Route Optimization for Large Scale Network Mobility Assisted by BGP

2007 ◽  
Author(s):  
Feriel Mimoune ◽  
Farid Nait-Abdesselam ◽  
Tarik Taleb ◽  
Kazuo Hashimoto
Keyword(s):  
Large Scale ◽  
Route Optimization ◽  
Network Mobility ◽  
Large Scale Network ◽  
Scale Network

scholarly journals A Graph Based Framework for Route Optimization in Sea-Trade Logistics

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Dianhui Chu ◽  
Chunshan Li ◽  
Xiaofei Xu ◽  
Xiaofeng Zhang
Keyword(s):  
Large Scale ◽  
Graphical Model ◽  
Transportation Network ◽  
Optimization Methods ◽  
Route Optimization ◽  
Ant Colony Optimization Algorithm ◽  
Routing Problem ◽  
Logistics Industry ◽  
Large Scale Network ◽  
Scale Network

How to find the optimal transportation route in sea-trade is very important for the logistics industry. The traditional routing problem is solved by performing the combinatorial optimization over a specified transportation network. Facing the huge network extracted from the foreign trading industry as well as the complex constraints, it is impossible for the traditional optimization methods to find the solution in a short time, which motivates our work. In this paper, we first carefully study the property of foreign trade network, and then convert the transportation network into a hierarchical one and propose a novel framework based on graphical model to solve this large scale network optimization problem. The experimental results demonstrate that our approach is superior to the famous ant colony optimization algorithm (ACO) in terms of accuracy and the time spent.

Large-Scale Network Analysis for Online Social Brand Advertising

MIS Quarterly ◽  
2016 ◽  
Vol 40 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Kunpeng Zhang ◽  
◽  
Siddhartha Bhattacharyya ◽  
Sudha Ram ◽  
◽  
...  
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Large Scale Network ◽  
Brand Advertising ◽  
Scale Network

Attention Biases Visual Activity in Visual Short-term Memory

2014 ◽  
Vol 26 (7) ◽  
pp. 1377-1389 ◽  
Author(s):  
Bo-Cheng Kuo ◽  
Mark G. Stokes ◽  
Alexandra M. Murray ◽  
Anna Christina Nobre
Keyword(s):  
Large Scale ◽  
Short Term Memory ◽  
Control Mechanisms ◽  
Top Down ◽  
Short Term ◽  
Visual Activity ◽  
Visual Short Term Memory ◽  
Large Scale Network ◽  
Visual Areas ◽  
Scale Network

In the current study, we tested whether representations in visual STM (VSTM) can be biased via top–down attentional modulation of visual activity in retinotopically specific locations. We manipulated attention using retrospective cues presented during the retention interval of a VSTM task. Retrospective cues triggered activity in a large-scale network implicated in attentional control and led to retinotopically specific modulation of activity in early visual areas V1–V4. Importantly, shifts of attention during VSTM maintenance were associated with changes in functional connectivity between pFC and retinotopic regions within V4. Our findings provide new insights into top–down control mechanisms that modulate VSTM representations for flexible and goal-directed maintenance of the most relevant memoranda.

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