Traffic Predicting Model for Dynamic Spectrum Sharing Over 5G Networks
| Autor: | Ahmed Alshaflut, Vijey Thayananthan |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
General Computer Science
Wireless network business.industry Computer science 020206 networking & telecommunications 020302 automobile design & engineering 02 engineering and technology Traffic flow 0203 mechanical engineering Component (UML) 0202 electrical engineering electronic engineering information engineering Spectrum sharing business 5G Computer network |
| Zdroj: | International Journal of Advanced Computer Science and Applications. 9 |
| ISSN: | 2156-5570 2158-107X |
| DOI: | 10.14569/ijacsa.2018.090650 |
| Popis: | Recently, wireless networks and traffic requirements have been rapidly aggregated in diverse applications in 5G environments. For this reason, researchers have investigated the influences of this growth based on a user’s requirements inside these networks. However, the stream of traffic has been considered a crucial role for the user’s needs over 5G network. In this paper, gigantic data traffic is considered for enabling dynamic spectrum sharing over 5G networks. Thus, various accessing plans are covered to manage the overall network traffic. Additionally, it proposes a traffic predicting model for a technique of managing traffic when multiple requests are received to decrease delays. It has considered different significances related to a large size of traffic practices. Additionally, this work will guide us to enhance traffic solutions within massive requests over outsized networks. Systematically, it has focused on the traffic flow, starting from the accessing steps until passing on requests to suitable spectrum carriers. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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