Evaluating user-centric multihomed flow management in multi-user scenarios

Modern mobile devices comprise multiple interfaces for heterogeneous network technologies. However, currently implemented mechanisms to decide which one(s) to use and distribute application flows accordingly (i.e., solving the multihomed flow management problem, MFM) are rather coarse and do not leverage the opportunities. A user-centric quality-aware (QA) MFM has been proposed which optimises network use based on user-perceivable metrics such as application quality as well as energy and monetary costs. This paper refines this approach by providing a single method for both real-time and elastic (i.e., TCP-based) traffic, and uses realistic available capacity estimation. We evaluate this method in OPNET-simulated LTE and WLAN mobile networks. We study the impact of methods used to trigger the decision algorithm, and investigate the influence of an increasing number of users employing the QA-MFM technique on both the user-perceivable metrics and the global network performance. We find that on-demand triggering performs better than a static periodic method. We also demonstrate that the proposed approach out-performs classical network selection techniques in terms of application quality. We also show that the QA-MFM is not too greedy as to not scale with a number of users, and has a positive effect on the network loads, by preemptively adapting applications parameters to match network conditions.