With the 802.11 WLAN multimedia applications (Video, Audio, real-time voice over IP,…) increasing, providing Quality of Service (QoS) support becomes very important since the original standard doesn't take QoS into account. The standard offers access to the wireless users only regarding physical considerations. This can lead to overloaded access points (AP) and considerable degradation of the QoS. This paper deals with this problem. It focuses on the presentation of a QoS management solution for wireless communication systems. It mainly defends that a balanced distribution of mobile stations among the available access points leads to better performances of the Wireless LAN. Some OPNET simulations of the proposed approach are presented to show a better resources allocation and efficiency on QoS metrics. A protocol structure between mobiles and APs is also specified for the implementation of this approach. An SDL description and MSC simulation of this protocol is provided as a first step in its development.
The development of wireless acoustic sensor networks has driven the use of acoustic signals for target monitoring. Most monitoring applications require continuous network connectivity and data transfers, which can rapidly exhaust nodes’ energy. Consequently, sensors must collaborate in an adequate architecture to perform target recognition and localization tasks and then to send the results to a remote server with a reduced data volume. The design of an energy-efficient scheme that achieves acoustic target recognition and localization remains an open research problem. Accordingly, this article proposes a low-energy acoustic-based sensing scheme for target recognition and localization to be implemented in a cluster-based sensing approach designed to appropriately balance energy consumption and local processing performed by sensor nodes. A reduced set of low-complexity feature extraction methods in the time domain signal are used in the recognition process. The scheme uses the received energy of the acoustic signals for the target localization. This article details the network architecture, the scheme specification, and its implementation. The results show that the scheme can classify targets with 81.34% accuracy. It requires 3.2 mJ of energy when executed in MICAz, achieving 99% energy savings compared to streaming 3 s of an acoustic signal to a remote server.
International audienceIn this paper, we propose a VHDL-AMS implementation of a physical model of a microelectromechanical systems (MEMS) piezoelectric microgenerator. Such an executable model acts as a bridge between specifications and fabricated devices. Usually, physical and geometrical parameters of electromechanical parts of a system are only considered in lower levels of the design flow, typically using finite-element tools, which, despite their accuracy, do not allow efficient optimization of the structure properties and dimensions. Thus, it would be very interesting to have a model of the entire harvesting system (the MEMS piezoelectric microgenerator cascaded with the electronic circuit) to perform efficient optimization. Some features like damping effects and process fluctuations have considerable impact on the performance of MEMS, especially the resonant structures. We propose a method of integrating such features early in the design flow, while keeping the simulation time reasonable. The resulting model is reusable, predictive (comparable to experimental results) and respects Kirchhoff laws. Consequently, it can be integrated in global simulation of multidomain and mixed signal systems like wireless sensor nodes
In this paper, we present and evaluate a hardware implementation for user-driven and packet-loss tolerant image compression, especially designed to enable low-power image compression and communication over wireless sensors networks (WSNs). The proposed compression scheme, presented as a CMOS circuit, is intended to be embedded in the camera sensor.It will be considered as a co-processor for tasks related with image compression and data packetization, which unloads the main microcontroller so that it will spend less time in active mode. The interest of our solution is twofold. First, compression settings can be changed at runtime (upon reception of a request message sent by an end-user or according to the internal state of the camera sensor node). Second, the image compression chain includes a (block of) pixel interleaving scheme which significantly improves the robustness against packet loss in image communication. The main part of this paper focuses on the specification and the performances analysis of this solution when implemented on FPGA and ASIC circuits.
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