Method and system for solving distributable task scheduling model

A scheduling model and task division technology, applied in the information field, can solve problems such as low efficiency and huge time overhead.

Inactive Publication Date: 2015-03-25
XIDIAN UNIV
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  • Abstract
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Problems solved by technology

Existing methods for solving separable task scheduling problems considering the release time mostly use the exhaus

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  • Method and system for solving distributable task scheduling model
  • Method and system for solving distributable task scheduling model
  • Method and system for solving distributable task scheduling model

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Embodiment 1

[0195] Aiming at the proposed model and algorithm, we conducted several sets of comparative experiments. The experimental parameters are set as follows: the total number of processors N=20, z=0.8, w=1.2. Processor P 1 ~P 20 The release time r 1 ~ r 20 is an exponentially distributed random number. In addition, the following parameters are used in the genetic algorithm: population size PopSize=100, crossover probability p cros =0.6, mutation probability p mut =0.02, the number of retained elites E=5, and the termination condition is evolutionary algebra t=100. Table 1 shows the different tasks (W total =1.0~10.0) The experimental results of the comparison of two algorithms, wherein GA represents the global optimization genetic algorithm proposed by the present invention, and EA represents a commonly used exhaustive algorithm in the prior art.

[0196] Table 1. Experimental results of the comparison of two algorithms under different task loads

[0197]

[0198] The n...

Embodiment 2

[0205] This embodiment provides a system for realizing the solution method of the above-mentioned divisible task scheduling model, including a divisible task scheduling model building module and a divisible task scheduling model solving module connected in sequence;

[0206] The described separable task scheduling model building module is used to realize the following functions:

[0207] Record the total number of slave processors as N, P 0 main processor, {P i |i∈{1,2,...,N}} is the slave processor, slave processor P i The release time of is denoted as r i , from processor P i The start time of is denoted as s i ; Note that the number of slave processors participating in the calculation is n, and the divisible task is divided into n subtasks α 1 ,α 2 ,...,α n , z is the time spent on the link transmission unit task, w is the time required to calculate the unit task from the processor;

[0208] There are three kinds of constraints to be met from the processor release t...

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Abstract

The invention discloses a method and system for solving a distributable task scheduling model. The hybrid timing constraint distributable task scheduling model is built and solved with a genetic algorithm. According to the method and system, the releasing time of processors is sufficiently considered in the distributable task scheduling model, and the method and system are more reasonable and more effective; the running time of the genetic algorithm for solving the model is much shorter than the time of an exhaustive algorithm, and the optimal solution of the model can be more efficiently and more accurately solved.

Description

technical field [0001] The invention belongs to the related field of information technology, and relates to a method system for solving a divisible task scheduling model. Background technique [0002] Most of the existing divisible task scheduling models assume that all processors are idle at the beginning of new task allocation, but in fact, in a real parallel and distributed environment, when a new task arrives, many processors may still be idle. The calculation task assigned last time has not been completed, so it is still in the busy state, and it needs to wait for a certain period of time to change from the busy state to the idle state before it can participate in the calculation of the new task. Existing methods for solving separable task scheduling problems considering the release time mostly use the exhaustive method. Although this method can get the correct result, it will bring huge time overhead and low efficiency. Therefore, it is particularly important to desig...

Claims

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Application Information

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IPC IPC(8): G06F9/48G06F9/50
Inventor 王晓丽王宇平景祯彦胡丽娟孟坤李杰
Owner XIDIAN UNIV
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