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In this paper, we propose a user centric bandwidth allocation scheme for low latency data transmission in ultra dense vehicular networks. Various mobile devices such as mobile phones, sensors of vehicles or autonomous driving systems,require low latency and bandwidth intensive packet delivery between the devices and the Internet aiming to support real-time applications. In the ultra dense vehicular network, small base stations (SBSs) are densely deployed in a fixed geographic area to provides higher date rate. In further, each SBS cooperates with others to form clusters to better support seamless wireless data transmissions, and each mobile device dynamically plans its wireless connectivity for data transmission when it moves in the network. Specifically, each mobile device pre-allocates the amount of bandwidth from a cluster, formed by several SBSs, based on its expected movement, the delay and band-width requirement of the packet transmission and the resource availability of each cluster. Moreover, to effectively utilize the available network resource, each cluster also redistributes its residual bandwidth to the mobile devices pre-allocate bandwidth from it. Consequently, the latency of the data transmission can be better sustained in the ultra dense vehicular network.

In ultra dense WiFi networks, access points are deployed with high density in order to support Internet access for large amount of mobile users at the same time. Since the mobile users may not be uniformly distributed in the network, the heavy loaded access points and the interference among different access points would cause the network throughput degradation. Further, although increasing transmission power levels of access points could enhance network throughput, the energy efficiency would be low. Energy consumption is an increasingly important issue today so that the network performance needs to be improved in an energy efficient manner. Under this condition, we propose a distributed power adjustment scheme to intelligently maximize the throughput of the entire network without increasing transmission power in the presence of dynamic distributed mobile users. To validate the performance of our proposed scheme, we simulate various network conditions and the results show that our proposed scheme can sustain throughput with less energy consumption with less than 200 iterations.