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1To mitigate performance anomalies due to different transmission rates and to improve throughput performance in ad hoc networks, previous work has proposed a new method called user-cooperative mobility. This article also shows that the method achieves good improvement in ad hoc nodes, i.e., human users appropriately move. However, this method only employed a theoretical evaluation, which does not include detailed behaviors such as the capture effect or dynamic back-off time, which are considered to largely affect the performance in terms of throughput. Here, we employ an NS3 network simulator to clarify how the difference in throughput affects user mobility and throughput improvement in an ad hoc network. The result shows a huge difference in system throughput between theoretical estimations and simulations. This is caused by different transmitting opportunities due to the capture effect and the dynamic back-off time. In some cases, the system throughput will even drop when the throughput improvement ratio is under 1.0, being 0.64 when the throughput results from user moves are compared with those from no moves. We conclude that to improve the throughput as much as possible, a user should move based on the simulation results, which includes a capture effect and back-off time, instead of using only theoretical evaluation.

To mitigate performance anomalies due to different transmission rates and to improve throughput performance in ad-hoc networks, a previous work has proposed a new method called user cooperative mobility. It also showed that the method achieved good improvement when users appropriately move. However, it only employed theoretical evaluation which does not include detailed behavior such as capture effect or dynamic back-off time. We here employ NS3 network simulator to investigate differs from theoretical one. The result shows that capture effect and dynamic back-off time significantly affected on the transmitting opportunity, which leads to a huge difference in system throughput. The difference varies widely according to user mobility, by 172% at maximum and nearly 0 % at minimum. Thus, we conclude that theoretical evaluation requires a correction based on user mobility, in case of unequal transmitting opportunity for each node.