Emanuele Lattanzi

Energetic sustainability of routing algorithms for energy-harvesting wireless sensor networks

A new class of wireless sensor networks that harvest power from the environment is emerging because of its intrinsic capability of providing unbounded lifetime. While a lot of research has been focused on energy-aware routing schemes tailored to battery-operated networks, the problem of optimal routing for energy harvesting wireless sensor networks (EH-WSNs) has never been explored. The objective of routing optimization in this context is not extending network lifetime, but maximizing the workload that can be autonomously sustained by the network. In this work we present a methodology for assessing the energy efficiency of routing algorithms for networks whose nodes drain power from the environment. We first introduce the energetic sustainability problem, then we define the maximum energetically sustainable workload (MESW) as the objective function to be used to drive the optimization of routing algorithms for EH-WSNs. We propose a methodology that makes use of graph algorithms and network simulations for evaluating the MESW starting from a network topology, a routing algorithm and a distribution of the environmental power available at each node. We present a tool flow implementing the proposed methodology and we show comparative results achieved on several routing algorithms. Experimental results highlight that routing strategies that do not take into account environmental power do not provide optimal results in terms of workload sustainability. Using optimal routing algorithms may lead to sizeable enhancements of the maximum sustainable workload. Moreover, optimality strongly depends on environmental power configurations. Since environmental power sources change over time, our results prompt for a new class of routing algorithms for EH-WSNs that are able to dynamically adapt to time-varying environmental conditions.

Avian soundscapes and cognitive landscapes: theory, application and ecological perspectives

The soundscape is proposed as a phenomenological entity with which to investigate environmental complexity. In particular, the avian soundtope, which is defined as a place in which sound is intentionally structured by different bird species, is regarded as an agency acting to achieve several goals. In fact, the soundtope could be viewed as a special case of an eco-field used by birds, not only to establish territorial ownership and patrol an area but also as a means of locating and evaluating the availability of many other material and immaterial resources. The meaning of the multifaceted acoustic pattern produced by bird communities during the breeding season is discussed here under the acoustic niche hypothesis in terms of community coalescence and the permanent establishment of an inter-specific communication network. Furthermore, the spatial and temporal dimensions of a bird soundscape have also been analyzed and discussed in terms of their relationship with environmental proxies. A new Acoustic Complexity Index (ACI), coupled with the implementation (ACI plug-in) of a specific sound editor (WaveSurfer©), is proposed as a way of processing sound data efficiently, thus providing new opportunities to use the bird soundscape signature for landscape characterization and describing the ecological dynamics of long-term monitoring schemes.

Specification and Analysis of Power-Managed Systems

Dynamic power management encompasses several techniques for reducing energy dissipation in electronic systems by selective slowdown or shutdown of components. We present a theoretical framework for explaining and classifying different approaches to power management. Within this framework, we model power-manageable components, workloads, and controllers as discrete-event systems (DESs). The structure of these DESs is specified in terms of physical states (representing operation modes) and events (triggering state transitions), while system behavior is specified in terms of next-event and next-state functions. In particular, nondeterministic next-event and next-state functions are modeled by conditional probability distributions, according to generalized semi-Markov processes (GSMPs). The modeling framework provides a general denotational model for system specification and a rigorous execution semantics that enables event-driven simulation. We introduce a modeling framework, built on top of MathWorks Simulink, supporting the specification and execution of our model. In particular, we present templates for the Simulink simulator to execute GSMP models, and we describe how to use such templates for specifying, analyzing, and optimizing dynamic power-managed systems. Finally, we demonstrate the expressive power and versatility of the proposed approach by using the modeling framework and the simulator for the analysis of representative real-life case studies, including the Intel Xscale processor architecture, a multitasking real-time system, and a sensor network.

Energetic sustainability of environmentally powered wireless sensor networks

Environmentally-powered wireless sensor networks (WSNs) exploit renewable energy sources to make the lifetime of sensor nodes theoretically unlimited. This perspective requires a paradigm shift in the design of energy-aware WSNs: Instead of maximizing the lifetime under given energy constraints, we need to maximize the workload that can be sustained by a given distribution of environmental power. This paper formulates the maximum energetically sustainable workload problem (MESW) and we shows that it can be cast into an instance of a modified max-flow problem

VirtualSense: A Java-Based Open Platform for Ultra-Low-Power Wireless Sensor Nodes

Idleness has to be carefully exploited in wireless sensor networks (WSNs) to save power and to accumulate the energy possibly harvested from the environment. State-of-the-art microcontroller units provide a wide range of ultra-low-power inactive modes with sub-millisecond wakeup time that can be effectively used for this purpose. At the same time they are equipped with 16-bit RISC architectures clocked at tens of MHz, which make them powerful enough to run a Java-compatible virtual machine (VM). This makes it possible to bring the benefits of a virtual runtime environment into power-constrained embedded systems. VMs, however, risk to impair the effectiveness of dynamic power management as they are seen as always-active processes by the scheduler of the operating system in spite of the idleness of the threads running on top of them. Avoiding to keep sensor nodes busy when they could be idle is mandatory for the energetic sustainability of WSNs. While most of the tasks of a sensor node are inherently event-driven, the functioning of its hardware-software components is not, so that they require to be redesigned in order to exploit idleness. This paper presents VirtualSense, an open-hardware open-source ultra-low-power reactive wireless sensor module featuring a Java-compatible VM.

