research-article

InFeMo: Flexible Big Data Management Through a Federated Cloud System

Authors:

Christos L. Stergiou,

Konstantinos E. Psannis,

Brij B. GuptaAuthors Info & Claims

ACM Transactions on Internet Technology (TOIT), Volume 22, Issue 2

Article No.: 46, Pages 1 - 22

https://doi.org/10.1145/3426972

Published: 22 October 2021 Publication History

Abstract

This paper introduces and describes a novel architecture scenario based on Cloud Computing and counts on the innovative model of Federated Learning. The proposed model is named Integrated Federated Model, with the acronym InFeMo. InFeMo incorporates all the existing Cloud models with a federated learning scenario, as well as other related technologies that may have integrated use with each other, offering a novel integrated scenario. In addition to this, the proposed model is motivated to deliver a more energy efficient system architecture and environment for the users, which aims to the scope of data management. Also, by applying the InFeMo the user would have less waiting time in every procedure queue. The proposed system was built on the resources made available by Cloud Service Providers (CSPs) and by using the PaaS (Platform as a Service) model, in order to be able to handle user requests better and faster. This research tries to fill a scientific gap in the field of federated Cloud systems. Thus, taking advantage of the existing scenarios of FedAvg and CO-OP, we were keen to end up with a new federated scenario that merges these two algorithms, and aiming for a more efficient model that is able to select, depending on the occasion, if it “trains” the model locally in client or globally in server.

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Index Terms

InFeMo: Flexible Big Data Management Through a Federated Cloud System
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
2. Security and privacy
  1. Database and storage security

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Published In

cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 22, Issue 2

May 2022

582 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/3490674

Editor:
Ling Liu
Georgia Institute of Technology, USA

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Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 October 2021

Accepted: 01 October 2021

Revised: 01 September 2020

Received: 01 July 2020

Published in TOIT Volume 22, Issue 2

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https://dl.acm.org/doi/10.4018/IJSWIS.336550
Ma HGai Z(2024)Semantic Web-Based Structural Equation Modeling and Mediating Effects Are Used to Investigate Key FactorsInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.33564120:1(1-27)Online publication date: 7-Jan-2024
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Chui KSaini DMishra ASiddharth DJoshi PBansal RBansal S(2024)Development of Enhanced Chimp Optimization Algorithm (OFCOA) in Cognitive Radio Networks for Energy Management and Resource AllocationInternational Journal of Software Science and Computational Intelligence10.4018/IJSSCI.33589815:1(1-20)Online publication date: 21-Feb-2024
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Widodo AWidayanti RWisnujati AAnwar NBansal STabassum FRahaman M(2024)Port-to-Port Expedition Security Monitoring System Based on a Geographic Information SystemInternational Journal of Digital Strategy, Governance, and Business Transformation10.4018/IJDSGBT.33589713:1(1-20)Online publication date: 12-Jan-2024
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