Static and dynamic data management in networks

1997 ◽  
pp. 46-56
Author(s):  
Friedhelm Meyer auf der Heide ◽  
Berthold Vöcking
Keyword(s):  
Data Management ◽  
Dynamic Data

scholarly journals C3PO - A Dynamic Data Placement Agent for ATLAS Distributed Data Management

2017 ◽  
Vol 898 ◽  
pp. 062012 ◽  
Author(s):  
T Beermann ◽  
M Lassnig ◽  
M Barisits ◽  
C Serfon ◽  
V Garonne ◽  
...  
Keyword(s):  
Data Management ◽  
Data Placement ◽  
Distributed Data ◽  
Dynamic Data ◽  
Distributed Data Management

scholarly journals Integrating a dynamic data federation into the ATLAS distributed data management system

2019 ◽  
Vol 214 ◽  
pp. 07009
Author(s):  
Frank Berghaus ◽  
Tobias Wegner ◽  
Mario Lassnig ◽  
Marcus Ebert ◽  
Cedric Serfon ◽  
...  
Keyword(s):  
Data Management ◽  
Management System ◽  
Data Management System ◽  
Distributed Data ◽  
Dynamic Data ◽  
Distributed Data Management ◽  
Data Federation ◽  
Other Information ◽  
Multiple Copies ◽  
Set Up

Input data for applications that run in cloud computing centres can be stored at remote repositories, typically with multiple copies of the most popular data stored at many sites. Locating and retrieving the remote data can be challenging, and we believe that federating the storage can address this problem. In this approach, the closest copy of the data is used based on geographical or other information. Currently, we are using the dynamic data federation, Dynafed, a software solution developed by CERN IT. Dynafed supports several industry standard interfaces, such as Amazon S3, Microsoft Azure and HTTP with WebDAV extensions. Dynafed functions as an abstraction layer under which protocol-dependent authentication details are hidden from the user, requiring the user to only provide an X509 certificate. We have set up an instance of Dynafed and integrated it into the ATLAS distributed data management system, Rucio. We report on the challenges faced during the installation and integration.

Efficient Dynamic Memory Management for Multiprocessor Cyber-Physical Systems

2019 ◽  
Vol 1 (1) ◽  
pp. 35-44
Author(s):  
Ali Ahmadinia
Keyword(s):  
Data Management ◽  
Memory Management ◽  
Multiprocessor System ◽  
Dynamic Data ◽  
Dynamic Memory ◽  
Static Data ◽  
Different Types ◽  
Dynamic Memory Management ◽  
The Many ◽  
Compare And Contrast

Dynamic data management for multiprocessor systems in the absence of an operating system (OS) is a challenging area of research. OSs are typically used to abstract developers from the process of managing dynamic data at runtime. However, due to the many different types of multiprocessor available, an OS is not always available, making the management of dynamic data a difficult task. In this article, we present a hardware and software co-design methodology for the management of dynamic data in multiprocessor system on chips (MPSoC) development environments without an OS. We compare and contrast the method of sharing dynamic data between cores with standard methods and also to static data management methods and find that the proposed methodology can improve the performance of dynamic memory operations by up to 72.94% with negligible power and resource consumption.

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