Spatial and temporal variation of bird dawn chorus and successive acoustic morning activity in a Mediterranean landscape

Ecoacoustic techniques using multiple acoustic sensors and two metrics of the acoustic community – the acoustic complexity index (ACI) and the chorus ratio (CR) – were successfully used to describe and characterize the morning acoustic activity of birds according to three equal temporal intervals during spring 2013: Dawn Chorus, Post Chorus 1, and Post Chorus 2.The metrics were applied across five Italian Mediterranean locations (Valenza, Madonna dei Colli, Monte Curto, Virolo, Croce di Tergagliana) that differed by land-cover typologies. Results from the ACI metrics showed a peak during the Dawn Chorus and a visible lull close to sunrise between Dawn Chorus and Post Chorus 1.The lull was evident in all localities except Valenza, where singing activity was relatively constant across the successive morning intervals. Temperature and vegetation structure were confirmed as important factors associated with morning acoustic activities. Vegetation evenness and temperature across the season was negatively correlated with ACI, whereas CR was positively correlated with temperature and vegetation diversity. Of the 33 species of birds identified during the maximum dawn chorus activity, Blackcap, Blackbird, European Robin, and Great Tit were acoustically dominant and their activity was significantly higher before sunrise except for Blackcap, whose acoustic activity showed no significant differences across time intervals. The dawn chorus is one of the most conspicuous behaviours of birds, engendering much speculation but no definitive, univocal explanations. The ecoacoustic approach opens a new perspective for investigating this complex phenomenon.

Self-adapting maximum flow routing for autonomous wireless sensor networks

Autonomous wireless sensor networks are subject to power, bandwidth, and resource limitations that can be represented as capacity constraints imposed to their equivalent flow networks. The maximum sustainable workload (i.e., the maximum data flow from the sensor nodes to the collection point which is compatible with the capacity constraints) is the maxflow of the flow network. Although a large number of energy-aware routing algorithms for ad-hoc networks have been proposed, they usually aim at maximizing the lifetime of the network rather than the steady-state sustainability of the workload. Energy harvesting techniques, providing renewable supply to sensor nodes, prompt for a paradigm shift from energy-constrained lifetime optimization to power-constrained workload optimization.This paper presents a self-adapting maximum flow (SAMF) routing strategy which is able to route any sustainable workload while automatically adapting to time-varying operating conditions. The theoretical properties of SAMF routing are formally proved and a simulation model is developed on top of OMNeT++ (http://www.omnetpp.org/) in order to enable simulation-based assessment and design exploration. Simulation results are reported which demonstrate the applicability of the proposed approach.

Towards a true energetically sustainable WSN: A case study with prediction-based data collection and a wake-up receiver

One of the most challenging goals of many wireless sensor network (WSN) deployments is the reduction of energy consumption to extend system lifetime. This paper considers a novel combination of techniques that address energy savings at the hardware and application levels: wake-up receivers and node-level power management, plus prediction-based data collection. Individually, each technique can achieve significant energy savings, but in combination, the results are impressive. This paper presents a case study of these techniques as applied in a road tunnel for light monitoring. Preliminary results show the potential for two orders of magnitude reduction in power consumption. This savings of 380 times allows the creation of an energetically sustainable system by considering integration with a simple, photovoltaic energy harvester.

A Sub-A Ultrasonic Wake-Up Trigger with Addressing Capability for Wireless Sensor Nodes

Wireless sensor nodes spend most of the time waiting either for sensed data or for packets to be routed to the sink. While on board, sensors can raise hardware interrupts to trigger the wake-up of the processor, incoming packets require the radio module to be turned on in order to be properly received and processed; thus, reducing the effectiveness of dynamic power management and exposing the node to unintended packets cause energy waste. The capability of triggering the wake-up of a node over the air would makes it possible to keep the entire network asleep and to wake up the nodes along a path to the sink whenever there is a packet to transmit. This paper presents an ultrasonic wake-up trigger for ultra-low-power wireless sensor nodes developed as a plug-in module for VirtualSense motes. The module supports a simple out-of-band addressing scheme to enable the selective wake-up of a target node. In addition, it makes it possible to exploit the propagation speed of ultrasonic signals to perform distance measurements. The paper outlines the design choices, reports the results of extensive measurements, and discusses the additional degrees of freedom introduced by ultrasonic triggering in the power-state diagram of VirtualSense.

Improving Java performance using dynamic method migration on FPGAs

With the diffusion of Java in advanced multimedia mobile devices, there is a growing need for speeding up the execution of Java bytecode beyond the limits of traditional interpreters and just-in-time compilers. In this area, Java coprocessors are viewed as a promising technology, which marries the flexibility of a general-purpose microprocessor to run legacy code and lightweight Java methods, with the high performance of a specialised execution engine on speed-critical bytecode. This work proposes and analyses a microprocessor with FPGA coprocessor architecture with efficient shared-memory communication support. Furthermore, we describe a complete run-time environment that supports dynamic migration of Java methods to the coprocessor, and we quantitatively analyse speedups achievable under a number of system configurations using an accurate complete-system simulator.