An Efficient Algorithm for Service Function Chains Reconfiguration in Mobile Edge Cloud Networks

2021 ◽  
Author(s):  
Biyi Li ◽  
Bo Cheng ◽  
Junliang Chen
Keyword(s):  
Efficient Algorithm ◽  
Cloud Networks ◽  
Service Function

Enabling Efficient Service Function Chains at Terrestrial-Satellite Hybrid Cloud Networks

IEEE Network ◽  
2019 ◽  
Vol 33 (6) ◽  
pp. 94-99 ◽  
Author(s):  
Bohao Feng ◽  
Guanglei Li ◽  
Guanwen Li ◽  
Yuming Zhang ◽  
Huachun Zhou ◽  
...  
Keyword(s):  
Hybrid Cloud ◽  
Cloud Networks ◽  
Service Function

An architecture for securing federated cloud networks with Service Function Chaining

2016 ◽  
Author(s):  
Philippe Massonet ◽  
Sebastien Dupont ◽  
Arnaud Michot ◽  
Anna Levin ◽  
Massimo Villari
Keyword(s):  
Cloud Networks ◽  
Service Function

Efficient Mappings of Service Function Chains at Terrestrial-Satellite Hybrid Cloud Networks

2018 ◽  
Author(s):  
Bohao Feng ◽  
Guanglei Li ◽  
Guanwen Li ◽  
Huachun Zhou ◽  
Hongke Zhang ◽  
...  
Keyword(s):  
Hybrid Cloud ◽  
Cloud Networks ◽  
Service Function

Computational Micrograph Registration with Sieve Processes

1996 ◽  
Vol 54 ◽  
pp. 440-441
Author(s):  
P.J. Phillips ◽  
J. Huang ◽  
S. M. Dunn
Keyword(s):  
Planar Graph ◽  
Efficient Algorithm ◽  
Spatial Organization ◽  
Spatial Arrangement ◽  
Stereo Image ◽  
Image Model ◽  
Geometric Invariants ◽  
Point Set

In this paper we present an efficient algorithm for automatically finding the correspondence between pairs of stereo micrographs, the key step in forming a stereo image. The computation burden in this problem is solving for the optimal mapping and transformation between the two micrographs. In this paper, we present a sieve algorithm for efficiently estimating the transformation and correspondence.In a sieve algorithm, a sequence of stages gradually reduce the number of transformations and correspondences that need to be examined, i.e., the analogy of sieving through the set of mappings with gradually finer meshes until the answer is found. The set of sieves is derived from an image model, here a planar graph that encodes the spatial organization of the features. In the sieve algorithm, the graph represents the spatial arrangement of objects in the image. The algorithm for finding the correspondence restricts its attention to the graph, with the correspondence being found by a combination of graph matchings, point set matching and geometric invariants.

Energy efficient algorithm for lookup-tables on mobile devices

2016 ◽  
Vol 2016 (7) ◽  
pp. 1-6
Author(s):  
Sergey Makov ◽  
Vladimir Frantc ◽  
Viacheslav Voronin ◽  
Igor Shrayfel ◽  
Vadim Dubovskov ◽  
...  
Keyword(s):  
Mobile Devices ◽  
Efficient Algorithm ◽  
Energy Efficient ◽  
Lookup Tables
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