Integrated processor scheduling for multimedia

1995 ◽  
pp. 202-205 ◽  
Author(s):  
Jason Nieh ◽  
Monica S. Lam
Keyword(s):  
Processor Scheduling

A new greedy algorithm for multi-processor scheduling with gang scheduling

2010 ◽  
Vol 5 (1) ◽  
pp. 7-12
Author(s):  
Sarath B. Siyambalapitiya ◽  
M. Sandirigama
Keyword(s):  
Greedy Algorithm ◽  
Processor Scheduling ◽  
Gang Scheduling

Proof of the 4/3 conjecture for preemptive vs. nonpreemptive two-processor scheduling

1993 ◽  
Vol 40 (5) ◽  
pp. 991-1018 ◽  
Author(s):  
E. G. Coffman ◽  
M. R. Garey
Keyword(s):  
Processor Scheduling

ON THE COMPLEXITY OF SCHEDULING WITH COMMUNICATION DELAY AND CONTENTION

1995 ◽  
Vol 05 (03) ◽  
pp. 331-341 ◽  
Author(s):  
MICHAEL G. NORMAN ◽  
SUSANNA PELAGATTI ◽  
PETER THANISCH
Keyword(s):  
Execution Time ◽  
Communication Delay ◽  
Interprocessor Communication ◽  
Communication Latency ◽  
Processor Scheduling ◽  
Np Completeness

We show the NP-Completeness of two processor scheduling with tasks of execution time 1 or 2 units and unit interprocessor communication latency. We develop a model of scheduling in the presence of communication contention, and show the NP-Completeness of two processor scheduling with unit execution time tasks in our model.

scholarly journals A comparative study of two algorithms of multi - processor scheduling

2005 ◽  
Vol 17 (2) ◽  
pp. 115-130
Author(s):  
Isra Al-Kallak ◽  
Ahmed Al-Sabawi
Keyword(s):  
Comparative Study ◽  
Processor Scheduling

NEW APPROACH TO MULTI-LEVEL PROCESSOR SCHEDULING

2010 ◽  
Vol 19 (03) ◽  
pp. 335-346 ◽  
Author(s):  
SAMANEH HOSSEINI SEMNANI ◽  
KAMRAN ZAMANIFAR
Keyword(s):  
Fitness Function ◽  
Systems Design ◽  
Heuristic Function ◽  
Problem Space ◽  
New Approach ◽  
Processor Scheduling ◽  
Quantum Time ◽  
Multi Level ◽  
Evaluation Parameters

The problem of finding the best quantum time in multi-level processor scheduling is addressed in this paper. Processor scheduling is one of the most important issues in operating systems design. Different schedulers are introduced to solve this problem. In one scheduling approach, processes are placed in different queues according to their properties, and the processor allocates time to each queue iteratively. One of the most important parameters of a processor's efficiency in this approach is the amount of time slices associated to each processor queue. In this paper, an ant colony optimization (ACO) algorithm is presented to solve the problem of finding appropriate time slices to assign to each processor queue. In this technique, each ant tries to find an appropriate scheduling. Ant algorithm searches the problem space to find the best scheduling. The quality of each ant's solution is evaluated using a new fitness function. This fitness function is designed according to the evaluation parameters of each processor queue and also according to the queue theory's relations. Also a heuristic function is presented which prompts ant to select better solutions. Computational tests are presented and the comparisons made with genetic algorithm (GA) and particle swarm optimization (PSO) algorithms which try to solve same problem. The results show the efficiency of this algorithm.

Probabilistic Analysis of the LPT Processor Scheduling Heuristic

1982 ◽  
pp. 319-331 ◽  
Author(s):  
E. G. Coffman ◽  
G. N. Frederickson ◽  
G. S. Lueker
Keyword(s):  
Probabilistic Analysis ◽  
Processor Scheduling ◽  
Scheduling Heuristic
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