Showing papers by "Roberto Nardone published in 2013"

Estimation of the Energy Consumption of Mobile Sensors in WSN Environmental Monitoring Applications

Abstract: The increasing necessity to have wireless sensor nodes capable to be active for a long time without battery recharge asks for technologies and methods that can anticipate the level of energy drain in these devices In this paper a modelling approach based on Fluid Stochastic Petri Nets is proposed The main contribution of the paper is the definition of a model to estimate single node performance in presence of several energy consuming entities The definition of this single node model is relevant in order to properly support the design of more complex network topologies The paper also reports first experimental results on model analysis mainly conducted by simulation

Petri net based evaluation of energy consumption in wireless sensor nodes

Abstract: Wireless Sensor Networks have proven their capability to deal with problems where wide and hardly accessible areas need to be monitored. Among the other systems there are also sensor networks in which nodes can voluntarily modify their positions to better adapt to changes of monitored phenomenon. One of the major issues arising in these situations is the energy consumption: as all the movements affect the batteries lifetime, the life of a sensor can be extended by equipping the device with power generators that exploit renewable sources, albeit this solution does not always avoid a full battery discharge. In this paper a Fluid Stochastic Petri Net modelling framework is presented to provide a wide evaluation of all the factors that contribute to the energy dissipation in mobile wireless sensor nodes. The framework allows the generation of extensible and composable models capable to evaluate the energy consumption due to sensing, communication and movement functions as well as the impact of power saving mechanisms on the energetical balance of the node. The approach is applied to a marine sensing problem and is validated by comparing the model analysis results with experimental results achieved through an existing off-the-shelf sensor network simulator.

A Compositional Modelling Approach for Large Sensor Networks Design

Abstract: Sensor Networks are required to be properly designed in order to avoid resource waste and optimize their lifetime. Large monitoring applications require proper methodologies and tools supporting the design, when multiple solutions increase the complexity of this task. Indeed, different parameters affect the performance of a solution, as node distribution, sensing coverage, battery usage, etc. A compositional modelling approach can provide early measures, allowing to evaluate and compare different solutions since the design phase. The main contribution of the paper is the definition of a general modelling framework to integrate simple models representing the main components and features of sensor networks. A library for specific sensor devices have been developed, using the Stochastic Activity Network (SAN) formalism. This approach is shown to be compositional since the creation of complex networks can be accomplished by simple subcomponents aggregation. With this approach, obtained models can analyse the dynamic evolution of the overall network, even if complex. First experimental results are also reported and discussed.

An integrated lifetime and network quality model of large WSNs

Abstract: This paper introduces a modeling approach to the design and evaluation of large wireless sensor networks against the topology of the network and the monitoring application and taking into account the performance degradation due to the power consumption The model is built by composing Stochastic Activity Network (SAN) models of the nodes and a Markovian Agent Model (MAM) of the whole network The SAN models are used to conduct a performance analysis of the nodes (ie to measure their sampling time) and evaluate their mean time to discharge The MAM is used to compose the results of the SAN model analysis into a complex topology-aware model able to evaluate the Packet Delivery Ratio (PDR) and the power consumption of the network The possibility to model spatially distributed interdependencies featured by the MAM makes the integrated model a concrete, scalable mean to evaluate different design choices and perform meaningful what-if analyses The model has been validated by comparing the analysis results with real node values: specifically we present the experimental results obtained by using TelosB nodes equipped with TinyOs

A model-driven methodology to evaluate performability of metro systems

Abstract: Metro systems are required to continuously achieve acceptable levels of reliability, availability, maintainability, and performance (performability) in order to comply with the target values reported in operation and maintenance contracts. These requirements are regulated by several international standards that control the lifecycle defining both processes, documentation flows, and enabling techniques, aiming at controlling disturbances on service performed by the system. This chapter focuses on a complete modeldriven methodology with the aim to support the performability evaluation of a metro system during design and in-service phases, as well as requirements assessment. In detail, the methodology allows the automatic generation of those formal models required for performability analysis, specialized according to the specific track layout and the defined operational strategies. The proposed methodology is perfectly coherent with the European Standard CENELEC EN 50126 and it allows the generation of all the technical reports needed in the related documentation.