A green energy model for resource allocation in computational grid using differential evolution algorithm

2021 ◽  
Author(s):  
Mahnaz Rafie
Keyword(s):  
Resource Allocation ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Computational Grid ◽  
Energy Model ◽  
Green Energy ◽  
Evolution Algorithm

Green Energy Model for Grid Resource Allocation

2014 ◽  
Vol 6 (2) ◽  
pp. 52-73 ◽  
Author(s):  
Achal Kaushik ◽  
Deo Prakash Vidyarthi
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Computational Grid ◽  
Energy Model ◽  
Green Energy ◽  
Energy Utilization ◽  
Theoretic Model ◽  
Performance Study ◽  
Characteristic Parameters ◽  
Grid Resource

The computational grid helps in faster execution of compute intensive jobs. Many characteristic parameters are intended to be optimized while making resource allocation for job execution in computational grid. Most often, the green energy aspect, in which one tries for better energy utilization, is ignored while allocating the grid resources to the jobs. The conventional systems, which propose energy efficient scheduling strategies, ignore other Quality of Service parameters while scheduling the jobs. The proposed work tries to optimize the energy in resource allocation to make it a green energy model. It explores how effectively the jobs submitted to the grid can be executed for optimal energy uses making no compromise on other desired related characteristic parameters. A graph theoretic model has been developed for this purpose. The performance study of the proposed green energy model has been experimentally evaluated by simulation. The result reveals the benefits and gives an insight for an energy efficient resource allocation.

A Green Energy Model for Resource Allocation in Computational Grid

2014 ◽  
Vol 58 (7) ◽  
pp. 1530-1547 ◽  
Author(s):  
Achal Kaushik ◽  
Deo Prakash Vidyarthi
Keyword(s):  
Resource Allocation ◽  
Computational Grid ◽  
Energy Model ◽  
Green Energy

scholarly journals Innovative Approach in Modeling Business Processes with a Focus on Improving the Allocation of Human Resources

2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Almir Djedovic ◽  
Almir Karabegovic ◽  
Zikrija Avdagic ◽  
Samir Omanovic
Keyword(s):  
Resource Allocation ◽  
Differential Evolution ◽  
Simulation Model ◽  
Business Processes ◽  
Process Mining ◽  
Fitness Function ◽  
Differential Evolution Algorithm ◽  
Statistical Techniques ◽  
Novel Approach ◽  
Evolution Algorithm

Organizations can improve efficiency of process execution through a correct resource allocation, as well as increase income, improve client satisfaction, and so on. This work presents a novel approach for solving problems of resource allocation in business processes which combines process mining, statistical techniques, and metaheuristic algorithms for optimization. In order to get more reliable results of the simulation, in this paper, we use process mining analysis and statistical techniques for building a simulation model. For finding optimal human resource allocation in business processes, we use the improved differential evolution algorithm with population adaptation. Because of the use of a stochastic simulation model, noise appears in the output of the model. The differential evolution algorithm is modified in order to include uncertainty in the fitness function. In the end, validation of the model was done on three different data sets in order to demonstrate the generality of the approach, and the comparison with the standard approach from the literature was done. The results have shown that this novel approach gives solutions which are better than the existing model from literature.

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