Optimizing Transfer Efficiency in Multi-cloud Storage Systems with Edge and Fog Computing

Nitesh Bharot; Nisha Ghangare; Priyanka Verma

doi:10.1007/978-3-031-64076-6_18

Optimizing Transfer Efficiency in Multi-cloud Storage Systems with Edge and Fog Computing

Nitesh Bharot
, Nisha Ghangare
, Priyanka Verma

University of Galway

Research output: Chapter in Book or Conference Publication/Proceeding › Conference Publication › peer-review

Abstract

Multi-cloud environments have emerged as a promising solution for computing, offering scalability, fault tolerance, and vendor flexibility. However, efficient data transfer between multiple cloud providers and data owners is crucial for ensuring optimal performance and timely execution of workloads. This paper explores the challenges associated with data transfer rates in multi-cloud storage systems and discusses various optimization strategies to improve data transfer efficiency. It highlights the limitations of single-cloud storage systems and the unresolved issues related to data transfer in conventional models. To address these challenges, a comprehensive architecture is proposed, integrating multiple cloud storage services and leveraging fog and edge computing paradigms. The study aims to optimize the data transfer efficiency in multi-cloud storage systems.

Original language	English
Title of host publication	Advanced Network Technologies and Intelligent Computing - 3rd International Conference, ANTIC 2023, Proceedings
Editors	Anshul Verma, Pradeepika Verma, Kiran Kumar Pattanaik, Sanjay Kumar Dhurandher, Isaac Woungang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	278-289
Number of pages	12
ISBN (Print)	9783031640759
DOIs	https://doi.org/10.1007/978-3-031-64076-6_18
Publication status	Published - 2024
Event	3rd International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2023 - Varansi, India Duration: 20 Dec 2023 → 22 Dec 2023

Publication series

Name	Communications in Computer and Information Science
Volume	2090 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	3rd International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2023
Country/Territory	India
City	Varansi
Period	20/12/23 → 22/12/23

Keywords

Bandwidth
Edge computing
Fog computing
Multi-cloud
Transfer rate

Access to Document

10.1007/978-3-031-64076-6_18

Cite this

Bharot, N., Ghangare, N., & Verma, P. (2024). Optimizing Transfer Efficiency in Multi-cloud Storage Systems with Edge and Fog Computing. In A. Verma, P. Verma, K. K. Pattanaik, S. K. Dhurandher, & I. Woungang (Eds.), Advanced Network Technologies and Intelligent Computing - 3rd International Conference, ANTIC 2023, Proceedings (pp. 278-289). (Communications in Computer and Information Science; Vol. 2090 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-64076-6_18

Bharot, Nitesh ; Ghangare, Nisha ; Verma, Priyanka. / Optimizing Transfer Efficiency in Multi-cloud Storage Systems with Edge and Fog Computing. Advanced Network Technologies and Intelligent Computing - 3rd International Conference, ANTIC 2023, Proceedings. editor / Anshul Verma ; Pradeepika Verma ; Kiran Kumar Pattanaik ; Sanjay Kumar Dhurandher ; Isaac Woungang. Springer Science and Business Media Deutschland GmbH, 2024. pp. 278-289 (Communications in Computer and Information Science).

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title = "Optimizing Transfer Efficiency in Multi-cloud Storage Systems with Edge and Fog Computing",

abstract = "Multi-cloud environments have emerged as a promising solution for computing, offering scalability, fault tolerance, and vendor flexibility. However, efficient data transfer between multiple cloud providers and data owners is crucial for ensuring optimal performance and timely execution of workloads. This paper explores the challenges associated with data transfer rates in multi-cloud storage systems and discusses various optimization strategies to improve data transfer efficiency. It highlights the limitations of single-cloud storage systems and the unresolved issues related to data transfer in conventional models. To address these challenges, a comprehensive architecture is proposed, integrating multiple cloud storage services and leveraging fog and edge computing paradigms. The study aims to optimize the data transfer efficiency in multi-cloud storage systems.",

keywords = "Bandwidth, Edge computing, Fog computing, Multi-cloud, Transfer rate",

author = "Nitesh Bharot and Nisha Ghangare and Priyanka Verma",

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Bharot, N, Ghangare, N & Verma, P 2024, Optimizing Transfer Efficiency in Multi-cloud Storage Systems with Edge and Fog Computing. in A Verma, P Verma, KK Pattanaik, SK Dhurandher & I Woungang (eds), Advanced Network Technologies and Intelligent Computing - 3rd International Conference, ANTIC 2023, Proceedings. Communications in Computer and Information Science, vol. 2090 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 278-289, 3rd International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2023, Varansi, India, 20/12/23. https://doi.org/10.1007/978-3-031-64076-6_18

Optimizing Transfer Efficiency in Multi-cloud Storage Systems with Edge and Fog Computing. / Bharot, Nitesh; Ghangare, Nisha; Verma, Priyanka.
Advanced Network Technologies and Intelligent Computing - 3rd International Conference, ANTIC 2023, Proceedings. ed. / Anshul Verma; Pradeepika Verma; Kiran Kumar Pattanaik; Sanjay Kumar Dhurandher; Isaac Woungang. Springer Science and Business Media Deutschland GmbH, 2024. p. 278-289 (Communications in Computer and Information Science; Vol. 2090 CCIS).

Research output: Chapter in Book or Conference Publication/Proceeding › Conference Publication › peer-review

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AU - Bharot, Nitesh

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Y1 - 2024

N2 - Multi-cloud environments have emerged as a promising solution for computing, offering scalability, fault tolerance, and vendor flexibility. However, efficient data transfer between multiple cloud providers and data owners is crucial for ensuring optimal performance and timely execution of workloads. This paper explores the challenges associated with data transfer rates in multi-cloud storage systems and discusses various optimization strategies to improve data transfer efficiency. It highlights the limitations of single-cloud storage systems and the unresolved issues related to data transfer in conventional models. To address these challenges, a comprehensive architecture is proposed, integrating multiple cloud storage services and leveraging fog and edge computing paradigms. The study aims to optimize the data transfer efficiency in multi-cloud storage systems.

AB - Multi-cloud environments have emerged as a promising solution for computing, offering scalability, fault tolerance, and vendor flexibility. However, efficient data transfer between multiple cloud providers and data owners is crucial for ensuring optimal performance and timely execution of workloads. This paper explores the challenges associated with data transfer rates in multi-cloud storage systems and discusses various optimization strategies to improve data transfer efficiency. It highlights the limitations of single-cloud storage systems and the unresolved issues related to data transfer in conventional models. To address these challenges, a comprehensive architecture is proposed, integrating multiple cloud storage services and leveraging fog and edge computing paradigms. The study aims to optimize the data transfer efficiency in multi-cloud storage systems.

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BT - Advanced Network Technologies and Intelligent Computing - 3rd International Conference, ANTIC 2023, Proceedings

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Bharot N, Ghangare N, Verma P. Optimizing Transfer Efficiency in Multi-cloud Storage Systems with Edge and Fog Computing. In Verma A, Verma P, Pattanaik KK, Dhurandher SK, Woungang I, editors, Advanced Network Technologies and Intelligent Computing - 3rd International Conference, ANTIC 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2024. p. 278-289. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-64076-6_18