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On scheduling transaction in grid computing using cuckoo search-ant colony optimization considering load

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Abstract

Scheduling of transactions in the grid computing system is known to be an NP-hard problem. In order to solve this problem, this paper introduces a hybrid approach named cuckoo search-ant colony optimization. The approach is to dynamically generate an optimal schedule by clustering the resources considering their load so as to complete the transactions within their deadlines as well as utilizing the resources in an efficient way. The approach also balances the load of the system before scheduling the transactions. We use cuckoo search method for making clusters of resources based on their load. We use ant colony optimization for selecting the appropriate and optimal resources. We evaluate the performance of the proposed algorithm with six existing algorithms. The results illustrate that an important advantage of the cuckoo search-ant colony optimization algorithm is its speed of clustering and ability to obtain faster and feasible load balanced schedules.

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Notes

  1. Atomicity, Consistency, Isolation, Durability.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Hamirpur, Hamirpur, Himachal Pradesh, India

    Dharmendra Prasad Mahato, Nagendra Pratap Singh & Vishal Kaushal

  2. Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India

    Jasminder Kaur Sandhu

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  1. Dharmendra Prasad Mahato
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Mahato, D.P., Sandhu, J.K., Singh, N.P. et al. On scheduling transaction in grid computing using cuckoo search-ant colony optimization considering load. Cluster Comput 23, 1483–1504 (2020). https://doi.org/10.1007/s10586-019-03016-x

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