Sensor Data Dissemination Research Articles

Resilient Sensor Data Dissemination to Mitigate Link Faults in IoT Networks With Long-Haul Optical Wires for Power Transmission Grids

Resilient Sensor Data Dissemination to Mitigate Link Faults in IoT Networks With Long-Haul Optical Wires for Power Transmission Grids

Blockage Avoidance Based Sensor Data Dissemination in Multi-Hop MmWave Vehicular Networks

MmWave communication has emerged as a promising technology to fulfill requirements of gigabit-level data rates, so as to support the exchange of large amounts of sensor data in vehicle-to-vehicle (V2V) communications. However, inter-vehicle line-of-sight (LOS) blockages may significantly deteriorate the link quality and lead to data packet loss. Addationally, it is difficult to coordinate directional transmissions to broadcast massive sensor data to nearby vehicles timely for enhanced environmental awareness. To overcome these challenges, this article proposes a blockage avoidance based multi-hop sensor data dissemination (BAMD) scheme in a centralized manner. First, we propose a mmWave LOS link availability identification method based on the geometric relation among vehicles. Second, the problem of sensor data dissemination among all vehicles is formulated aiming at minimizing the overall transmission delay. To find an approximate solution, a novel transmission utility function based multi-hop data dissemination algorithm is designed jointly considering the distance between vehicles, packet queue, the number of LOS neighbors and concurrent transmissions. By theoretical analysis and extensive simulation, it is indicated that the proposed scheme can achieve a reliable and fast sensor data dissemination. In high-density case, BAMD can improve reliability by 20 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and reduce transmission delay by 82 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> compared with baselines.

RDDS: A Real-Time Data Distribution Service for Cyber-Physical Systems

One of the primary requirements in many cyber-physical systems (CPS) is that the sensor data derived from the physical world should be disseminated in a timely and reliable manner to all interested collaborative entities. However, providing reliable and timely data dissemination services is especially challenging for CPS since they often operate in highly unpredictable environments. Existing network middleware has limitations in providing such services. In this paper, we present a novel publish/subscribe-based middleware architecture called Real-time Data Distribution Service (RDDS). In particular, we focus on two mechanisms of RDDS that enable timely and reliable sensor data dissemination under highly unpredictable CPS environments. First, we discuss the semantics-aware communication mechanism of RDDS that not only reduces the computation and communication overhead, but also enables the subscribers to access data in a timely and reliable manner when the network is slow or unstable. Further, we extend the semantics-aware communication mechanism to achieve robustness against unpredictable workloads by integrating a control-theoretic feedback controller at the publishers and a queueing-theoretic predictor at the subscribers. This integrated control loop provides Quality-of-Service (QoS) guarantees by dynamically adjusting the accuracy of the sensor models. We demonstrate the viability of the proposed approach by implementing a prototype of RDDS. The evaluation results show that, compared to baseline approaches, RDDS achieves highly efficient and reliable sensor data dissemination as well as robustness against unpredictable workloads.

Sensor data dissemination systems using Web-based standards: a case study of publishing data in support of evapotranspiration models in California

Developing real-time and near real-time systems and models based on sensor data acquisition requires efficient access to distributed data sources. This is especially true when multi-source datasets are required for a comprehensive model. For example, developing daily spatial estimations of water evaporation and transpiration requires access to weather stations, combined with satellite imagery, and potentially weather prediction models as well. Most existing online data dissemination services support dissemination with ad-hoc methods, designed for specific limited purposes. General purpose access methods, required by a broadening range of uses, become increasingly important. In this study, we examine standard Web services for sensor data and how clients can consume such services seamlessly in their applications. Specifically, we describe a prototype system that supports Open Geospatial Consortium standards and the Network Data Access Protocol standard. This system allows standard access to weather stations, which provide comprehensive, timely weather data, as well as access to NOAA GOES satellite data for real-time remote sensing images of California. The prototype provides daily reference evapotranspiration map for California. In addition to presenting the technical details of the implementation, the costs and benefits of building such a standard-based sensor data dissemination system are discussed.

An Adaptive Data Dissemination Strategy for Wireless Sensor Networks

Future large-scale sensor networks may comprise thousands of wirelessly connected sensor nodes that could provide an unimaginable opportunity to interact with physical phenomena in real time. However, the nodes are typically highly resource-constrained. Since the communication task is a significant power consumer, various attempts have been made to introduce energy-awareness at different levels within the communication stack. Clustering is one such attempt to control energy dissipation for sensor data dissemination in a multihop fashion. The Time-Controlled Clustering Algorithm (TCCA) is proposed to realize a network-wide energy reduction. A realistic energy dissipation model is derived probabilistically to quantify the sensor network's energy consumption using the proposed clustering algorithm. A discrete-event simulator is developed to verify the mathematical model and to further investigate TCCA in other scenarios. The simulator is also extended to include the rest of the communication stack to allow a comprehensive evaluation of the proposed algorithm.