Persistent Data Storage

2020 ◽  
pp. 443-474
Author(s):  
David P. Voorhees
Keyword(s):  
Data Storage ◽  
Persistent Data

scholarly journals DBE2 – Management of experimental data for the VANTED system

2011 ◽  
Vol 8 (2) ◽  
pp. 85-94
Author(s):  
Hendrik Mehlhorn ◽  
Falk Schreiber
Keyword(s):  
Experimental Data ◽  
Information System ◽  
Data Integration ◽  
Data Management ◽  
Data Storage ◽  
Controlled Vocabulary ◽  
Biological Experiment ◽  
Experiment Data ◽  
Measurement Units ◽  
Persistent Data

Summary DBE2 is an information system for the management of biological experiment data from different data domains in a unified and simple way. It provides persistent data storage, worldwide accessibility of the data and the opportunity to load, save, modify, and annotate the data. It is seamlessly integrated in the VANTED system as an add-on, thereby extending the VANTED platform towards data management. DBE2 also utilizes controlled vocabulary from the Ontology Lookup Service to allow the management of terms such as substance names, species names, and measurement units, aiming at an eased data integration.

Flexible Digital Library Search

2011 ◽  
pp. 200-224
Author(s):  
Menzo Windhouwer ◽  
Albrecht Schmidt ◽  
Roelof van Zwol ◽  
Milan Petkovic ◽  
Henk E. Blok
Keyword(s):  
Search Engine ◽  
Data Storage ◽  
Digital Library ◽  
System Architecture ◽  
Multimedia Retrieval ◽  
Domain Specific ◽  
Persistent Data ◽  
Physical Level ◽  
Index 2 ◽  
High Degree

In this chapter the development of a specialised search engine for a digital library is described.  The proposed system architecture consists of three levels: the conceptual, the logical and the physical level.  The conceptual level schema enables by its exposure of a domain specific schema semantically rich conceptual search.  The logical level provides a description language to achieve a high degree of flexibility for multimedia retrieval.  The physical level takes care of scalable and efficient persistent data storage.  The role, played by each level, changes during the various stages of a search engine’s lifecycle: (1) modeling the index, (2) populating and maintaining the index and (3) querying the index.  The integration of all this functionality allows the combination of both conceptual and content-based querying in the query stage.  A search engine for the Australian Open tennis tournament website is used as a running example, which shows the power of the complete architecture and its various components.

One solution for persistent data storage in automotive industry

2017 ◽  
Author(s):  
Dragan Radanovic ◽  
Ivan Kastelan ◽  
Milovan Vidovic ◽  
Radovan Prodanovic
Keyword(s):  
Data Storage ◽  
Automotive Industry ◽  
Persistent Data

scholarly journals Position-Based Aggregator Node Election in Wireless Sensor Networks

2010 ◽  
Vol 6 (1) ◽  
pp. 679205 ◽  
Author(s):  
Levente Buttyán ◽  
Péter Schaffer
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Storage ◽  
Base Station ◽  
Base Stations ◽  
Wireless Sensor ◽  
Simulation Environment ◽  
Hand Panel ◽  
Network Applications ◽  
Persistent Data

We introduce PANEL a position-based aggregator node election protocol for wireless sensor networks. The novelty of PANEL with respect to other aggregator node election protocols is that it supports asynchronous sensor network applications where the sensor readings are fetched by the base stations after some delay. In particular, the motivation for the design of PANEL was to support reliable and persistent data storage applications, such as TinyPEDS; see the study by Girao et al. (2007). PANEL ensures load balancing, and it supports intra and intercluster routing allowing sensor-to-aggregator, aggregator-to-aggregator, base station-to-aggregator, and aggregator to-base station communications. We also compare PANEL with HEED; see the study by Younis and Fahmy (2004) in the simulation environment provided by TOSSIM, and show that, on one hand, PANEL creates more cohesive clusters than HEED, and, on the other hand, that PANEL is more energy efficient than HEED.

