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Authors: Arun Ramamurthy 1 ; Priyanka Pantula 2 ; Mangesh Gharote 1 ; Kishalay Mitra 2 and Sachin Lodha 1

Affiliations: 1 TCS Research and Innovation, Tata Consultancy Services, India ; 2 Indian Institute of Technology, Hyderabad, India

Keyword(s): Cloud Computing, Scientific Workflow, Resource Allocation, Multi-objective Optimization, NSGA-II, Chance Constrained Programming.

Abstract: Providing resources and services from various cloud providers is now an increasingly promising paradigm. Workflow applications are becoming increasingly computation-intensive or data-intensive, with resource allocation being maintained in terms of pay per usage. In this paper, a multi-objective optimization study for scientific workflow in a cloud environment is proposed. The aim is to minimize execution time and purchasing cost simultaneously while satisfying the demand requirements of customers. The uncertainties present in the model are identified and handled using a well-known technique called Chance Constrained Programming (CCP) for real-world implementation. The model is solved using the Non-dominated Sorting Genetic Algorithm – II (NSGA-II). This comprehensive study shows that the solutions obtained on considering uncertainties vary from the deterministic case. Based on the probability of constraint satisfaction, the objective functions improve but at the cost of reliability o f the solution. (More)

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Paper citation in several formats:
Ramamurthy, A.; Pantula, P.; Gharote, M.; Mitra, K. and Lodha, S. (2021). Multi-objective Optimization for Virtual Machine Allocation in Computational Scientific Workflow under Uncertainty. In Proceedings of the 11th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-510-4; ISSN 2184-5042, SciTePress, pages 240-247. DOI: 10.5220/0010453302400247

@conference{closer21,
author={Arun Ramamurthy. and Priyanka Pantula. and Mangesh Gharote. and Kishalay Mitra. and Sachin Lodha.},
title={Multi-objective Optimization for Virtual Machine Allocation in Computational Scientific Workflow under Uncertainty},
booktitle={Proceedings of the 11th International Conference on Cloud Computing and Services Science - CLOSER},
year={2021},
pages={240-247},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010453302400247},
isbn={978-989-758-510-4},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Cloud Computing and Services Science - CLOSER
TI - Multi-objective Optimization for Virtual Machine Allocation in Computational Scientific Workflow under Uncertainty
SN - 978-989-758-510-4
IS - 2184-5042
AU - Ramamurthy, A.
AU - Pantula, P.
AU - Gharote, M.
AU - Mitra, K.
AU - Lodha, S.
PY - 2021
SP - 240
EP - 247
DO - 10.5220/0010453302400247
PB - SciTePress