The classical TCP/IP layered protocol architecture is beginning to show signs of age. In order to cope with problems such as the poor performance of wireless links and mobile terminals, including the high error rate of wireless network interfaces, power saving requirements, quality of service, and an increasingly dynamic network environment, a protocol architecture that considers cross-layer interactions seems to be required. This article describes a framework for further enhancements of the traditional IPbased protocol stack to meet current and future requirements. Known problems associated with the strictly layered protocol architecture are summarized and classified, and a first solution involving cross-layer design is proposed.

When networking researchers meet the task of doing simulations, there is always a need to evaluate the value of such models by measuring a set of well known network performance metrics. However, simulators in general and NS-3 in particular, require significant programming effort from the researcher in order to collect those metrics. This paper reports a contribution for NS-3 consisting of a new flow monitoring module that makes it easier to collect and save to persistent storage a common set of network performance metrics. The module automatically detects all flows passing through the network and stores in a file most of the metrics that a researcher might need to analyze about the flow, such as bitrates, duration, delays, packet sizes, and packet loss ratio.The value of this module is demonstrated using an easy to follow example. It is also validated by comparing the measurements of a simple scenario with the expected values. Finally, the performance of flow monitoring is characterized and shown to introduce small overheads.

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The eXplicit Control Protocol (XCP) was developed to overcome some of the limitations of TCP, such as low utilization in high bandwidth delay product networks, unstable throughput, large queue build-up, and limited fairness. XCP, however, requires that each queue controller in a path knows the exact capacity of its link. In shared access media, e.g. IEEE 802.11, knowing the actual capacity of the channel is a difficult task.In this paper we propose modifications to the XCP algorithm that enable the utilization of XCP even when the capacity of a link is unknown. These modifications are validated through simulation.We also present the results of a comparison between the performance of the modified XCP and TCP, where XCP controlled flows result more stable, fairness increases, and the network delay becomes lower. In addition, as the bandwidth delay product increases, XCP is able to maintain near-maximum utilization while TCP decreases utilization.

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Available wireless sensor networks targeting the domain of healthcare enables the development of new applications and services in the context of E-Health. Such networks play an important role in several scenarios of patient monitoring, particularly those where data collection is vital for diagnosis and/or research purposes. However, despite emerging solutions, wearable sensors still depend on users' acceptance. One proposed solution to improve wearability relies on the use of smaller sensing nodes, requiring more energy-efficient networks, due to smaller room available for energy sources. In such context, smaller wireless sensor network nodes are required to work long time periods without human intervention and, at the same time, to provide appropriate levels of reliability and quality of service. Satisfaction of these two goals depends on several key factors, such as the routing protocol, the network topology, and energy efficiency. This paper offers a solution to increase the network lifetime based on a new Energy-Aware Objective Function used to design a Routing Protocol for Low-Power and Lossy Networks. The proposed Objective Function uses the Expected Transmission Count Metric and the Remaining Energy on each sensor node to compute the best paths to route data packets across the network. When compared with state of the art solutions, the proposed method increases the network lifetime by 21% and reduces the peaks of energy consumption by 12%. In this way, wireless sensor network nodes wearability can be improved, making them smaller and lighter, while maintaining the required performance.

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