Research and Improvement of Database Storage Method

2014 ◽  
Vol 608-609 ◽  
pp. 641-645 ◽  
Author(s):  
Feng Sheng Zeng
Keyword(s):  
Parallel Processing ◽  
Data Storage ◽  
Processing Method ◽  
High Availability ◽  
Map Reduce ◽  
Massive Data ◽  
Distributed Data ◽  
Simulation Test ◽  
Persistent Data ◽  
High Scalability

This paper presents a massive data storage and parallel processing method based on MPP architecture, and put forward full persistent data storage way from the client to request, and the integration the idea of Map/Reduce, the system will be distributed to each data node, the data has high scalability, high availability, high concurrency. And the simulation test and verifies the feasibility of mass data storage mode by building a distributed data node.

scholarly journals DNA-based data storage via combinatorial assembly

2021 ◽  
Author(s):  
Nathaniel Roquet ◽  
Swapnil P Bhatia ◽  
Sarah A Flickinger ◽  
Sean Mihm ◽  
Michael W Norsworthy ◽  
...  
Keyword(s):  
Data Storage ◽  
Narrow Band ◽  
Dna Computation ◽  
Data Encoding ◽  
Exciting Potential ◽  
Persistent Data ◽  
Combinatorial Assembly ◽  
Opening Up ◽  
Practical Scheme

AbstractPersistent data storage is the basis of all modern information systems. The long-term value and volume of data are growing at an accelerating rate and pushing extant storage systems to their limits. DNA offers exciting potential as a storage medium, but no practical scheme has been proposed to date that can scale beyond narrow-band write rates. Here, we demonstrate a combinatorial DNA data encoding scheme capable of megabits per second write speeds. The system relies on rapid, combinatorial assembly of multiple smaller DNA parts that are dispensed through inkjet printing. To demonstrate this approach, we wrote approximately 25 kB of information into DNA using our system and read the information back out with commercially available nanopore sequencing. Moreover, we demonstrate the ability to replicate and selectively access the information while it is in DNA, opening up the possibility of more sophisticated DNA computation.

Palm OS Programming

2011 ◽  
pp. 333-350
Author(s):  
Wen-Chen Hu
Keyword(s):  
Data Storage ◽  
Battery Life ◽  
Backward Compatibility ◽  
Cellular Telephony ◽  
Extensive Coverage ◽  
Usage Patterns ◽  
Persistent Data ◽  
Basic Documentation ◽  
Sd Card ◽  
New Applications

Programming for Palm devices is not a trivial task and it is especially hard for beginners starting their first assignment. This chapter is not intended to be a comprehensive Palm programming guide, but rather to give an overview of what a Palm program is and how it works. For details of how to create Palm OS application programs, extensive coverage of this topic is provided by the Palm OS Developer Documentation at the URL (http://www.palmos.com/dev/support/docs/) (PalmSource, Inc. (2004a,b,c). The following steps for getting started with Palm OS programming are taken from PalmSource Inc. (2006): 1. Join the Palm OS Developer Program: Enroll as a member of Palm OS Developer Program at the URL (https://www.developerpavilion.com/palmos/ page.asp?page_id=175) in order to download tools such as Palm OS Developer Suite and receive updates of Palm information. 2. Choose a core platform: There are two versions of the Palm OS core platform: Palm OS Garnet (above Palm OS 5.3) and • Palm OS Cobalt (Palm OS 6). and three Palm OS application types: • Palm OS 68K applications, • Palm OS 68K applications with PACE Native Objects, and • Palm OS Protein applications. 3. Choose a programming language and tools: Although most Palm OS applications are written in C, development environments are available that will let developers create Palm OS applications in a number of different languages including C, C++, Visual Basic, or Java. 4. Learn the basics of Palm OS programming: Basic documentation related to Palm OS programming includes: • Introduction to Palm OS Development Suite, which is a conceptual introduction to all of the tools delivered with Garnet OS Development Suite. It can be found at at the URL (http://www.access-company.com/developers/ documents/docs/dev_suite/PalmOSDevSuite/ToolsTOC.html) • Garnet OS 68K SDK Documentation, which contains documentation on the 68K software development kit. It can be found at the URL (http://www. access-company.com/developers/documents/palmos/index.html). Also, there are several considerations that developers need to keep in mind as they design and build their applications: • Small screen size. • Usage patterns: for example, a handheld may be turned on 40 times in 1 hour. • Limited input methods. • Various wireless connectivity. • Limited computing power. • Short battery life. Actions such as wireless communications, sound, extended animation, or other tasks that occupy the CPU for long periods of time consume a great deal of power. • Small memory. Expansion is often limited to the capacity of an SD card. • Persistent data storage. • Backward compatibility. 5. Consider wireless-enabling applications: Palm powered devices can connect with networks and with each other in an increasing number of ways, including infrared, Bluetooth, Wi-Fi, and cellular telephony. Programmers can benefit from exploring these opportunities, discovering new grab tips, tools, and insights and learning how PalmSource can help test new applications and deploy them in the wireless marketplace. 6. Tailor solutions to specific devices: Although Palm OS forms the core of every Palm powered device, some devices have features that are specific to that device from a Palm OS licensee.

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