Understanding Processing Overheads of Network Coding-Based Content Distribution in VANETs

Content distribution in vehicular networks, such as multimedia file sharing and software updates, poses a great challenge due to network dynamics and high-speed mobility. In recent years, network coding has been shown to efficiently support distribution of content in such dynamic environments, thereby considerably enhancing the performance. However, the related work in the literature has mostly focused on theoretic or algorithmic aspects of network coding so far. In this paper, we provide an in-depth analysis on the implementation issues of network coding in wireless networks. In particular, we study the impact of resource constraints (namely CPU, disk, memory, and bandwidth) on the performance of network coding in the content distribution application. The contribution of this paper is twofold. First, we develop an abstract model of a general network coding process and evaluate the validity of the model via several experiments on real systems. This model enables us to find the key resource constraints that influence the network coding strategy and thus to efficiently configure network coding parameters in wireless networks. Second, we propose schemes that considerably improve the performance of network coding under resource constrained environments. We implement our overhead model in the QualNet network simulator and evaluate these schemes in a large-scale vehicular network. Our results show that the proposed schemes can significantly improve the network coding performance by reducing the coding overhead.