An insect inspired approach for optimization of tasks scheduling in computational grids
- PDF / 2,009,057 Bytes
- 15 Pages / 595.276 x 790.866 pts Page_size
- 83 Downloads / 135 Views
SPECIAL ISSUE
An insect inspired approach for optimization of tasks scheduling in computational grids Debashreet Das1 · Chitta Ranjan Tripathy1 · Pradyumna Kumar Tripathy2 Received: 28 August 2020 / Revised: 21 September 2020 / Accepted: 27 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The article suggests a novel optimization algorithm named Lepidoptera butterfly approach (LBA) that is inspired from the behavior of insects, American butterflies and their counterparts. This algorithm keenly observes the behavior of the Lepidoptera insects and tries to find an optimal solution through a larger solution space. The proposed algorithm LBA mimics the behavioral aspects of these insects. The insects (butterflies) migrate more often from one land to another in search of food particles and reproduction of offsprings. If they find the food particles and climate of the new land suitable, these insects often reproduce their offsprings in this new land. Hence, the suggested approach classifies the network of grids into two subnetworks (or two different lands) and thereby, generates two sub-populations. The algorithm then considers each individual subnetwork and their subpopulations. In our case, these are the jobs that contribute to each subnetwork and the offsprings that are reproduced are called as tasks. Our algorithm finds the best tasks and best jobs in every subnetwork and finally combines them and try to allocate the tasks/jobs to resources considering the constraints like cost and make-span time. However, this scheduling of tasks is considered as an NP-Complete problem. The algorithm is tested using 30 runs for simulation under these two constraints. This article makes a comparison with different existing optimization techniques like GA, TLBO, etc. The results signifies that our proposed approach of LBA performs better as compared to others. This inspires the authors to study the performance behavior of this approach in optimizing the scheduling problem in a computational grid environment under the constraints like time and cost. Keywords Computational grids · Grid computing · Grid scheduling · Task optimization
1 Introduction Meta-Computing or grid computing is a type of distribution based computing, where the computational power in combination with other resources like storage space, CPU time, etc. gets exploited scientifically. This form of the grid can be used to tackle a complex project with large applications, which are supposed to be solved only by supercomputers * Debashreet Das [email protected] Chitta Ranjan Tripathy [email protected] Pradyumna Kumar Tripathy [email protected] 1
Department of Computer Science and Engineering, VSSUT, Burla, Sambalpur, Odisha, India
Department of Computer Science and Engineering, Silicon Institute of Technology, Bhubaneswar, India
2
[1]. In this model, the resources are spread over a wider geographical area with multiples networks that form the Grid. The grids can be classified in many forms like data-grid
Data Loading...
