scholarly journals Securing Grid Data Transfer Services with Active Network Portals

Author(s):  
Onur Demir ◽  
Michael R. Head ◽  
Kanad Ghose ◽  
Madhusudhan Govindaraju
2018 ◽  
Vol 6 (1) ◽  
pp. 37-43 ◽  
Author(s):  
Deniss Brodņevs

Abstract Remotely piloted operations of lightweight Unmanned Air Vehicles (UAV) are limited by transmitter power consumption and are always restricted to Line-of-Sight (LOS) distance. The use of mobile cellular network data transfer services (e.g. 3G HSPA and LTE) as well as long-range terrestrial links (e.g. LoraWAN) makes it possible to significantly extend the operation range of the remotely piloted UAV. This paper describes the development of a long-range communication solution for the UAV telemetry system. The proposed solution is based on (but not restricted to) cellular data transfer service and is implemented on Raspberry Pi under Gentoo Linux control. The goal of the project is to develop a flexible system for implementing optimized redundant network solutions for the Non-LOS remote control of the UAV


Author(s):  
Priyaa Thavasimani

AbstractData Management of Astronomy Data is often a laborious task and it is even more challenging for the extraordinary amounts of data expected from the world’s largest radio telescope, Square Kilometre Array. There are overt issues in transferring the voluminous data and the traditional data transfer methods are fragile especially for the data transfer between two continents. To address this, a new data transfer framework is proposed and the data transfer is achieved using two steps: international and local transfers. The efficiency of different end-to-end data transfer tools used in is evaluated on different dataset sizes. Further, a comparative study of two IRIS grid data transfer methods is made to understand each methods’ advantages and disadvantages. This study can be used as a reference for the development of future SKA’s data transfer operations.


Author(s):  
Borja Bergua ◽  
Felix Garcia-Carballeira ◽  
Alejandro Calderon ◽  
Luis-Miguel Sanchez ◽  
Jesus Carretero

Author(s):  
Navonil Mustafee ◽  
Simon J.E. Taylor

The computational grid offers services for efficiently scheduling jobs on the grid, but for grid-enabled applications where data handling is a most relevant part, the data grid kicks in. It typically builds on the concept of files, sites and file transfers between sites. These use a data transfer service, plus a replica manager to keep track of where replicas are located. The authors consider a multi-site, grid-aware data warehouse, which is a large distributed repository sharing a schema and data concerning scientific or business domains. Differently from typical grid scenarios, the data warehouse is not simply a set of files and accesses to individual files. It is a single distributed schema and both localized and distributed computations must be managed over that schema. Given this difference, it is important to study approaches for placement and computation over the grid data warehouse and this is our contribution in this book chapter.


IEEE Network ◽  
1988 ◽  
Vol 2 (3) ◽  
pp. 75-81 ◽  
Author(s):  
W.T. Strayer ◽  
A.C. Weaver

Author(s):  
Rogério Luís de Carvalho Costal ◽  
Pedro Furtado

The computational grid offers services for efficiently scheduling jobs on the grid, but for grid-enabled applications where data handling is a most relevant part, the data grid kicks in. It typically builds on the concept of files, sites and file transfers between sites. These use a data transfer service, plus a replica manager to keep track of where replicas are located. The authors consider a multi-site, grid-aware data warehouse, which is a large distributed repository sharing a schema and data concerning scientific or business domains. Differently from typical grid scenarios, the data warehouse is not simply a set of files and accesses to individual files. It is a single distributed schema and both localized and distributed computations must be managed over that schema. Given this difference, it is important to study approaches for placement and computation over the grid data warehouse and this is our contribution in this book chapter.


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