Marco Zimmerling

Low-power wireless bus

We present the Low-Power Wireless Bus (LWB), a communication protocol that supports several traffic patterns and mobile nodes immersed in static infrastructures. LWB turns a multi-hop low-power wireless network into an infrastructure similar to a shared bus, where all nodes are potential receivers of all data. It achieves this by mapping all traffic demands on fast network floods, and by globally scheduling every flood. As a result, LWB inherently supports one-to-many, many-to-one, and many-to-many traffic. LWB also keeps no topology-dependent state, making it more resilient to link changes due to interference, node failures, and mobility than prior approaches. We compare the same LWB prototype on four testbeds with seven state-of-the-art protocols and show that: (i) LWB performs comparably or significantly better in many-to-one scenarios, and adapts efficiently to varying traffic loads; (ii) LWB outperforms our baselines in many-to-many scenarios, at times by orders of magnitude; (iii) external interference and node failures affect LWBs performance only marginally; (iv) LWB supports mobile nodes acting as sources, sinks, or both without performance loss.

FlockLab: a testbed for distributed, synchronized tracing and profiling of wireless embedded systems

Testbeds are indispensable for debugging and evaluating wireless embedded systems. While existing testbeds provide ample opportunities for realistic, large-scale experiments, they are limited in their ability to closely observe and control the distributed operation of resource-constrained nodes-access to the nodes is restricted to the serial port. This paper presents FlockLab, a testbed that overcomes this limitation by allowing multiple services to run simultaneously and synchronously against all nodes under test in addition to the traditional serial port service: tracing of GPIO pins to record logical events occurring on a node, actuation of GPIO pins to trigger actions on a node, and high-resolution power profiling. FlockLabs accurate timing information in the low microsecond range enables logical events to be correlated with power samples, thus providing a previously unattained level of visibility into the distributed behavior of wireless embedded systems. In this paper, we describe FlockLabs design, benchmark its performance, and demonstrate its capabilities through several real-world test cases.

pTunes: runtime parameter adaptation for low-power MAC protocols

We present pTUNES, a framework for runtime adaptation of low-power MAC protocol parameters. The MAC operating parameters bear great influence on the system performance, yet their optimal choice is a function of the current network state. Based on application requirements expressed as network lifetime, end-to-end latency, and end-to-end reliability, pTUNES automatically determines optimized parameter values to adapt to link, topology, and traffic dynamics. To this end, we introduce a flexible modeling approach, separating protocol-dependent from protocol-independent aspects, which facilitates using pTUNES with different MAC protocols, and design an efficient system support that integrates smoothly with the application. To demonstrate its effectiveness, we apply pTUNES to X-MAC and LPP. In a 44-node testbed, pTUNES achieves up to three-fold lifetime gains over static MAC parameters optimized for peak traffic, the latter being current-and almost unavoidable-practice in real deployments. pTUNES promptly reacts to changes in traffic load and link quality, reducing packet loss by 80 % during periods of controlled wireless interference. Moreover, pTUNES helps the routing protocol recover quickly from critical network changes, reducing packet loss by 70 % in a scenario where multiple core routing nodes fail.

Chaos: versatile and efficient all-to-all data sharing and in-network processing at scale

An important building block for low-power wireless systems is to efficiently share and process data among all devices in a network. However, current approaches typically split such all-to-all interactions into sequential collection, processing, and dissemination phases, thus handling them inefficiently. We introduce Chaos, the first primitive that natively supports all-to-all data sharing in low-power wireless networks. Different from current approaches, Chaos embeds programmable in-network processing into a communication support based on synchronous transmissions. We show that this design enables a variety of common all-to-all interactions, including network-wide agreement and data aggregation. Results from three testbeds and simulations demonstrate that Chaos scales efficiently to networks consisting of hundreds of nodes, achieving severalfold improvements over LWB and CTP/Drip in radio duty cycle and latency with almost 100 % reliability across all scenarios we tested. For example, Chaos computes simple aggregates, such as the maximum, in a 100-node multi-hop network within less than 90 milliseconds.

Energy-Efficient Routing in Linear Wireless Sensor Networks

Wireless sensor networks are used for structure monitoring and border surveillance. Typical applications, such as sensors embedded in the outer surface of a pipeline or mounted along the supporting structure of a bridge, feature a linear sensor arrangement. Economical power use of sensor nodes is essential for long-lasting operation. In this paper, we present MERR (minimum energy relay routing), a novel approach to energy-efficient data routing to a single control center in a linear sensor topology. Based on an optimal transmission distance, relay paths are established that aim for minimizing the total power consumption. We study MERR by both stochastic analysis and simulation, comparing it to other possible approaches and a theoretically optimal protocol. We find that MERR consumes 80% less power than conventional approaches and performs close to the theoretical optimum for practicable sensor networks.

