Analysis Methodology for Flow-level Evaluation of a Hybrid Mobile-Sensor Network

Our society uses a large diversity of co-existing wired and wireless networks in order to satisfy its communication needs. A cooper- ation between these networks can benefit performance, service availabil- ity and deployment ease, and leads to the emergence of hybrid networks. This position paper focuses on a hybrid mobile-sensor network identify- ing potential advantages and challenges of its use and defining feasible applications. The main value of the paper, however, is in the proposed analysis approach to evaluate the performance at the mobile network side given the mixed mobile-sensor traffic. The approach combines packet- level analysis with modelling of flow-level behaviour and can be applied for the study of various application scenarios. In this paper we consider two applications with distinct traffic models namely multimedia traffic and best-effort traffic.

LTE uplink scheduling - flow level analysis

Long Term Evolution (LTE) is a cellular technology foreseen to extend the capacity and improve the performance of current 3G cellular networks. A key mechanism in the LTE traffic handling is the packet scheduler, which is in charge of allocating resources to active flows in both the frequency and time dimension. In this paper we present a performance comparison of three distinct scheduling schemes for LTE uplink with main focus on the impact of flow-level dynamics resulting from the random user behaviour. We apply a combined analytical/simulation approach which enables fast evaluation of flow-level performance measures. The results show that by considering flow-level dynamics we are able to observe performance trends that would otherwise stay hidden if only packet-level analysis is performed.