The Internet of Things is anticipated to connect billions of embedded devices equipped with sensors to perceive their surroundings. Thereby, the state of the real world will be available online and in real-time and can be combined with other data and services in the Internet to realize novel applications such as Smart Cities, Smart Grids, or Smart Healthcare. This requires an open representation of sensor data and scalable search over data from diverse sources including sensors. In this paper we show how the Semantic Web technologies RDF (an open semantic data format) and SPARQL (a query language for RDF-encoded data) can be used to address those challenges. In particular, we describe how prediction models can be employed for scalable sensor search, how these prediction models can be encoded as RDF, and how the models can be queried by means of SPARQL. Full article

In many applications, the quality of data gathered by sensor networks is directly related to the signal-to-noise ratio (SNR) of the sensor data being transmitted in the networks. Different from the SNR that is often used in measuring the quality of communication links, the SNR used in this work measures how accurately the data in the network packets represent the physical parameters being sensed. Hence, the signal here refers to the physical parameters that are being monitored by sensor networks; the noise is due to environmental interference and circuit noises at sensor nodes, and packet loss during network transmission. While issues affecting SNR at sensor nodes have been intensively investigated, the impact of network packet loss on data SNR has not attracted significant attention in sensor network design. This paper investigates the impact of packet loss on sensor network data SNR and shows that data SNR is dramatically affected by network packet loss. A data quality metric, based on data SNR, is developed and a cross-layer adaptive scheme is presented to minimize data quality degradation in congested sensor networks. The proposed scheme consists of adaptive downsampling and bit truncation at sensor nodes and intelligent traffic management techniques at the network level. Simulation results are presented to demonstrate the validity and effectiveness of the proposed techniques. Full article

In this paper, we study the channel allocation in multi-channel wireless ad hoc networks with directional antennas. In particular, we investigate the problem: given a set of wireless nodes equipped with directional antennas, how many channels are needed to ensure collision-free communications? We derive the upper bounds on the number of channels, which heavily depend on the node density and the interference ratio (i.e., the ratio of the interference range to the transmission range). We construct several scenarios to examine the tightness of the derived bounds. We also take the side-lobes and back-lobes as well as the signal path loss into our analysis. Our results can be used to estimate the number of channels required for a practical wireless network (e.g., wireless sensor network) with directional antennas. Full article

In this paper we present the design and implementation of the Constrained Application Protocol (CoAP) for TinyOS, which we refer to as TinyCoAP. CoAP seeks to apply the same application transfer paradigm and basic features of HTTP to constrained networks, while maintaining a simple design and low overhead. The design constraints of Wireless Sensor Networks (WSNs) require special attention in the design process of the CoAP implementation. We argue that better performance and minimal resource consumption can be achieved developing a native library for the operating system embedded in the network. TinyOS already includes in its distribution an implementation of CoAP called CoapBlip. However, this is based on a library not originally designed to meet the requirements of TinyOS. We demonstrate the effectiveness of our approach by a comprehensive performance evaluation. In particular, we test and evaluate TinyCoAP and CoapBlip in a real scenario, as well as solutions based on HTTP. The evaluation is performed in terms of latency, memory occupation, and energy consumption. Furthermore, we evaluate the reliability of each solution by measuring the goodput obtained in a channel affected by Rayleigh fading. We also include a study on the effects that high workloads have on a server. Full article

With the evolution and fusion of wireless sensor network and embedded camera technologies, distributed smart camera networks have emerged as a new class of systems for wide-area surveillance applications. Wireless networks, however, introduce a number of constraints to the system that need to be considered, notably the communication bandwidth constraints. Existing approaches for target tracking using a camera network typically utilize target handover mechanisms between cameras, or combine results from 2D trackers in each camera into 3D target estimation. Such approaches suffer from scale selection, target rotation, and occlusion, drawbacks typically associated with 2D tracking. In this paper, we present an approach for tracking multiple targets directly in 3D space using a network of smart cameras. The approach employs multi-view histograms to characterize targets in 3D space using color and texture as the visual features. The visual features from each camera along with the target models are used in a probabilistic tracker to estimate the target state. We introduce four variations of our base tracker that incur different computational and communication costs on each node and result in different tracking accuracy. We demonstrate the effectiveness of our proposed trackers by comparing their performance to a 3D tracker that fuses the results of independent 2D trackers. We also present performance analysis of the base tracker along Quality-of-Service (QoS) and Quality-of-Information (QoI) metrics, and study QoS vs. QoI trade-offs between the proposed tracker variations. Finally, we demonstrate our tracker in a real-life scenario using a camera network deployed in a building. Full article

An optimised logical topology facilitates the sensors of a network to communicate with each other with little overheads, lower energy consumption, and reduced latency. It also lengthens the lifetime of the network, provides scalability, and increases reliability in communications. However, designing an optimal logical topology for wireless sensor networks requires considering numerous factors. In this paper, we elaborately discuss these design issues and challenges. We also present a chain oriented logical topology, which offers solutions to those design issues. The proposed logical topology provides not only a communication abstraction, but also node management and resource management. The performance of the proposed topology is compared with other topologies with respect to energy consumptions, latency, and lifetime of the network. Full article

Smart embedded objects will become an important part of what is called the Internet of Things. However, the integration of embedded devices into the Internet introduces several challenges, since many of the existing Internet technologies and protocols were not designed for this class of devices. In the past few years, there have been many efforts to enable the extension of Internet technologies to constrained devices. Initially, this resulted in proprietary protocols and architectures. Later, the integration of constrained devices into the Internet was embraced by IETF, moving towards standardized IP-based protocols. In this paper, we will briefly review the history of integrating constrained devices into the Internet, followed by an extensive overview of IETF standardization work in the 6LoWPAN, ROLL and CoRE working groups. This is complemented with a broad overview of related research results that illustrate how this work can be extended or used to tackle other problems and with a discussion on open issues and challenges. As such the aim of this paper is twofold: apart from giving readers solid insights in IETF standardization work on the Internet of Things, it also aims to encourage readers to further explore the world of Internet-connected objects, pointing to future research opportunities. Full article