Asycome: A JointCloud Data Asynchronous Collaboration Mechanism Based on Blockchain

2021 ◽  
pp. 530-544
Author(s):  
Linhui Li ◽  
Peichang Shi ◽  
Xiang Fu ◽  
Shengtian Zhang ◽  
Tao Zhong ◽  
...  
2008 ◽  
Vol 17 (04) ◽  
pp. 523-554 ◽  
Author(s):  
PABLO GOTTHELF ◽  
ALEJANDRO ZUNINO ◽  
MARCELO CAMPO

Many advances have been done to allow groups of people to work together and collaborate in the Internet. Collaborative systems are characterized by the way participants interact. In many cases, equal standing members should cooperate in a non-authoritative environment, where no entity or authority is or should be in charge of regulating the group. Therefore, decentralized communication infrastructures have been hailed as promising alternatives. Recently, decentralized infrastructures based on P2P approaches have drawn the attention of the research community because of their benefits in terms of scalability, robustness, availability and potentials for leveraging computational resources distributed across the Internet. In this paper, a scalable peer-to-peer (P2P) communication Infrastructure for groupware applications is presented. It enables a large number of people to join and cooperate in a robust, decentralized and easy deployable way, without requiring high capacity servers or any other special network infrastructure. The communication infrastructure is based on a binary tree as overlay structure, which implements all groupware communication functionality, including membership management and packet forwarding, at application level, making it an inexpensive and fast deployable solution for equal standing members, such as home users with a domestic connection to the Internet. Two applications, one for synchronous groupware and the other for asynchronous collaboration, have been developed to validate the approach. Comparisons with other communication infrastructures in aspects such as end-to-end propagation delay, group latency, throughput, protocol overhead, failure recovery and link stress, show that our approach is a scalable and robust alternative.


2008 ◽  
Vol 7 (8) ◽  
pp. 1182-1187 ◽  
Author(s):  
J. Xu ◽  
J. Zhang ◽  
T. Harvey ◽  
J. Young

2016 ◽  
Vol 12 (S325) ◽  
pp. 311-315 ◽  
Author(s):  
Dany Vohl ◽  
Christopher J. Fluke ◽  
Amr H. Hassan ◽  
David G. Barnes ◽  
Virginia A. Kilborn

AbstractRadio survey datasets comprise an increasing number of individual observations stored as sets of multidimensional data. In large survey projects, astronomers commonly face limitations regarding: 1) interactive visual analytics of sufficiently large subsets of data; 2) synchronous and asynchronous collaboration; and 3) documentation of the discovery workflow. To support collaborative data inquiry, we present encube, a large-scale comparative visual analytics framework. encube can utilise advanced visualization environments such as the CAVE2 (a hybrid 2D and 3D virtual reality environment powered with a 100 Tflop/s GPU-based supercomputer and 84 million pixels) for collaborative analysis of large subsets of data from radio surveys. It can also run on standard desktops, providing a capable visual analytics experience across the display ecology. encube is composed of four primary units enabling compute-intensive processing, advanced visualisation, dynamic interaction, parallel data query, along with data management. Its modularity will make it simple to incorporate astronomical analysis packages and Virtual Observatory capabilities developed within our community. We discuss how encube builds a bridge between high-end display systems (such as CAVE2) and the classical desktop, preserving all traces of the work completed on either platform – allowing the research process to continue wherever you are.


2020 ◽  
Author(s):  
Raghvinder Sangwan ◽  
Kathryn Jablokow ◽  
Matt Bass ◽  
Dan Paulish

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