scholarly journals Semi-online scheduling with known partial information about job sizes on two identical machines

2011 ◽  
Vol 412 (29) ◽  
pp. 3731-3737 ◽  
Author(s):  
Qian Cao ◽  
Zhaohui Liu ◽  
T.C.E. Cheng
2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Taibo Luo ◽  
Yinfeng Xu

This paper investigates semi-online scheduling problems on two parallel machines under a grade of service (GoS) provision subject to minimize the makespan. We consider three different semi-online versions with knowing the total processing time of the jobs with higherGoSlevel, knowing the total processing time of the jobs with lowerGoSlevel, or knowing both in advance. Respectively, for the three semi-online versions, we develop algorithms with competitive ratios of3/2,20/13, and4/3which are shown to be optimal.


2015 ◽  
Vol 11 (1) ◽  
pp. 185-198 ◽  
Author(s):  
Jiping Tao ◽  
◽  
Ronghuan Huang ◽  
Tundong Liu

2014 ◽  
Vol 25 (06) ◽  
pp. 745-761 ◽  
Author(s):  
LIN CHEN ◽  
DESHI YE ◽  
GUOCHUAN ZHANG

We consider the online scheduling problem in a CPU-GPU cluster. In this problem there are two sets of processors, the CPU processors and the GPU processors. Each job has two distinct processing times, one for the CPU processor and the other for the GPU processor. Once a job is released, a decision should be made immediately about which processor it should be assigned to. The goal is to minimize the makespan, i.e., the largest completion time among all the processors. Such a problem could be seen as an intermediate model between the scheduling problem on identical machines and unrelated machines. We provide a 3.85-competitive online algorithm for this problem and show that no online algorithm exists with competitive ratio strictly less than 2. We also consider two special cases of this problem, the balanced case where the number of CPU processors equals to that of GPU processors, and the one-sided case where there is only one CPU or GPU processor. For the balanced case, we first provide a simple 3-competitive algorithm, and then a better algorithm with competitive ratio of 2.732 is derived. For the one-sided case, a 3-competitive algorithm is given.


2012 ◽  
Vol 26 (3) ◽  
pp. 472-479 ◽  
Author(s):  
Xiao Min ◽  
Yuqing Wang ◽  
Jing Liu ◽  
Min Jiang

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