Localized power-aware routing in linear wireless sensor networks

Energy-efficency is a key concern when designing protocols for wireless sensor networks (WSN). This is of particular importance in commercial applications where demonstrable return on investment is a crucial factor. One such commercial application that motivated this work is telemetry and control for freight railroad trains. Since a railroad train has a global linear structure by nature, we consider in this paper linear WSNs as sensor networks having, roughly, a linear topology. Aiming at such networks, we introduce two routing schemes that efficiently utilize energy: Minimum Energy Relay Routing (MERR) and Adaptive MERR (AMERR). We derive a theoretical lower bound on the optimal power consumption of routing in a linear WSN, where we assume a Poisson model for the distribution of nodes along a linear path. We evaluate the efficiency of our protocols with respect to the theoretical optimal lower bound and with respect to other well-known protocols. AMERR achieves optimal performance for practical deployment settings, while MERR rapidly approaches optimal performance as sensors are more densely deployed. Compared to other protocols, we show that MERR and AMERR are less complex and have better scalability. We also postulate how both protocols might be generalized to a two-dimensional WSN.

X-SENSE: Sensing in extreme environments

The field of Wireless Sensor Networks (WSNs) is now in a stage where serious applications of societal and economical importance are in reach. For example, it is well known that the global climate change dramatically influences the visual appearance of mountain areas like the European Alps. Very destructive geological processes may be triggered or intensified, impacting the stability of slopes, possibly inducing landslides. Unfortunately, the interactions between these complex processes is poorly understood. Therefore, one needs to develop wireless sensing technology as a new scientific instrument for environmental sensing under extreme conditions. Large variations in temperature, humidity, mechanical forces, snow coverage, and unattended operation play a crucial role in long-term deployments. We argue that, in order to significantly advance the application domain, it is inevitable that sensor networks be created as a quality scientific instrument with known and predictable properties, and not as a research toy delivering average observations at best. In this paper, key techniques for achieving highly reliable, yet resource efficent wireless sensor networks are discussed on the basis of productive wireless sensor networks measuring permafrost processes in the Swiss Alps.

ZeroCal: automatic MAC protocol calibration

Sensor network MAC protocols are typically configured for an intended deployment scenario once and for all at compile time. This approach, however, leads to suboptimal performance if the network conditions deviate from the expectations. We present ZeroCal, a distributed algorithm that allows nodes to dynamically adapt to variations in traffic volume. Using ZeroCal, each node autonomously configures its MAC protocol at runtime, thereby trying to reduce the maximum energy consumption among all nodes. While the algorithm is readily usable for any asynchronous low-power listening or low-power probing protocol, we validate and demonstrate the effectiveness of ZeroCal on X-MAC. Extensive testbed experiments and simulations indicate that ZeroCal quickly adapts to traffic variations. We further show that ZeroCal extends network lifetime by 50% compared to an optimal configuration with identical and static MAC parameters at all nodes.

Virtual Synchrony Guarantees for Cyber-physical Systems

By integrating computational and physical elements through feedback loops, CPSs implement a wide range of safety-critical applications, from high-confidence medical systems to critical infrastructure control. Deployed systems must therefore provide highly dependable operation against unpredictable real-world dynamics. However, common CPS hardware-comprising battery-powered and severely resource-constrained devices interconnected via low-power wireless-greatly complicates attaining the required communication guarantees. VIRTUS fills this gap by providing atomic multicast and view management atop resource-constrained devices, which together provide virtually synchronous executions that developers can leverage to apply established concepts from the dependable distributed systems literature. We build VIRTUS upon an existing best-effort communication layer, and formally prove the functional correctness of our mechanisms. We further show, through extensive real-world experiments, that VIRTUS incurs a limited performance penalty compared with best-effort communication. To the best of our knowledge, VIRTUS is the first system to provide virtual synchrony guarantees atop resource-constrained CPS hardware.

On Modeling Low-Power Wireless Protocols Based on Synchronous Packet Transmissions

Mathematical models play a pivotal role in understanding and designing advanced low-power wireless systems. However, the distributed and uncoordinated operation of traditional multi-hop low-power wireless protocols greatly complicates their accurate modeling. This is mainly because these protocols build and maintain substantial network state to cope with the dynamics of low-power wireless links. Recent protocols depart from this design by leveraging synchronous transmissions (ST), whereby multiple nodes simultaneously transmit towards the same receiver, as opposed to pair wise link-based transmissions (LT). ST improve the one-hop packet reliability to an extent that efficient multi-hop protocols with little network state are feasible. This paper studies whether ST also enable simple yet accurate modeling of these protocols. Our contribution to this end is two-fold. First, we show, through experiments on a 139-node test bed, that characterizing packet receptions and losses as a sequence of independent and identically distributed (i.i.d.) Bernoulli trials-a common assumption in protocol modeling but often illegitimate for LT-is largely valid for ST. We then show how this finding simplifies the modeling of a recent ST-based protocol, by deriving (i) sufficient conditions for probabilistic guarantees on the end-to-end packet reliability, and (ii) a Markovian model to estimate the long-term energy consumption. Validation using test bed experiments confirms that our simple models are also highly accurate, for example, the model error in energy against real measurements is 0.25%, a figure never reported before in the related literature.