Roberto Pagliari

Scalable Network Synchronization with Pulse-Coupled Oscillators

The Pulse-Coupled Oscillator (PCO) is a novel protocol inspired by models used in mathematical biology to justify the emergence of synchrony in the natural world. Our paper introduces and demonstrates the efficacy of a new PCO protocol implementation that, by disabling all collision resolution mechanisms for a suitable portion of the node operations, lets the rapid establishment of a common clock and its maintenance. The key idea is to allow signals to be superimposed in time, a feature that is absent in previous implementations, because it is prevented by traditional medium access schemes. We map the PCO protocol into an event-driven asynchronous coloring algorithm, based on the local exchange of information to explain its convergence properties. The event-based description of the PCO protocol sets the stage for our experimental comparison with a competing decentralized network synchronization approach, namely, the Reference Broadcast Protocol (RBS). For comparison, we combined RBS with an asynchronous average consensus protocol, running exactly on the same MicaZ platforms. The experimental results showcase the better scalability of the PCO scheme compared to the competing method based on RBS, proving that the PCO primitive is a reasonable option to consider for wireless sensor network applications.

Decentralized binary detection with noisy communication links

This correspondence presents a Bayesian framework for distributed detection in sensor networks with noisy communication links between the sensors and the fusion center (or access point (AP)). Noisy links are modeled as binary symmetric channels (BSCs), but the proposed framework can be extended to other communication link models. To improve the system robustness against observation and communication noises, we propose schemes with 1) multiple observations and a single AP and 2) single observations and multiple APs. By using the De Moivre-Laplace approximation, we derive simple and accurate expressions for the probability of decision error in scenarios with a large number of nodes

The decentralized estimation of the sample covariance

In this paper we consider the problem of estimating the eigenvectors of the sample covariance matrix of decentralized measurements in a distributed fashion. The need for a distributed scheme is motivated by the many moment based methods that resort to the covariance of the data to extract information from the measurements. For large sensor network, gathering the data at a central processor generates a communication bottleneck. Our algorithm is based on a combination of the so called power method, that is used to compute the eigenvectors, and the average consensus protocol, that is utilized to structure the information exchange into a gossiping protocol. Our work shows how a completely distributed scheme based on near neighbors communications is feasible, and applies the proposed method to the estimation of the direction of arrival of a signal source.

Decentralized Detection in Clustered Sensor Networks

We investigate decentralized detection in clustered sensor networks with hierarchical multi-level fusion. We focus on simple majority-like fusion strategies, leading to closed-form analytical performance evaluation. The sensor nodes observe a binary phenomenon and transmit their own data to an access point (AP), possibly through intermediate fusion centers (FCs). We investigate the impact of uniform and nonuniform clustering on the system performance, evaluated in terms of probability of decision error on the phenomenon status at the AP. Our results show that, under a majority-like fusion rule, uniform clustering leads to the minimum performance degradation, which depends only on the number of decision levels rather than on the specific clustered topology. We then extend our approach, taking into account the impact of spatial variations of the phenomenon, noisy communication links, and weighed fusion rules. Finally the proposed distributed detection schemes are characterized with simulation and experimental results (relative to IEEE 802.15.4-based networks), which confirm the analytical predictions.

Decentralized Detection In Sensor Networks With Noisy Communication Links

This paper presents a general approach to distributed detection with multiple sensors in network scenarios with noisy communication links between the sensors and the fusion center (or access point, AP). The sensors are independent and observe a common phenomenon. While in most of the literature the performance metrics usually considered are missed detection and false alarm probabilities, in this paper we follow a Bayesian approach for the evaluation of the probability of decision error at the AP. We first derive an optimized fusion rule at the AP in a scenario with ideal communication links. Then, we consider the presence of noisy links and model them as binary symmetric channels (BSCs). This assumption leads to a simple, yet meaningful, performance analysis. Under this assumption, we show, both analytically and through simulations, that if the noise intensity is above a critical level (i.e., the cross-over probability of the BSC is above a critical value), the lowest probability of decision error at the AP is obtained if the AP selectively discards the information transmitted by the sensors with noisy links.

