research-article

Multi-objective Optimization of Data Placement in a Storage-as-a-Service Federated Cloud

Authors:

Amina Chikhaoui,

Laurent Lemarchand,

Kamel Boukhalfa,

Jalil BoukhobzaAuthors Info & Claims

ACM Transactions on Storage (TOS), Volume 17, Issue 3

Article No.: 22, Pages 1 - 32

https://doi.org/10.1145/3452741

Published: 16 August 2021 Publication History

Abstract

Cloud federation enables service providers to collaborate to provide better services to customers. For cloud storage services, optimizing customer object placement for a member of a federation is a real challenge. Storage, migration, and latency costs need to be considered. These costs are contradictory in some cases. In this article, we modeled object placement as a multi-objective optimization problem. The proposed model takes into account parameters related to the local infrastructure, the federated environment, customer workloads, and their SLAs. For resolving this problem, we propose CDP-NSGAII_IR, a Constraint Data Placement matheuristic based on NSGAII with Injection and Repair functions. The injection function aims to enhance the solutions’ quality. It consists to calculate some solutions using an exact method then inject them into the initial population of NSGAII. The repair function ensures that the solutions obey the problem constraints and so prevents from exploring large sets of unfeasible solutions. It reduces drastically the execution time of NSGAII. Experimental results show that the injection function improves the HV of NSGAII and the exact method by up to 94% and 60%, respectively, while the repair function reduces the execution time by an average of 68%.

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Multi-objective Optimization of Data Placement in a Storage-as-a-Service Federated Cloud

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cover image ACM Transactions on Storage

ACM Transactions on Storage Volume 17, Issue 3

August 2021

227 pages

ISSN:1553-3077

EISSN:1553-3093

DOI:10.1145/3477268

Editor:
Sam H. Noh
Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

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Publication History

Published: 16 August 2021

Accepted: 01 February 2021

Received: 01 November 2020

Published in TOS Volume 17, Issue 3

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Cited By

Ait-Oucheggou LRubini SBattou ABoukhobza J(2024)QM-ARC: QoS-aware Multi-tier Adaptive Cache Replacement StrategyFuture Generation Computer Systems10.1016/j.future.2024.107548(107548)Online publication date: Oct-2024
https://doi.org/10.1016/j.future.2024.107548
Wang YYang FZhou KLi CLiu CZhang JCheng Z(2024)An optimized learning-based directory placement policy with two-rounds selection in distributed file systemsFuture Generation Computer Systems10.1016/j.future.2023.12.012154:C(235-250)Online publication date: 25-Jun-2024
https://dl.acm.org/doi/10.1016/j.future.2023.12.012
Amiri A(2024)Column generation-based algorithm for fragment allocation: minimizing query splitting in distributed databasesInformation Technology and Management10.1007/s10799-024-00425-2Online publication date: 16-May-2024
https://doi.org/10.1007/s10799-024-00425-2
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