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http://hdl.handle.net/1942/33011
Title: | Queue based Vehicular Ad Hoc Network Prognostic Offloading Approach | Authors: | Guntuka, Sony Shakshuki, Elhadi M. Kaja, Siddardha YASAR, Ansar |
Issue Date: | 2020 | Publisher: | ELSEVIER SCIENCE BV | Source: | Procedia Computer Science 170, p. 584 -593. | Series/Report: | Procedia Computer Science | Series/Report no.: | 170 | Abstract: | Vehicular Ad hoc NETworking (VANET) enables a vehicle to connect with other vehicles and the surrounding devices such as Road Side Units (RSUs) and base-stations through a wireless network. There are challenging issues within VANET environment caused by the high demand of Internet access. These issues include an increase in the vehicle traffic and the necessity of dynamic topologies. Nowadays, the high usage of Internet in vehicles is also increasing the load on the cellular network base-stations. To alleviate the load from the base-stations, vehicles should be able to switch the communication between the cellular network and RSUs to offload the data. When a vehicle is not within the RSU signal range, it is still possible for the vehicle to exchange information using Vehicle-to-Vehicle (V2V) communication. The main aim of this paper is to predict the vehicles topology, identify multiple offloading paths and compute the costs of the identified paths. Towards this end, knowledge defined network is utilized. To deal with connection interruptions in V2V, we develop algorithms for predicting an efficient V2V offloading path using queues. These algorithms make it possible to reduce the response time, improve the resource management of the network and helps in efficient service connectivity. (C) 2020 The Authors. Published by Elsevier B.V. | Notes: | Guntuka, S (corresponding author), Acadia Univ, Jodrey Sch Comp Sci, Wolfville, NS B4P 2R6, Canada. 152874g@acadiau.ca |
Other: | Guntuka, S (corresponding author), Acadia Univ, Jodrey Sch Comp Sci, Wolfville, NS B4P 2R6, Canada. 152874g@acadiau.ca | Keywords: | VANET;RSU;Offloading path;Knowledge Defined Networking | Document URI: | http://hdl.handle.net/1942/33011 | DOI: | 10.1016/j.procs.2020.03.129 | ISI #: | WOS:000582714500075 | Rights: | © 2020 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 Chairs. 10.1016/j.procs.2020.03.129 | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2021 |
Appears in Collections: | Research publications |
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GuntukaSony_2020.pdf | Published version | 770.59 kB | Adobe PDF | View/Open |
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