Traffic Predicting Model for Dynamic Spectrum Sharing Over 5G Networks

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.

@article{Alshaflut2018,
  title     = {Traffic Predicting Model for Dynamic Spectrum Sharing Over 5G Networks},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {6},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Ahmed Alshaflut and Vijey Thayananthan},
  doi       = {10.14569/IJACSA.2018.090650},
  url       = {https://doi.org/10.14569/IJACSA.2018.090650}
}