Decentralised binary detection with non-constant SNR profile at the sensors

In this paper, we consider the problem of decentralised binary detection in sensor networks characterised by non-constant observation Signal-to-Noise Ratios (SNRs) at the sensors. In general, SNRs at the sensors could have a generic non-constant distribution. In order to analyse the performance of these decentralised detection schemes, we introduce the concept of sensor SNR profile, and we consider four possible profiles (linear, quadratic, cubic and hyperbolic) as representative of a large number of realistic scenarios. Furthermore, we show how the impact of communication noise in the links between the sensors and the Access Point (AP) depends on the sensor SNR profile (i.e. the spatial distribution of the observation noise). More precisely, different sensor SNR profiles are compared under two alternative assumptions: (i) common maximum sensor SNR or (ii) common average sensor SNR. Finally, we propose an asymptotic (for a large number of sensors) performance analysis, deriving a simple expression for the limiting probability of decision error. We validate our theoretical analysis with experimental results.

Pulse coupled oscillators' primitive for low complexity scheduling

Pulse coupled oscillators (PCOs) are pulsing devices that pulse individually in a periodic manner but alter their pulsing patterns in response to the pulsing of other nodes. A network of PCOs can produce a number of different dynamics from their pulsing activities, among which the synchrony of pulsing is perhaps the most well known. In this paper, we study the primitive that falls into the class of “desynchronization”. Specifically, we propose a simple pulse-coupling mechanism that allows each node in the network to converge to a desynchronized state where the nodes will pulse periodically with a constant spacing among each others firing times. We discuss the convergence of the PCO mechanism and propose to apply this primitive to resolve contention in the reservation phase of a reservation-based MAC protocol.

Non-cooperative versus Cooperative Approaches for Distributed Network Synchronization

In this paper we compare the so called pulse coupled oscillator (PCO) protocol with an alternative gossiping algorithm, known as average consensus protocol, considering the application of decentralized network synchronization. The main difference between the PCO algorithm and the average consensus protocol is that the latter is based on the explicit exchange of time-stamps in the pay load of packets, which are delivered with contention to the neighbors. The PCO scheme, instead, implicitly encodes the computed state into the transmission time, driving the nodes to transmit packets in synchrony. Our results show clearly how as more nodes tend to transmit at unison, cooperative transmission emerges boosting up the signal level and, therefore, speeding up the algorithm convergence. Conversely, the average consensus protocol, requires increasing energy as the number of nodes increases

Pulse coupled oscillators’ primitives for collision-free multiple access with application to body area networks

This paper investigates strategies to achieve collectively coordination in sensor networks, with extremely limited complexity. We propose and compare novel backoff mechanisms to achieve adaptively the desired scheduling among a number of sensors that contend for their access to the wireless medium. The method considered models the interactions among sensors as that of pulse coupled oscillators (PCO), which have been widely studied in mathematical biology to capture the interaction among biological entities (such as neurons) and the emergence of firing patterns in their networks. Modeling our sensors as UWB pulse emitters, our interest in this paper is to discuss strategies that allow the sensors to interleave their pulsing activities in a sequence so as to provide a frame subdivision for the collision free transmissions. The bio-inspired algorithm featured is a useful network primitive for multiple access in highly scalable sensor networks, which adds on to the well known primitive for network synchronization where PCO models are popular for.

Adaptive wireless networking primitives for distributed scheduling: Can radios swarm?

Motivated by the beauty and the simplicity of biologically inspired algorithm, we study a class of self-organizing protocols based on the Pulse-Coupled Oscillators (PCO). Specifically, we consider two different dynamics of this protocol and show how by flipping the sign of the coupling among the nodes translates into two different emerging pattern: synchrony and de-synchrony. The former is a state where all the nodes pulse at unison. The latter is a situation where the nodes alternate their firings, so that the time between two consecutive firings is constant.