Enabling Disaster Resilient 4G Mobile Communication Networks

The 4G Long Term Evolution (LTE) is the cellular technology expected to outperform the previous generations and to some extent revolutionize the experience of the users by taking advantage of the most advanced radio access techniques (i.e. OFDMA, SC-FDMA, MIMO). However, the strong dependencies between user equipments (UEs), base stations (eNBs) and the Evolved Packet Core (EPC) limit the flexibility, manageability and resiliency in such networks. In case the communication links between UEs-eNB or eNB-EPC are disrupted, UEs are in fact unable to communicate. In this article, we reshape the 4G mobile network to move towards more virtual and distributed architectures for improving disaster resilience, drastically reducing the dependency between UEs, eNBs and EPC. The contribution of this work is twofold. We firstly present the Flexible Management Entity (FME), a distributed entity which leverages on virtualized EPC functionalities in 4G cellular systems. Second, we introduce a simple and novel device-todevice (D2D) communication scheme allowing the UEs in physical proximity to communicate directly without resorting to the coordination with an eNB.Comment: Submitted to IEEE Communications Magazin

ontext-aware security and secure context-awareness in ubiquitous computing environments

Context-awareness emerges as an important element of future wireless systems. In particular, concepts like ambient intelligence and ubiquitous computing rely on context information in order to personalize services provided to their target users. However, security implications of employing context-awareness in computing systems are not well understood. Security challenges in context-aware systems include integrity, confidentiality and availability of context information, as well as target user's privacy. Another interesting and open question is to what extent availability of additional context information could be used in order to optimise and reconfigure security-related services

STIM map: detection map for exoplanets imaging beyond asymptotic Gaussian residual speckle noise

Direct imaging of exoplanets is a challenging task as it requires to reach a high contrast at very close separation to the star. Today, the main limitation in the high-contrast images is the quasi-static speckles that are created by residual instrumental aberrations. They have the same angular size as planetary companions and are often brighter, hence hindering our capability to detect exoplanets. Dedicated observation strategies and signal processing techniques are necessary to disentangle these speckles from planetary signals. The output of these methods is a detection map in which the value of each pixel is related to a probability of presence of a planetary signal. The detection map found in the literature relies on the assumption that the residual noise is Gaussian. However, this is known to lead to higher false positive rates, especially close to the star. In this paper, we re-visit the notion of detection map by analyzing the speckle noise distribution, namely the Modified Rician distribution. We use non-asymptotic analysis of the sum of random variables to show that the tail of the distribution of the residual noise decays as an exponential distribution, hence explaining the high false detection rate obtained with the Gaussian assumption. From this analysis, we introduce a novel time domain detection map and we demonstrate its capabilities and the relevance of our approach through experiments on real data. We also provide an empirical rule to determine detection threshold providing a good trade off between true positive and false positive rates for exoplanet detection

A case study on regularity in cellular network deployment

This paper aims to validate the $\beta$-Ginibre point process as a model for the distribution of base station locations in a cellular network. The $\beta$-Ginibre is a repulsive point process in which repulsion is controlled by the $\beta$ parameter. When $\beta$ tends to zero, the point process converges in law towards a Poisson point process. If $\beta$ equals to one it becomes a Ginibre point process. Simulations on real data collected in Paris (France) show that base station locations can be fitted with a $\beta$-Ginibre point process. Moreover we prove that their superposition tends to a Poisson point process as it can be seen from real data. Qualitative interpretations on deployment strategies are derived from the model fitting of the raw data

Behavioural response of green peach aphid Myzus persicae (Sulzer) to volatiles from different rosemary (Rosmarinus officinalis L.) clones

Previous studies have shown that rosemary (Rosmarinus officinalis L.) can serve as a companion plant to control Myzus persicae (Sulzer) because of the repellent effect of certain volatile organic compounds (VOCs) that it emits. In the present study, we investigated which of five clones of rosemary may reveal a repellent effect on M. persicae and aimed to determine the possible VOCs involved.Analyses of the mixtures of VOCs released by the different clones revealed the presence of 15 main components. However, each clone was characterized by a specific volatile profile showing the existence of marked chemical variability.By testing the identified VOCs individually, using a dual‐choice olfactometer, we observed that five volatiles had a significant repulsive effect on M. persicae: bornyl acetate, camphor, α‐terpineol, terpinene‐4‐ol and geranyl acetone. In addition, only one clone of rosemary elicited a significant repulsive action.Nevertheless, all of the tested clones released compounds that are repellent to the aphid when tested individually. Therefore, the emission of individual volatiles by a rosemary plant is not sufficient to elicit a repellent effect.The concentration, proportion and even the association/synergy of VOCs in the released olfactory bouquets can probably explain these contrasting results and are worthy of additional exploration in future studies