Vehicular Network Coverage And Cache Replacement Strategy For Mobile Users

The development of wireless network technology and the popularization of intel-ligent mobile terminals have brought great convenience to our daily life.Data traffic has migrated from fixed networks to wireless networks.Concepts such as ultra-high-definition video and the Internet of Things have further promoted the explosive growth of mobile network data traffic.However,the current network access can not satisfy the user’s demand for mo-bility and bandwidth at the same time.Users access the mobile network in two main ways:mobile cellular network and wireless access points(APs).Mobile cellular net-work covers a wide range of areas,but it suffers severe performance degradation at high user densities due to bandwidth bottleneck.Wireless APs have higher bandwidth,but they usually require fixed access points and have small communication range,which makes them not scalable and can not support user mobility well.In order to mitigate the shortcomings of fixed APs,we introduced vehicle APs for better network coverage.Vehicles in urban areas usually have higher density and lower velocity,which can provide more network access opportunities and better network cov-erage.By leveraging the MPTCP protocol,we can connect to multiple networks with multiple network interfaces.However,due to the mobility of vehicle APs,the fol-lowing issues arise:(1)The mobile device needs to frequently scan for available APs which requires quite long time;(2)The distance between the vehicle AP and the mobile device changes all the time,and the traditional RSSI-based AP selection and handoff strategy will no longer apply.To solve the problems above,this paper designs a system that uses vehicle APs for network coverage.Based on the radio propagation model and the mobility model of the vehicle AP,we build a throughput model for estimating the expected throughput and expected communication time after the mobile device connects to the vehicle AP.The system collects vehicle AP information through a controller and uses the throughput model to filter and sort candidate vehicle APs.Because mobile devices have informa-tion such as available vehicle APs and the channels they are working on,the mobile device can avoid the time overhead of AP discovery;and AP selection and handoff strategies based on throughput models can efectively improve throughput and reduce service interruption time.We evaluated its performance through simulation experi-ments.The experimental results show that compared with the traditional RSSI-based handoff strategy,the strategy adopted in this system will increase the throughput by 30%.In addition,the increase in throughput does not always mean that the user experi-ence is improved.For key applications such as video transmission,the user experience is related not only to the average video quality,but also to other factors such as the average video quality variations,stalling frequency.In the mobile environment,the network bandwidth varies all the time,which makes it more challenge to improve the user experience.In order to further enhance the quality of experience,we have op-timized the video streaming using vehicle APs.We introduce caching to shorten the delay for users to obtain video blocks,and use the throughput model to adjust the bitrate requested by the video player to improve quality of experience.In order to improve the cache effectiveness and reduce the back-end traffic,we leverage the computing ca-pability of the vehicle AP to transcode high-bitrate video blocks into low-bitrate video blocks to satisfy user requests.As existing LFU cache replacement algorithms can not reflect the conversion relationship between blocks with high and low bitrates,we have modified the LFU cache replacement algorithm to fully take into consideration that low bitrate video blocks can be produced by high bitrate video blocks.During cache re-placement,the low bitrate video blocks are removed prior and high bitrate video blocks are retained as far as possible.