RESUMEN
Dependability and standardization are essential to the adoption of Wireless Sensor Networks (WSN) in industrial applications. Standards such as ZigBee, WirelessHART, ISA100.11a and WIA-PA are, nowadays, at the basis of the main process-automation technologies. However, despite the success of these standards, management of WSNs is still an open topic, which clearly is an obstacle to dependability. Existing diagnostic tools are mostly application- or problem-specific, and do not support standard-based multi-network monitoring. This paper proposes a WSN monitoring architecture for process-automation technologies that addresses the mentioned limitations. Specifically, the architecture has low impact on sensor node resources, uses network metrics already available in industrial standards, and takes advantage of widely used management standards to share the monitoring information. The proposed architecture was validated through prototyping, and the obtained performance results are presented and discussed in the final part of the paper. In addition to proposing a monitoring architecture, the paper provides an in-depth insight into metrics, techniques, management protocols, and standards applicable to industrial WSNs.
RESUMEN
The wireless backhaul has emerged as an attractive alternative to traditional fiber backhaul for 5G technology, offering greater flexibility and cost-effectiveness thanks to the availability of high bandwidths capable of achieving fiber-like data rates. However, the millimeter-wave-based (mmWave) protocols, namely IEEE 802.11ad and later IEEE 802.11ay, suffer from a high susceptibility to obstruction, which only allows correct operation under Line-of-Sight conditions (LOS). Any sudden obstructions can significantly reduce the maximum achievable throughput, leading to delays exceeding acceptable limits for critical applications, and may even culminate in link failure in certain circumstances. Therefore, it is essential to assess how different types and durations of obstructions impact different network OSI layers to determine the feasibility of mmWave. WiGig-based technologies for wireless backhaul scenarios. This article describes a dataset collected from an experimental IEEE 802.11ad backhaul network, mmWave-based mesh network at 60 GHz, deployed in an outdoor environment. The data contains multi-layer information, including MAC, PHY, and network data, which provides valuable insights into the WiGig network behavior under three distinct scenarios. These scenarios include normal operation, long-term blocked scenario, and short-term blocked scenario, based on the type and duration of the blockage event crossing the LOS path. The dataset presents an extensive PHY, MAC and transport layer measurement campaign for an outdoor WiGig network, and thus it is a valuable resource for researchers and professionals interested in understanding the behavior and performance of real-life mmWave-based WiGig networks aimed for 5G backhauling.
RESUMEN
Connecting vehicles to the Internet is an emerging challenge of wireless networks. There are two competing methods for achieving this. First, the wireless local area network (WLAN) approach is based on the IEEE 802.11p standard (in its European version called ETSI ITS-G5) created for Cooperative-Intelligent Transportation System applications. Second, the cellular network approach is based on LTE/5G technologies which have been exploited in recent years to support vehicular applications. Advantages such as high bandwidth, high coverage and high reliability make cellular networks a great option for the vehicular environment. This article describes two datasets that support the analysis of WLAN (ETSI ITS-G5) and Cellular (LTE/5G) technologies in a real vehicular and road environment. The two datasets summarize the results obtained in a collection of network performance tests performed in the city of Aveiro, Portugal. In these tests, a set of vehicles (8 On-Board Units) moved randomly around the city, passing near a group of stationary nodes (11 Road-Side Units) uploading data to a server. In the WLAN dataset, data was sent using the ETSI ITS-G5 technology, whereas, in the Cellular dataset, data was sent using LTE/5G technologies. While testing, location, signal quality, and network performance data (achieved throughput, jitter, etc.) were collected. This dataset can support a realistic analysis of WLAN and Cellular performance in an environment that is not only vehicular but also urban, with obstacles and interference.
RESUMEN
As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users' activities and locations, sharing this information amongst the user's friends within a social networking site. We also present some screenshot results of our experimental prototype.