.png){kind=icon}
.png){kind=icon}
Return
Distributed computing on core-periphery networks: Axiom-based design
.png){kind=icon}
OA
AI
DOI：10.1016/j.jpdc.2016.08.003.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Inspired by social networks and complex systems, we propose a core-periphery network architecture that supports fast computation for many distributed algorithms, is robust and uses a linear number of links. Rather than providing a concrete network model, we take an axiom-based design approach. We provide three intuitive and independent algorithmic axioms and prove that any network that satisfies all axioms enjoys an efficient algorithm for a range of tasks (such as MST, sparse matrix multiplication, and more). We also show the necessity of our axiom set: for networks that satisfy any subset of the axioms, the same efficiency cannot be guaranteed for any deterministic algorithm. (C) 2016 Elsevier Inc. All rights reserved.
Keywords:
Distributed computing
Core-periphery networks
Axiom-base design
Minimum spanning tree
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4
Papers:
3.8K
Citations:
4.8K