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http://hdl.handle.net/1942/35454
Title: | Long Short-Term Memory Approach for Routing Optimization in Cloud ACKnowledgement Scheme for Node Network | Authors: | Kaja, S Shakshuki, EM YASAR, Ansar |
Editors: | Shakshuki, E YASAR, Ansar |
Issue Date: | 2021 | Publisher: | ELSEVIER SCIENCE BV | Source: | Shakshuki, E ; Yasar (Ed.). 12TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 4TH INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS- volume 184, ELSEVIER SCIENCE BV, p. 461 -468 | Series/Report: | Procedia CompuProcedia Computer Scienceter Science | Series/Report no.: | 184 | Abstract: | Routing optimization using machine learning has been receiving a lot of attention recently. Additionally, cloud computing is evolving exponentially in processing power and memory units. This paper proposes a routing optimization approach for a Cloud ACKnowledgement Scheme using machine learning techniques. Our proposed approach is based on synthetic generated data for respective node values in a network. Moreover, it involves a variant of Recurrent Neural Network called Long Short-Term Memory (LSTM). The machine learning model is developed using LSTM through a sliding-window technique. The results achieved are very encouraging. They show that the cloud can mostly predict whether the forthcoming transmission of a certain node in the network will be a success. (C) 2021 The Authors. Published by Elsevier B. V. | Keywords: | Machine Learning;Long Short-Term Memory;Acknowledgement Scheme;Acknowledgement Packets;Routing | Document URI: | http://hdl.handle.net/1942/35454 | ISSN: | 1877-0509 | DOI: | 10.1016/j.procs.2021.03.058 | ISI #: | 000672800000057 | Rights: | 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer -review under responsibility of the Conference Program Chair | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2022 |
Appears in Collections: | Research publications |
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