture; the architecture mainly relies on XML files to drive the entire simulation process, and XML files have strong readability and do not need special software to read.

Maintaining Replicated Recovery Log for RESTful Services

2015 ◽  
Vol 7 (3) ◽  
pp. 23-35 ◽  
Author(s):  
Anna Kobusińska ◽  
Dariusz Wawrzyniak
Keyword(s):  
Information Systems ◽  
Fault Tolerance ◽  
Rollback Recovery ◽  
Failure State ◽  
Service Oriented ◽  
Restful Services ◽  
Persistent Storage

Along with development of information systems, their requirements in terms of fault-tolerance increase and become more stringent. A possible approach to deal with this issue is rollback-recovery that consists in loading by the recovering node its most recent checkpoint, or retransmitting requests saved in its message log, to reach a consistent pre-failure state. Both checkpoint and message log are commonly said to be saved in a persistent storage able to survive any failure. In this paper the authors propose the implementation of a stable storage by means of replication of the log containing recovery information. The proposed solution is especially tailored for the service oriented systems implemented accordingly to REST paradigm. Thus, they utilize RESTful semantics in order to reduce the size of replicated recovery log and thereby increasing the efficiency of the proposed recovery log replication protocol.

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