Abstract
The demand for broadband underwater communications is being pushed by the increasing use of Autonomous Underwater Vehicles (AUV) in underwater missions. IEEE 802.11, already used in AUV for above water communications, can also be employed underwater to enable cost-effective, high bandwidth, short range communications. However, the high RF attenuation underwater induces high variations of received power, which may affect the performance of existing rate adaptation algorithms designed for over-the-air networks. This paper evaluates the most relevant state-of-the-art IEEE 802.11 rate adaptation algorithms in underwater environment. Simulation results show the AARF algorithm outperforms the widely used Minstrel algorithm, as well as the CARA, RRAA and ONOE algorithms. Copyright 2015 ACM.

Abstract
Wireless Underground Networks (WUNs) have applications such as agriculture, border surveillance, maintenance of playing fields, and infrastructure monitoring. When designing a sensor network for one of these applications some of the sensors (communication nodes) will be buried underground, which means the propagation medium will be the soil or hybrid (air plus soil) in case of one of the nodes is aboveground. Thus, new models have to be implemented in existing simulators, in order to enable the proper simulation of these communications scenarios. This paper presents a new model, named underground model, and discusses its integration into the NS-3 simulator. The underground model enables the simulation of WUNs, including network topologies with underground and aboveground nodes. The accuracy of the underground model is shown for two frequency bands by comparing simulations results with experimental results. © 2015 ACM.

Abstract
Wireless Sensor Networks (WSNs) can be deployed using available hardware and software. The Contiki is an operative system compatible with a wide range of WSN hardware. A Contiki development environment named InstantContiki is also available and includes the Cooja simulator, useful to test WSN simulation scenarios prior to their deployment. Cooja can provide realistic results since it uses the full Contiki's source code and some motes can be emulated at the hardware level. However this implies extending the simulation runtime, which is heightened since the Cooja is single threaded, i.e, it makes use of a single core per instant of time, not taking advantage of the current multi-core processors. This chapter presents a framework to automate the configuration and execution of Cooja simulations. When a multi-core processor is available, this framework runs multiple simultaneous Cooja instances to reduce simulations runtime in exchange of higher CPU load and RAM usage.

Abstract
WSN can be deployed using widely available hardware and software solutions. The Contiki is an open source operative system compatible with a wide range of WSN hardware. A Contiki development environment named InstantContiki is also available and includes the Cooja simulation tool, useful for the simulation of WSN scenarios, prior to their deployment. This simulation tool can provide realistic results since it uses the full Contiki's source code and some motes can be emulated at the hardware level. However, the Cooja simulator uses one process per simulation, not taking advantage of multiple core processors. In this paper we propose a framework to automate the execution of simulations of multiple scenarios and configurations in Cooja. When a multiple cores processor is available, this framework can run multiple simultaneous Cooja instances, taking advantage of processing resources and contributing to reduce the total simulation runtime.

Abstract
A common problem in networking research and development is the duplicate effort of writing simulation and implementation code. This duplication can be avoided through the use of fast-prototyping methodologies, which enable reusing simulation code in real prototyping and in production environments. Although this functionality is already available by using ns-3 emulation, there are still limitations regarding the support of real network interfaces and easy configuration of the network settings, such as IP and MAC addresses. In this paper we propose an improved version of the ns-3 emulation component by introducing new functionalities that address these limitations. The new functionalities include the support of new types of real network interfaces and the easier integration of emulation nodes with existing networks by means of a new auto-configuration mechanism for ns-3 nodes. Experimental results obtained in a laboratorial testbed and in a real vehicular network testbed demonstrate the new functionalities proper operation, and their backwards compatibility with previously coded ns-3 scenarios. Copyright © 2015 ICST.

Abstract
Real-time monitoring applications may be used in a wireless sensor network (WSN) and may generate packet flows with strict quality of service requirements in terms of delay, jitter, or packet loss. When strict delays are imposed from source to destination, the packets must be delivered at the destination within an end-to-end delay (EED) hard limit in order to be considered useful. Since the WSN nodes are scarce both in processing and energy resources, it is desirable that they only transport useful data, as this contributes to enhance the overall network performance and to improve energy efficiency. In this paper, we propose a novel cross-layer admission control (CLAC) mechanism to enhance the network performance and increase energy efficiency of a WSN, by avoiding the transmission of potentially useless packets. The CLAC mechanism uses an estimation technique to preview packets EED, and decides to forward a packet only if it is expected to meet the EED deadline defined by the application, dropping it otherwise. The results obtained show that CLAC enhances the network performance by increasing the useful packet delivery ratio in high network loads and improves the energy efficiency in every network load.