Andrea Vitaletti

Cell-ID location technique, limits and benefits: an experimental study

The mobile phone market lacks a satisfactory location technique that is accurate, but also economical and easy to deploy. Current technology provides high accuracy, but requires substantial technological and financial investment. In this paper, we present the results of experiments intended to asses the accuracy of inexpensive Cell-ID location technique and its suitability for the provisioning of location based services. We first evaluate the accuracy of Cell-ID in urban, suburban and highway scenarios (both in U.S. and Italy), we then introduce the concepts of discovery-accuracy and discovery-noise to estimate the impact of positioning accuracy on the quality of resource discovery services. Experiments show that the accuracy of Cell-ID is not satisfactory as a general solution. In contrast we show how Cell-ID can be effectively exploited to implement more effective and efficient voice location-based services.

Smart City: An Event Driven Architecture for Monitoring Public Spaces with Heterogeneous Sensors

In this paper, we present the Smart City Architecture developed in the context of the ARTEMIS JU SP3 SOFIA project. It is an Event Driven Architecture that allows the management and cooperation of heterogeneous sensors for monitoring public spaces. The main components of the architecture are implemented in a testbed on a subway scenario with the objective to demonstrate that our proposed solution, can enhance the detection of anomalous events and simplify both the operators tasks and the communications to passengers in case of emergency.

First experiences using wireless sensor networks for noise pollution monitoring

The assessment of environmental pollution levels is a complex and expensive task that public administration and often also private entities are willing or forced to take over. Focusing on the assessment of environmental noise pollution in urban areas, we provide qualitative considerations and experimental results to show the feasibility of wireless sensor networks to be used in this context. We present a prototype for the collection and logging of noise pollution data based on the Tmote invent prototyping platform, using which we performed indoor and outdoor noise pollution measurements. We build upon these first experimental results to depict the potentials and limits of currently available wireless sensor networks prototyping platforms to be used as noise pollution sensors. Furthermore, we present tinyLAB, a Matlab-based tool developed in the context of this work, which enables real-time acquisition, processing and visualization of data collected in wireless sensor networks.

Passive inspection of sensor networks

Deployment of sensor networks in real-world settings is a labor-intensive and cumbersome task: environmental influences often trigger problems that are difficult to track down due to limited visibility of the network state. In this paper we present a framework for passive inspection (i.e., no instrumentation of sensor nodes required) of deployed sensor networks and show how this framework can be used to inspect data gathering applications. The basic approach is to temporarily install a distributed network sniffer alongside the inspected sensor network, with overheard messages being analyzed by a data stream processor and network state being displayed in a graphical user interface. Our tool can be flexibly applied to different sensor network operating systems and protocol stacks, and can deal well with incomplete information.

Latency-constrained aggregation in sensor networks

A sensor network consists of sensing devices which may exchange data through wireless communication; sensor networks are highly energy constrained since they are usually battery operated. Data aggregation is a possible way to save energy consumption: nodes may delay data in order to aggregate them into a single packet before forwarding them towards some central node (sink). However, many applications impose constraints on the maximum delay of data; this translates into latency constraints for data arriving at the sink. We study the problem of data aggregation to minimize maximum energy consumption under latency constraints on sensed data delivery, and we assume unique communication paths that form an intree rooted at the sink. We prove that the offline problem is strongly NP-hard and we design a 2-approximation algorithm. The latter uses a novel rounding technique. Almost all real-life sensor networks are managed online by simple distributed algorithms in the nodes. In this context we consider both the case in which sensor nodes are synchronized or not. We assess the performance of the algorithm by competitive analysis. We also provide lower bounds for the models we consider, in some cases showing optimality of the algorithms we propose. Most of our results also hold when minimizing the total energy consumption of all nodes.

On the accuracy of omnet++ in the wireless sensornetworks domain: simulation vs. testbed

In this paper we present a first effort in assessing the reliability of OMNeT++ and the MAC Simulator framework insimulating Wireless Sensor Networks. A collection of metricson the flooding algorithm running on a simple testbed made of few Tmote Sky is used as reference to evaluate the qualityof the simulation results. Our experiments show that simulation results tend to over-estimate the metrics collected inthe testbed. A correcting factor derived from experimental evidences must be considered in order to improve the simulation results. At the best of our knowledge, this is thefirst result about the accuracy of OMNet++ in the wireless sensor network domain.

Routing protocols for delay tolerant networks: a quantitative evaluation

In this paper we propose a new taxonomy for Delay Tolerant Networks (DTNs) routing protocols and a thorough quantitative evaluation of many protocols proposed in the literature. We categorize DTN protocols, according to their use of three main techniques: queue management, forwarding and replication. Queue management orders and manages the messages in the nodes buffer, forwarding selects the messages to be delivered when there is a contact and finally replication bounds the number of replicas in the network. Contrary to most previous papers, where either only qualitative comparisons have been presented or only a single category of protocols have been analysed, in our work we discuss the results of our experimental activity on many of the DTN protocols in the literature. Our results show that, an effective combination of the proposed techniques, can significantly improve the performance of the protocols in terms of delivery ratio, overhead and delay.

Data Collection in Wireless Sensor Networks for Noise Pollution Monitoring

Focusing on the assessment of environmental noise pollution in urban areas, we provide qualitative considerations and experimental results to show the feasibility of wireless sensor networks to be used in this context. To select the most suitable data collection protocol for the specific noise monitoring application scenario, we evaluated the energy consumption performances of the CTP (Collection Tree Protocol) and DMAC protocols. Our results show that CTP, if used enabling the LPL (Low Power Listening) option, provides the better performances trade-off for noise monitoring applications.

Rijndael for Sensor Networks: Is Speed the Main Issue?

We present an implementation of Rijndael for wireless sensor networks running on Eyes sensor nodes. In previous works, Rijndael has not been considered a suitable encryption algorithm for sensor nodes because it is too slow and requires a large space in memory, a precious resource in this environment. Our implementation of Rijndael is smaller, from about 1/3 to 1/5 of the size of previous implementations. Furthermore, we observe that nowadays MAC and routing protocols for wireless sensor networks, exhibit latencies up to few seconds, and thus the few milliseconds required by Rijndael to encrypt a TinyOS message are negligible if compared to these latencies. For this reason, in our opinion the main focus on the implementation of encryption algorithms for wireless sensor networks should move from speed, to memory occupation and energy efficiency.

Approximation Algorithms for Bandwidth and Storage Allocation Problems under Real Time Constraints

The problem we consider is motivated by allocating bandwidth slots to communication requests on a satellite channel under real time constraints. Accepted requests must be scheduled on nonintersecting rectangles in the time/bandwidth Cartesian space with the goal of maximizing the benefit obtained from accepted requests. This problem turns out to be equal to the maximization version of the well known Dynamic Storage Allocation problem when storage size is limited and requests must be accommodated within a prescribed time interval. We present constant approximation algorithms for the problem introduced in this paper using as a basic step the solution of a fractional Linear Programming formulation. This problem has been independently studied by Bar-Noy et al [BNBYF+00] with different techniques. Our approach gives an improved approximation ratio for the problem.