Stefano Chessa

GPS free coordinate assignment and routing in wireless sensor networks

In this paper we consider the problem of constructing a coordinate system in a sensor network where location information is not available. To this purpose we introduce the virtual coordinate assignment protocol (VCap) which defines a virtual coordinate system based on hop distances. As compared to other approaches, VCap is simple and have very little requirements in terms of communication and memory overheads. We compare by simulations the performances of greedy routing using our virtual coordinate system with the one using the physical coordinates. Results show that the virtual coordinate system can be used to efficiently support geographic routing.

Crash faults identification in wireless sensor networks

In this paper we consider the problem of identifying faulty (crashed) nodes in a wireless sensor network. This problem is of fundamental importance in those applicative scenarios of wireless sensor networks in which battery replacement is feasible. The diagnostic information gathered by operational sensors can be used by an external operator for the sake of network reconfiguration and/or repair; thus extending network lifetime. A fault diagnosis protocol specifically designed for wireless sensor networks is introduced and analyzed. The protocol is proved to be optimal and energy efficient under certain assumptions.

Comparison-based system-level fault diagnosis in ad hoc networks

The problem of identifying faulty mobiles in ad-hoc networks is considered. Current diagnostic models were designed for wired networks, thus they do not take advantage of the shared nature of communication typical of ad-hoc networks. In this paper we introduce a new comparison-based diagnostic model based on the one-to-many communication paradigm. Two implementations of the model are presented. In the first implementation, we assume that the network topology does not change during diagnosis, and we show that both hard and soft faults can be easily, detected Based on this implementation, a diagnosis protocol is presented The evaluation of the communication and time complexity of the protocol indicates that efficient diagnosis protocols for ad-hoc networks based on our model can be designed In the second implementation we allow the system topology to change during diagnosis. As expected, the ability of diagnosing faults under this scenario is significantly reduced with respect to the stationary case.

A Novel Approach to Indoor RSSI Localization by Automatic Calibration of the Wireless Propagation Model

We propose a novel localization algorithm of mobile sensors based on wireless sensor networks providing RSSI measurements between the mobile and the fixed sensors (anchors) in the network. The algorithm selects and weights the RSSI measurements according to their strength, and it uses a propagation model to transform RSSI measurements into distances, in order to estimate the position of the mobile. The algorithm also uses a virtual calibration method of the propagation model that does not require human intervention. By an experimental setup we show that the localization algorithm increases the performance with respect to the commonly used least mean square algorithm showing also how to achieve a wished accuracy increasing the anchor density.

An experimental characterization of reservoir computing in ambient assisted living applications

In this paper, we present an introduction and critical experimental evaluation of a reservoir computing (RC) approach for ambient assisted living (AAL) applications. Such an empirical analysis jointly addresses the issues of efficiency, by analyzing different system configurations toward the embedding into computationally constrained wireless sensor devices, and of efficacy, by analyzing the predictive performance on real-world applications. First, the approach is assessed on a validation scheme where training, validation and test data are sampled in homogeneous ambient conditions, i.e., from the same set of rooms. Then, it is introduced an external test set involving a new setting, i.e., a novel ambient, which was not available in the first phase of model training and validation. The specific test-bed considered in the paper allows us to investigate the capability of the RC approach to discriminate among user movement trajectories from received signal strength indicator sensor signals. This capability can be exploited in various AAL applications targeted at learning user indoor habits, such as in the proposed indoor movement forecasting task. Such a joint analysis of the efficiency/efficacy trade-off provides novel insight in the concrete successful exploitation of RC for AAL tasks and for their distributed implementation into wireless sensor networks.

Evaluating Ambient Assisted Living Solutions: The Localization Competition

Evaluation of ambient assisted living (AAL) systems is particularly challenging due to the complexity of such systems and the variety of solutions adopted and services offered. Yet analyzing and comparing AAL solutions is paramount for assessing research results in this area. Evaluating AAL Systems through Competitive Benchmarking (EvAAL) is a recently established international competition that aims to address this problem, letting benchmarking and comparison methodologies of AAL systems emerge from experience. Here, the authors describes the first EvAAL competition, which was devoted to localization and tracking. They also review the proposed evaluation criteria, benchmarks, and results. All evaluation data is freely available from the EvAAL website.

Virtual Calibration for RSSI-Based Indoor Localization with IEEE 802.15.4

Localization systems based on Received Signal Strength Indicator (RSSI) exploit fingerprinting (based on extensive signal strength measurements) to calibrate the system parameters. This procedure is very expensive in terms of time as it relies on human operators. In this paper we propose a virtual calibration procedure which only exploits the measurements of the RSSI between pairs of anchors. In particular, we propose two procedures for virtual calibration and we evaluate their performance with respect to an ad-hoc calibration campaign by performing measures in an indoor environment with an IEEE 802.15.4 sensor network.

Sensor data fusion for activity monitoring in the PERSONA ambient assisted living project

User activity monitoring is a major problem in ambient assisted living, since it requires to infer new knowledge from collected and fused sensor data while dealing with highly dynamic environments, where devices continuously change their availability and (or) physical location. In the context of the European project PERSONA, we have developed an activity monitoring sub-system characterized by high modularity, little invasiveness of the environment and good responsiveness. In this paper we first illustrate the functional architecture of the proposed solution from a general point of view, discussing the motivations of the design. Then we describe in details the software components—sensor abstraction and integration layer, human posture classification, activity monitor—and the resulting activity monitoring application, presenting also a performance evaluation.

Dependable and secure data storage and retrieval in mobile, wireless networks

This paper introduces a distributed data storage for mobile, wireless networks based on a peer-to-peer paradigm. The distributed storage provides support to create and share files under a write-once model, and ensures at the same time data confidentiality and dependability by encoding files in a Redundant Residue Number System. More specifically files are partitioned into records and each record in encoded separately as (h+r)-tuples of data residues using h+r moduli. In turn, the residues are distributed among the mobiles in the network. Dependability is ensured since data can be reconstructed in the presence of up to s≤r residue erasures, combined with up to ¨ o 2 s r − corrupted residues, and data confidentiality is ensured since recovering the original information requires knowledge of the entire set of moduli.

Q-NiGHT: Adding QoS to Data Centric Storage in Non-Uniform Sensor Networks

Storage of sensed data in wireless sensor networks is essential when the sink node is unavailable due to failure and/or disconnections, but it can also provide efficient access to sensed data to multiple sink nodes. Recent approaches to data storage rely on Geographic Hash Tables for efficient data storage and retrieval. These approaches however do not support different QoS levels for different classes of data as the programmer has no control on the level of redundancy of data. They result in a great unbalance in the storage usage in each sensor, even when sensors are uniformly distributed. This may cause serious data losses, waste energy and shorten the overall lifetime of the sensornet. In this paper, we propose a novel protocol, Q- NiGHT, which (1) provides a direct control on the level of QoS in the data dependability, and (2) uses a strategy similar to the rejection method to build a hash function which scatters data approximately with the same distribution of sensors. The benefits of Q-NiGHT are assessed through a detailed simulation experiment, also discussed in the paper. Results show its good performance on different sensors distributions on terms of both protocol costs and load balance between sensors.