Middleware for Wireless Sensor Networks: An Outlook

In modern distributed computing, applications are rarely built directly atop operating system facilities, e.g., sockets. Higher-level middleware abstractions and systems are often employed to simplify the programmer’s chore or to achieve interoperability. In contrast, real-world wireless sensor network (WSN) applications are almost always developed by relying directly on the operating system. Why is this the case? Does it make sense to include a middleware layer in the design of WSNs? And, if so, is it the same kind of software system as in traditional distributed computing? What are the fundamental concepts, reasonable assumptions, and key criteria guiding its design? What are the main open research challenges, and the potential pitfalls? Most importantly, is it worth pursuing research in this field? This paper provides a (biased) answer to these and other research questions, preceded by a brief account on the state of the art in the field

Loupe: Verifying Publish-Subscribe Architectures with a Magnifying Lens

CONE

The Bus Goes Wireless: Routing-Free Data Collection with QoS Guarantees in Sensor Networks

Abstract—We present the low-power wireless bus (LWB), a new communication paradigm for QoS-aware data collection in lowpower sensor networks. The LWB maps all communication onto network floods by using Glossy, an efficient flooding architecture for wireless sensor networks. Therefore, unlike current solutions, the LWB requires no information of the network topology, and inherently supports networks with mobile nodes and multiple data sinks. A LWB prototype implemented in Contiki guarantees bounded end-to-end communication delay and duplicate-free, inorder packet delivery—key QoS requirements in many control and mission-critical applications. Experiments on two testbeds demonstrate that the LWB prototype outperforms state-of-theart data collection and link layer protocols, in terms of reliability and energy efficiency. For instance, we measure an average radio duty cycle of 1.69 % and an overall data yield of 99.97 % in a typical data collection scenario with 85 sensor nodes on Twist. I

Demo Abstract: Smart Antennas Made Practical: The SPIDA Way

WISENET (NES)CONE

Poster Abstract: Network Coding with Limited Overhearing

CONETGINSEN

Network Coding with Limited Overhearing

The two key benefits of network coding are increased reliability and throughput. Most network coding approaches for wireless networks rely on overhearing neighboring transmissions. Overhearing in sensor networks, however, is not energy-efficient. In this paper, we extend GinMAC, a state-of-the-art MAC protocol, applying network coding with limited overhearing. Our approach reduces the delay allocating less retransmission slots. Our results show that network coding with limited overhearing reduces the power consumption of GinMAC while maintaining the desired level of reliability

Mobile Systems Research with Drones

Robot vehicle platforms, often called “drones”, offer exciting new opportuni- ties for mobile computing. While many systems respond to device mobility (such as smartphones), drones allow computer systems to actively control device location, allowing them to interact with the physical world in new ways and with new-found scale, efficiency, or precision

Poster Abstract: Modeling an Electronically Switchable Directional Antenna for Low-power Wireless Networks

WISENET (NES

Efficient State Retention for Transiently-powered Embedded Sensing

We present state retention techniques to support embedded sensing applications on 32-bit microcontrollers whose energy provisioning is assisted through ambient harvesting or wireless energy transfer. As energy availability is likely erratic in these settings, applications may be unpredictably interrupted. To behave dependably, applications should resume from where they left as soon as energy is newly available. We investigate the fundamental building block necessary to this end, and conceive three mechanisms to checkpoint and restore a device's state on stable storage quickly and in an energy-efficient manner. The problem is unique in many regards; for example, because of the distinctive performance vs. energy trade-offs of modern 32-bit microcontrollers and the peculiar characteristics of current flash chips. Our results, obtained from real experiments using two different platforms, crucially indicate that there is no ``one-size-fits-all'' solution. The performance depends on factors such as the amount of data to handle, how in memory the data is laid out, as well as an application's read/write patterns

Model-based real-time testing of drone autopilots

Key to the operation of robot drones is the autopilot software that realizes the low-level control. The correctness of autopilot implementations is currently mainly verified based on simulations. These may overlook the timing aspects of control loop executions, which are however fundamental to dependable operation. We report on our experience in applying model-based real-time testing to Ardupilot, a widely adopted autopilot. We describe our approach at deriving a model of Ardupilot's core functionality and at reducing the model to enable practical testing. Our work reveals that Ardupilot may fail in meeting the time constraints associated to critical functionality, such as enabling fail-safe operation. Through controlled experiments, we demonstrate the real-world occurrence of such erroneous executions