Collaborative downloading in VANET using Network Coding

Abstract

Data downloading on the fly is the base of commercial data services in vehicular networks, such as office-onwheels and entertainment-on-wheels. Due to the sparse special distribution of roadside Base Stations (BS) along the road, downloading through Roadside-to-Vehicle (R2V) connections is intermittent. When multiple vehicles with geographical proximity have a common interest in certain objects to download, they can collaborate to significantly reduce their overall download time. In this paper, we investigate the application of Network Coding (NC) in collaborative downloading (CD). We focus on the R2V part of CD, and analytically derive probability distribution and the expected value of the amount of time necessary to deliver all of the information to the vehicles with and without NC. Our results show that using NC slightly improves the downloading time in addition to removing the need for having any sort of uplink communications from vehicles to the infrastructure.

Multiple Vehicles Collaborative Data Download Protocol via Network Coding

“…NC has been applied to the full data dissemination problem [15], the reliable multicasting problem [16] and V2V data dissemination in one-dimensional VANETs [9]. The authors in [10] propose an approach that uses NC in R2V data download while assuming perfect V2V transmission. Under the condition that there are two cooperative vehicles, the authors analytically derive the expected time needed to disseminate data from infrastructure to all vehicles.…”

Data Dissemination in Wireless Networks with Network Coding

“…On the other hand, when the size of the network keeps expanding, after a while we have P uv = 0 for some nodes in the network and that affects the trend of the dissemination delay. In Figure 1, after N = 30, the stopping time (from both the simulation and analytical 4 Noise Power is calculated for the bandwidth of 10MHz and in temperature 300K. This value, however, does not affect the result of the simulation.…”

“…where s u,v follows an exponential random variable with mean P · d(u, v) −2 and the N 0 is the variance of additive white Gaussian noise, assumed to be 4 × 10 −14 at all the receivers 4 , and z is the capture reception threshold whose value depends on channel coding and modulation. In our simulation, we set z = 45dBm.…”

“…Traditionally, the data dissemination problem over decentralized network architecture has focused on the impact of the dissemination algorithm designed to optimize a performance metric, such as dissemination latency (i.e., the time required for all nodes to acquire the entire file [3], [4]). Authors in [5], [6] showed that using Network Coding (NC) for dissemination in a wired network can improve dissemination latency.…”

“…In a simplified version of the all-to-all data-dissemination problem, a source file desired by all is divided into N mutually exclusive information packets, and each packet is stored at exactly one node in the network [1], [2]. Every node's objective is to acquire the remaining N − 1 pieces of the source file; the order in which each node receives the remaining information packets is not relevant.Traditionally, the data dissemination problem over decentralized network architecture has focused on the impact of the dissemination algorithm designed to optimize a performance metric, such as dissemination latency (i.e., the time required for all nodes to acquire the entire file [3], [4]). Authors in [5], [6] showed that using Network Coding (NC) for dissemination in a wired network can improve dissemination latency.…”