Probabilistic network coding techniques for vehicular ad-hoc networks

vehicular ad hoc network (vanet) is an emerging technology that enables moving vehicles on the road to connect and communicate as network devices. vanets enhance roads safety measures and improve traffic efficiency. however, due to the lack of centralization and the large number of highly mobile nodes, vanets are considered as highly congested networks with significant packet collisions and retransmissions. on the other hand, network coding is an emerging technique known to effectively utilize network resources by significantly reducing the number of transmissions. in network coding, intermediate nodes minimize the number of transmission by combining different packets before transmitting. however, a fundamental problem for network coding relay when it receives a packet is whether to wait for a coding opportunity to reduce network congestion; or to send the packet immediately without coding to reduce packet delay. this thesis proposes network coding techniques to reduce the number of transmissions and the bandwidth consumption in vanet multi-hop scenario. it also presents an analytical study on the trade-off between the average packet delay and the network throughput in network coding. it proposes a probabilistic approach for the intermediate nodes and therefore develops an analytical framework to present the effect of using such technique on the network performance. the system stability conditions have also been investigated. moreover, flows with different and same priorities are considered and different mechanisms that consider the nature of the different applications are proposed. for fair delay, this thesis provides the optimum transmission probability which achieves the minimum fair delay and results in an optimum throughput. while for different priority flows, a queue state based probabilistic scheduling schemes are proposed to avoid unbounded packet delays. to highlight the result, for symmetric rate flows, fairness scheme shows that the optimum fair delay can be achieved with probability of transmission of 0.5. it also shows that despite the flow data rate, using this probability will result in 33% improvement in the bandwidth consumption, and in an equal hop delay for both flows that is 0.5/?, where ? is the average flow data rate. moreover, for asymmetric rate flows the work provides the optimum transmission probability and its corresponding fair delay and throughput improvement. simulation is carried out to verify the analytical results where it is closely matched the theoretical results

On the maximum throughput of two-hop wireless network coding

Network coding has shown the promise of significant throughput improvement. In this paper, we study the throughput of two-hop wireless network coding and explore how the maximum throughput can be achieved under a random medium access scheme. Unlike previous studies, we consider a more practical network where the structure of overhearing status between the intended receivers and the transmitters is arbitrary. We make a formal analysis on the network throughput using network coding upon the concept of network coding cliques (NCCs). The analysis shows that the maximum normalized throughput, subject to fairness requirement, is n/n+m, where n is the number of transmitters and m is the number of NCCs in a 2-hop wireless network. We have also found that this maximum throughput can be achieved under a random medium access scheme when the medium access priority of the relay node is equal to the number of NCCs in the network. Our theoretical findings have been validated by simulation as well