Enhancing the LTEbased intelligent transportation systems performance Abstract   Intelligent transportation system is considered as one of the main features of the new generation wireless systems, where both of high speed data transmission and processing play a crucial role. This work presents two propositions in order to attain the performance improvement for both of data transmission and processing speed. Thus, the presented work consists of deriving a clustering algorithm based on a weighting algorithm for the head assignments processes, and emphasizing the parallelprocessing technique based on variety wavelet baby functions, respectively. Accordingly, both of the data transmission speed and power will be examined.  In order to verify the findings, a simulation has been done and compared with the following clustering algorithms; namely DMAC, PC, DBC, and LowerID DCA. This comparison is based on the following factors; namely efficiency factors involved in this investigation; namely complementary cumulative distributions, bit rates, energy efficiency, the cluster head life time and the ordinary nodes reattachinghead average times. The depicted results for the cluster head duration at 20 kms show a remarkable system stability based on both the clustering overhead, and the cluster head duration. The attained improvements reach the 53% and 88.4% over the DBC work and the LowestID DCA work, respectively.

Survey and taxonomy of clustering algorithms in 5G Abstract   The largescale deployment of fifth generation (5G) is expected to produce a massive amount of data with high variability due to ultradensification and the rapid increase in a heterogeneous range of applications and services (e.g., virtual reality, augmented reality, and driverless vehicles), and network devices (e.g., smart gadgets and sensors). Clustering organizes network topology by segregating nodes with similar interests or behaviors in a network into logical groups in order to achieve networklevel and clusterlevel enhancements, particularly cluster stability, load balancing, social awareness, fairness, and quality of service. Clustering has been investigated to support mobile user equipment (UE) in access networks, whereby UEs form clusters themselves and may connect to BSs. In this paper, we present a comprehensive survey of the research work of clustering schemes proposed for various scenarios in 5G networks and highlight various aspects of clustering schemes, including objectives, challenges, metrics, characteristics, performance measures. Furthermore, we present open issues of clustering in 5G.