Two uniform machines with nearly equal speeds: unified approach to known sum and known optimum in semi on-line scheduling

2009 ◽  
Vol 21 (4) ◽  
pp. 458-480 ◽  
Author(s):  
György Dósa ◽  
M. Grazia Speranza ◽  
Zsolt Tuza
2001 ◽  
Vol 4 (2) ◽  
pp. 71-92 ◽  
Author(s):  
Leah Epstein ◽  
John Noga ◽  
Steve Seiden ◽  
Ji?� Sgall ◽  
Gerhard Woeginger
Keyword(s):  

2005 ◽  
Vol 22 (02) ◽  
pp. 229-237 ◽  
Author(s):  
RUN-ZI LUO ◽  
SHI-JIE SUN

In this paper, we investigate a semi-on-line version for a special case of three machines M1, M2, M3 where the processing time of the largest job is known in advance. A speed si(s1 = s2 = 1, 1 ≤ s3 = s) is associated with machine Mi. Our goal is to maximize the C min — the minimum workload of three machines. We give a C min 3 algorithm and prove its competitive ratio is [Formula: see text] and the algorithm is the best possible for 1 ≤ s ≤ 2. We also claim the competitive ratio of algorithm C min 3 is tight.


2014 ◽  
Vol 18 (2) ◽  
pp. 185-194 ◽  
Author(s):  
Tianping Shuai ◽  
Donglei Du ◽  
Xiaoyue Jiang

1987 ◽  
Vol 27 (4) ◽  
pp. 611-614
Author(s):  
Inder M. Soi ◽  
K.K. Aggarwal

2004 ◽  
Vol 04 (04) ◽  
pp. 627-651 ◽  
Author(s):  
RUIGANG YANG ◽  
MARC POLLEFEYS ◽  
HUA YANG ◽  
GREG WELCH

We present a new method for using commodity graphics hardware to achieve real-time, on-line, 2D view synthesis or 3D depth estimation from two or more calibrated cameras. Our method combines a 3D plane-sweeping approach with 2D multi-resolution color consistency tests. We project camera imagery onto each plane, compute measures of color consistency throughout the plane at multiple resolutions, and then choose the color or depth (corresponding plane) that is most consistent. The key to achieving real-time performance is our use of the advanced features included with recent commodity computer graphics hardware to implement the computations simultaneously (in parallel) across all reference image pixels on a plane. Our method is relatively simple to implement, and flexible in term of the number and placement of cameras. With two cameras and an NVIDIA GeForce4 graphics card we can achieve 50–70 M disparity evaluations per second, including image download and read-back overhead. This performance matches the fastest available commercial software-only implementation of correlation-based stereo algorithms, while freeing up the CPU for other uses.


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