BurstProbe: Debugging Time-Critical Data Delivery in Wireless Sensor Networks

In this paper we present BurstProbe, a new technique to accurately measure link burstiness in a wireless sensor network employed for time-critical data delivery. Measurement relies on shared probing slots that are embedded in the transmission schedule and used by nodes to assess link burstiness over time. The acquired link burstiness information can be stored in the node's flash memory and relied upon to diagnose transmission problems when missed deadlines occur. Thus, accurate diagnosis is achieved in a distributed manner and without the overhead of transmitting rich measurement data to a central collection point. For the purpose of evaluation we have implemented BurstProbe in the GinMAC WSN protocol and we are able to demonstrate it is an accurate tool to debug time-critical data delivery. In addition, we analyze the cost of implementingBurstProbe and investigate its effectiveness

Quality-of-service in wireless sensor networks: state-of-the-art and future directions

Wireless sensor networks (WSNs) are one of today’s most prominent instantiations of the ubiquituous computing paradigm. In order to achieve high levels of integration, WSNs need to be conceived considering requirements beyond the mere system’s functionality. While Quality-of-Service (QoS) is traditionally associated with bit/data rate, network throughput, message delay and bit/packet error rate, we believe that this concept is too strict, in the sense that these properties alone do not reflect the overall quality-ofservice provided to the user/application. Other non-functional properties such as scalability, security or energy sustainability must also be considered in the system design. This paper identifies the most important non-functional properties that affect the overall quality of the service provided to the users, outlining their relevance, state-of-the-art and future research directions

On the capacity of cluster-tree ZigBee networks

Modeling the fundamental performance limits of Wireless Sensor Networks (WSNs) is of paramount importance to understand their behavior under worst-case conditions and to make the appropriate design choices. In that direction this paper contributes with an analytical methodology for modeling cluster-tree WSNs where the data sink can either be static or mobile. We assess the validity and pessimism of analytical model by comparing the worst-case results with the values measured through an experimental test-bed based on Commercial-Off- The-Shelf (COTS) technologies, namely TelosB motes running TinyOS

Dimensioning and worst-case analysis of cluster-tree sensor networks

Modeling the fundamental performance limits of Wireless Sensor Networks (WSNs) is of paramount importance to understand their behavior under the worst-case conditions and to make the appropriate design choices. This is particular relevant for time-sensitive WSN applications, where the timing behavior of the network protocols (message transmission must respect deadlines) impacts on the correct operation of these applications. In that direction this paper contributes with a methodology based on Network Calculus, which enables quick and efficient worst-case dimensioning of static or even dynamically changing cluster-tree WSNs where the data sink can either be static or mobile. We propose closed-form recurrent expressions for computing the worst-case end-to-end delays, buffering and bandwidth requirements across any source-destination path in a cluster-tree WSN. We show how to apply our methodology to the case of IEEE 802.15.4/ZigBee cluster-tree WSNs. Finally, we demonstrate the validity and analyze the accuracy of our methodology through a comprehensive experimental study using commercially available technology, namely TelosB motes running TinyOS

Embedded Network Combining CAN, ZigBee and DC-PLC for Motorhome

International audience— Today, the number of motorhomes increases in Europe and North America as they offer greater individual freedom. As motorhome users spend the most of their time in their confined area, it seems essential to develop new solutions that make their life easier. In order to meet the new needs of customers, a new centralized architecture of a control system based on ubiquitous wired and wireless solutions is studied in this paper. The objective of this study is to verify the feasibility of ubiquitous technologies in this original environment. Different measurements have been conducted on a motorhome using Controller Area Networks (CAN), ZigBee and direct current power line communications (DC-PLC). Results have shown that these technologies may be used in a future hybrid control system in a motorhome

Opportunities of IoT in Fog Computing for High Fault Tolerance and Sustainable Energy Optimization

Today, the importance of enhanced quality of service and energy optimization has promoted research into sensor applications such as pervasive health monitoring, distributed computing, etc. In general, the resulting sensor data are stored on the cloud server for future processing. For this purpose, recently, the use of fog computing from a real-world perspective has emerged, utilizing end-user nodes and neighboring edge devices to perform computation and communication. This paper aims to develop a quality-of-service-based energy optimization (QoS-EO) scheme for the wireless sensor environments deployed in fog computing. The fog nodes deployed in specific geographical areas cover the sensor activity performed in those areas. The logical situation of the entire system is informed by the fog nodes, as portrayed. The implemented techniques enable services in a fog-collaborated WSN environment. Thus, the proposed scheme performs quality-of-service placement and optimizes the network energy. The results show a maximum turnaround time of 8 ms, a minimum turnaround time of 1 ms, and an average turnaround time of 3 ms. The costs that were calculated indicate that as the number of iterations increases, the path cost value decreases, demonstrating the efficacy of the proposed technique. The CPU execution delay was reduced to a minimum of 0.06 s. In comparison, the proposed QoS-EO scheme has a lower network usage of 611,643.3 and a lower execution cost of 83,142.2. Thus, the results show the best cost estimation, reliability, and performance of data transfer in a short time, showing a high level of network availability, throughput, and performance guarantee

Smart Sensor Data Acquisition in trains

Whether for work or leisure, we see a large number of people traveling by train every day. In order to ensure the comfort and safety of passengers, it must be checked whether the composition is working normally. For this purpose, a constant monitoring of a train must be done, followed by a diagnosis of the com-position, prediction of failures and production of alarms in the event of any anomaly. To perform monitoring on a train, it is necessary to collect data from sensors distributed along its carriages and send them to a software system that performs the diagnosis of the composition in a fast and efficient way. The description of the activities necessary for monitoring of a train imme-diately refers to topics such as distributed systems, since the intended system will have to integrate several sensors distributed along the train, or Smart Systems, since each sensor must have the capacity to not only acquire data, but also trans-mit it, preferably, wirelessly. However, there are some obstacles to the implementation of such a system. Firstly, the existence of sources of distortions and noise in the medium interferes both in the acquisition and transmission of data and secondly the fact that the sensors distributed along the train are not prepared to be connected directly to a software system. This dissertation seeks to find a solution for the problems described by im-plementing a data acquisition system that is distributed and takes advantage of the current technologies of low-cost sensor nodes as well as web technologies for sensor networks