Tri Feature Streaming Approximation Based Random Placement and Location Selection for Macro Cells Units for Improved Data Rate in 5G-SDN Networks
S.Sasikala
, S.L.Swarna , D.Kokila
5G, SDN, MIMO, Macro Cell, Small Cell, Bandwidth Utilization, Streaming Rate, TSA Model.
The growing need of higher data rate streaming challenges the network service providers. The 5G network has been emerged to improve the streaming performance and set of algorithms available for the development of bandwidth utilization and streaming performance. The earlier methods suffer to achieve higher performance in terms of streaming and bandwidth utilization. To improve the performance, an Tri Feature Streaming Approximation technique is presented in this paper. The Tri feature streaming approximation technique is aimed to maintain the streaming performance with the features of cell units, bandwidth utilization, and congestion. Any sink node has been analyzed for the routes available, streaming performance, bandwidth utilization, presence of micro/macro/small units, MMO units and so on. Based on the above mentioned features, three factors have been analyzed as route support, cell support, and bandwidth support. Based on these values, tri feature streaming performance has been approximated. Approximated result has been used to find the suitability of routes to maintain the streaming performance and performs random placement of cells required. The proposed method improves the performance of streaming and bandwidth utilization.
"Tri Feature Streaming Approximation Based Random Placement and Location Selection for Macro Cells Units for Improved Data Rate in 5G-SDN Networks", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.7, Issue 4, page no.592-598, April-2022, Available :https://ijnrd.org/papers/IJNRD2204067.pdf
Volume 7
Issue 4,
April-2022
Pages : 592-598
Paper Reg. ID: IJNRD_180930
Published Paper Id: IJNRD2204067
Downloads: 000118812
Research Area: Science & Technology
Country: Namakkal, Tamil Nadu, India
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
