Stochastic characterization of the spectrum sharing game in ad-hoc networks

Abstract This work focuses on infrastructure-less ad hoc wireless networks where multiple transmitter/receiver pairs share the same radio resources (spectrum); transmitters have to choose how to split a total power budget across orthogonal spectrum bands with the goal to maximize their sum rate under cumulative interference from concurrent transmissions. We start off by introducing and characterizing the non-cooperative game among transmitter/receiver pairs when the network topology is deterministically given. The corresponding Nash equilibria are derived, highlighting their dependency on the topological parameters (distances between wireless nodes, propagation model, and background noise power). The analysis is then extended to the case of random network topologies drawn from a given spatial stochastic process. Tools of stochastic geometry are leveraged to derive a statistical characterization of the equilibria of the spectrum sharing game. Finally, a distributed algorithm is proposed to let the players of the spectrum sharing game converge to equilibria conditions. Numerical simulations show that the proposed algorithm drives the users to stable points that are close to the equilibria of the game requiring limited information exchange among nodes

An Implementation for Dynamic Application Allocation in Shared Sensor Networks

We present a system architecture implementation to perform dynamic application allocation in shared sensor networks, where highly integrated wireless sensor systems are used to support multiple applications. The architecture is based on a central controller that collects the received data from the sensor nodes, dynamically decides which applications must be simultaneously deployed in each node and, accordingly, over-the-air reprograms the sensor nodes. Waspmote devices are used as sensor nodes that communicate with the controller using ZigBee protocol. Experimental results show the viability of the proposal

A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques

A growing trend for information technology is to not just react to changes, but anticipate them as much as possible. This paradigm made modern solutions, such as recommendation systems, a ubiquitous presence in today's digital transactions. Anticipatory networking extends the idea to communication technologies by studying patterns and periodicity in human behavior and network dynamics to optimize network performance. This survey collects and analyzes recent papers leveraging context information to forecast the evolution of network conditions and, in turn, to improve network performance. In particular, we identify the main prediction and optimization tools adopted in this body of work and link them with objectives and constraints of the typical applications and scenarios. Finally, we consider open challenges and research directions to make anticipatory networking part of next generation networks

Computational reconstruction of pacemaking and intrinsic electroresponsiveness in cerebellar Golgi cells.

The Golgi cells have been recently shown to beat regularly in vitro (Forti et al., 2006. J. Physiol. 574, 711-729). Four main currents were shown to be involved, namely a persistent sodium current (I(Na-p)), an h current (I(h)), an SK-type calcium-dependent potassium current (I(K-AHP)), and a slow M-like potassium current (I(K-slow)). These ionic currents could take part, together with others, also to different aspects of neuronal excitability like responses to depolarizing and hyperpolarizing current injection. However, the ionic mechanisms and their interactions remained largely hypothetical. In this work, we have investigated the mechanisms of Golgi cell excitability by developing a computational model. The model predicts that pacemaking is sustained by subthreshold oscillations tightly coupled to spikes. I(Na-p) and I(K-slow) emerged as the critical determinants of oscillations. I(h) also played a role by setting the oscillatory mechanism into the appropriate membrane potential range. I(K-AHP), though taking part to the oscillation, appeared primarily involved in regulating the ISI following spikes. The combination with other currents, in particular a resurgent sodium current (I(Na-r)) and an A-current (I(K-A)), allowed a precise regulation of response frequency and delay. These results provide a coherent reconstruction of the ionic mechanisms determining Golgi cell intrinsic electroresponsiveness and suggests important implications for cerebellar signal processing, which will be fully developed in a companion paper (Solinas et al., 2008. Front. Neurosci. 2:4)

The association between air pollution and the incidence of idiopathic pulmonary fibrosis in Northern Italy

Acute exacerbations and worsening of idiopathic pulmonary fibrosis (IPF) have been associated with exposure to ozone (O3), nitrogen dioxide (NO2) and particulate matter, but chronic exposure to air pollution might also affect the incidence of IPF. We investigated the association between chronic exposure to NO2, O3 and particulate matter with an aerodynamic diameter <10 \u3bcm (PM10) and IPF incidence in Northern Italy between 2005 and 2010. Daily predictions of PM10 concentrations were obtained from spatiotemporal models, and NO2 and O3 hourly concentrations from fixed monitoring stations. We identified areas with homogenous exposure to each pollutant. We built negative binomial models to assess the association between area-specific IPF incidence rate, estimated through administrative databases, and average overall and seasonal PM10, NO2, and 8-hour maximum O3 concentrations. Using unadjusted models, an increment of 10 \u3bcg\ub7m-3 in NO2 concentration was associated with an increase between 7.93% (95% CI 0.36-16.08%) and 8.41% (95% CI -0.23-17.80%) in IPF incidence rate, depending on the season. After adjustment for potential confounders, estimated effects were similar in magnitude, but with larger confidence intervals. Although confirmatory studies are needed, our results trace a potential association between exposure to traffic pollution and the development of IPF

Energy-aware dynamic resource allocation in virtual sensor networks

Sensor network virtualization enables the possibility of sharing common physical resources to multiple stakeholder applications. This paper focuses on addressing the dynamic adaptation of already assigned virtual sensor network resources to respond to time varying application demands. We propose an optimization framework that dynamically allocate applications into sensor nodes while accounting for the characteristics and limitations of the wireless sensor environment. It takes also into account the additional energy consumption related to activating new nodes and/or moving already active applications. Different objective functions related to the available energy in the nodes are analyzed. The proposed framework is evaluated by simulation considering realistic parameters from actual sensor nodes and deployed applications to assess the efficiency of the proposals