17,880 research outputs found

    Portability, compatibility and reuse of MAC protocols across different IoT radio platforms

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    To cope with the diversity of Internet of Things (loT) requirements, a large number of Medium Access Control (MAC) protocols have been proposed in scientific literature, many of which are designed for specific application domains. However, for most of these MAC protocols, no multi-platform software implementation is available. In fact, the path from conceptual MAC protocol proposed in theoretical papers, towards an actual working implementation is rife with pitfalls. (i) A first problem is the timing bugs, frequently encountered in MAC implementations. (ii) Furthermore, once implemented, many MAC protocols are strongly optimized for specific hardware, thereby limiting the potential of software reuse or modifications. (iii) Finally, in real-life conditions, the performance of the MAC protocol varies strongly depending on the actual underlying radio chip. As a result, the same MAC protocol implementation acts differently per platform, resulting in unpredictable/asymmetrical behavior when multiple platforms are combined in the same network. This paper describes in detail the challenges related to multi-platform MAC development, and experimentally quantifies how the above issues impact the MAC protocol performance when running MAC protocols on multiple radio chips. Finally, an overall methodology is proposed to avoid the previously mentioned cross-platform compatibility issues. (C) 2018 Elsevier B.V. All rights reserved

    Real-time image streaming over a low-bandwidth wireless camera network

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    In this paper we describe the recent development of a low-bandwidth wireless camera sensor network. We propose a simple, yet effective, network architecture which allows multiple cameras to be connected to the network and synchronize their communication schedules. Image compression of greater than 90% is performed at each node running on a local DSP coprocessor, resulting in nodes using 1/8th the energy compared to streaming uncompressed images. We briefly introduce the Fleck wireless node and the DSP/camera sensor, and then outline the network architecture and compression algorithm. The system is able to stream color QVGA images over the network to a base station at up to 2 frames per second. © 2007 IEEE

    Powertrace: Network-level Power Profiling for Low-power Wireless Networks

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    Low-power wireless networks are quickly becoming a critical part of our everyday infrastructure. Power consumption is a critical concern, but power measurement and estimation is a challenge. We present Powertrace, which to the best of our knowledge is the first system for network-level power profiling of low-power wireless systems. Powertrace uses power state tracking to estimate system power consumption and a structure called energy capsules to attribute energy consumption to activities such as packet transmissions and receptions. With Powertrace, the power consumption of a system can be broken down into individual activities which allows us to answer questions such as “How much energy is spent forwarding packets for node X?”, “How much energy is spent on control traffic and how much on critical data?”, and “How much energy does application X account for?”. Experiments show that Powertrace is accurate to 94% of the energy consumption of a device. To demonstrate the usefulness of Powertrace, we use it to experimentally analyze the power behavior of the proposed IETF standard IPv6 RPL routing protocol and a sensor network data collection protocol. Through using Powertrace, we find the highest power consumers and are able to reduce the power consumption of data collection with 24%. It is our hope that Powertrace will help the community to make empirical energy evaluation a widely used tool in the low-power wireless research community toolbox
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