This article presents a scheduling algorithm for the IEEE 802.11e hybrid coordination function under definition by the IEEE 802.11e task group. HCF can be used to provide IP quality of service guarantees in IEEE802.11e infrastructure WLANs. The enhanced distributed coordination function is mainly used for data transmission without QoS guarantees, but can also be used to decrease the transmission delay of QoS-sensitive traffic. Scheduling of queued packets follows a delay-earliest-due-date algorithm. The proposed algorithm is compatible with the link adaptation mechanisms implemented in commercial WLANs, as it limits the amount of time during which the stations control the wireless medium. The performance of the algorithm is evaluated through computer simulation and compared with the reference scheduler presented by the IEEE 802.11e task group.

This paper presents an evaluation of the QoS enhancements to the IEEE 802.11 standard, named IEEE 802.11e, currently under specification. Both the Enhanced Distributed Coordination Function (EDCF) and Hybrid Coordination Function (HCF) modes of Medium Access Control (MAC) operation are analysed and compared with legacy Distributed Coordination Function (DCF) and Point Coordination Function (PCF). Performance evaluation is attained through computer simulation of a scenario of 802.11b/e access to an IP core network through an Access Point (AP) in an infrastructure WLAN.

Wireless sensor and actuator networks (WSAN) constitute an emerging technology with multiple applications in many different fields. Due to the features of WSAN (dynamism, redundancy, fault tolerance, and self-organization), this technology can be used as a supporting technology for the monitoring of critical infrastructures (CIs). For decades, the monitoring of CIs has centered on supervisory control and data acquisition (SCADA) systems, where operators can monitor and control the behavior of the system. The reach of the SCADA system has been hampered by the lack of deployment flexibility of the sensors that feed it with monitoring data. The integration of a multihop WSAN with SCADA for CI monitoring constitutes a novel approach to extend the SCADA reach in a cost-effective way, eliminating this handicap. However, the integration of WSAN and SCADA presents some challenges which have to be addressed in order to comprehensively take advantage of the WSAN features. This paper presents a solution for this joint integration. The solution uses a gateway and a Web services approach together with a Web-based SCADA, which provides an integrated platform accessible from the Internet. A real scenario where this solution has been successfully applied to monitor an electrical power grid is presented.

In the past, Unmanned Aerial Vehicles (UAVs) were mostly used in military operations to prevent pilot losses. Nowadays, the fast technological evolution has enabled the production of a class of cost-effective UAVs that can service a plethora of public and civilian applications, especially when configured to work cooperatively to accomplish a task. However, designing a communication network among the UAVs is a challenging task. In this article, we propose a centralized UAV placement strategy, where UAVs are used as flying access points forming a mesh network, providing connectivity to ground nodes deployed in a target area. The geographical placement of UAVs is optimized based on a Multi-Objective Evolutionary Algorithm (MOEA). The goal of the proposed scheme is to cover all ground nodes using a minimum number of UAVs, while maximizing the fulfillment of their data rate requirements. The UAVs can employ different data rates depending on the channel conditions, which are expressed by the Signal-to-Noise-Ratio (SNR). In this work, the elitist Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is used to find a set of optimal positions to place UAVs, given the positions of the ground nodes. We evaluate the trade-off between the number of UAVs used to cover the target area and the data rate requirement of the ground nodes. Simulation results show that the proposed algorithm can optimize the UAV placement given the requirement and the positions of the ground nodes in the geographical area.

This paper presents the distributed transport for sensor networks (DTSN), a novel reliable transport protocol for convergecast and unicast communications in wireless sensor networks (WSNs). In DTSN, the source completely controls the loss recovery process in order to minimize the overhead associated with control and data packets. The basic loss recovery algorithm is based on selective repeat ARQ, employing both positive and negative acknowledgements. DTSN is able to detect when all packets of a session are lost, besides scattered gaps in the packet sequence. Caching at intermediate nodes is used to avoid the inefficiency of the strictly end-to-end transport reliability TCP-like model, commonly employed in broadband networks. Reliability differentiation is achieved by means of the smart integration of partial buffering at the source, integrated with erasure coding and caching at intermediate nodes. The simulation results attest the effectiveness of both the full reliability and the reliability differentiation mechanisms in DTSN.