Comparison of Hardware and Software Based Encryption for Secure Communication in Wireless Sensor Networks

International audienceThis paper deals with the energy efficient issue of cryptographic mechanisms used for secure communication between devices in wireless sensor networks. Since these devices are mainly targeted for low power consumption appliances, there is an effort for optimization of any aspects needed for regular sensor operation. On a basis of utilization of hardware cryptographic accelerators integrated in microcontrollers, this article provides the comparison between software and hardware solutions. Proposed work examines the problems and solutions for implementation of security algorithms for WSN devices. Because the speed of hardware accelerator should be much higher than the software implementation, there are examination tests of energy consumption and validation of performance of this feature. Main contribution of the article is real testbed evaluation of the time latency and energy requirements needed for securing the communication. In addition, global evaluation for all important network communication parameters like throughput, delay and delivery ratio are also provided

Robust Wireless Sensor Network Deployment

International audienceIn this work we present a decentralized deployment algorithm for wireless mobile sensor networks focused on deployment Efficiency, connectivity Maintenance and network Reparation (EMR). We assume that a group of mobile sensors is placed in the area of interest to be covered, without any prior knowledge of the environment. The goal of the algorithm is to maximize the covered area and cope with sudden sensor failures. By relying on the locally available information regarding the environment and neighborhood, and without the need for any kind of synchronization in the network, each sensor iteratively chooses the next-step movement location so as to form a hexagonal lattice grid. Relying on the graph of wireless mobile sensors, we are able to provide the properties regarding the quality of coverage, the connectivity of the graph and the termination of the algorithm. We run extensive simulations to provide compactness properties of the deployment and evaluate the robustness against sensor failures. We show through the analysis and the simulations that EMR algorithm is robust to node failures and can restore the lattice grid. We also show that even after a failure, EMR algorithm call still provide a compact deployment in a reasonable time

Applications of Industrial Wireless Sensor Networks

International audienceThe collaborative nature of industrial wireless sensor networks (IWSNs) brings several advantages over traditional wired industrial monitoring and control systems, including self-organization, rapid deployment, flexibility, and inherent intelligent processing. In this regard, IWSNs play a vital role in creating more reliable, efficient, and productive industrial systems, thus improving companies' competitiveness in the marketplace. Industrial Wireless Sensor Networks: Applications, Protocols, and Standards examines the current state of the art in industrial wireless sensor networks and outlines future directions for research

Recombinational landscape of porcine X chromosome and individual variation in female meiotic recombination associated with haplotypes of Chinese pigs

<p>Abstract</p> <p>Background</p> <p>Variations in recombination fraction (θ) among chromosomal regions, individuals and families have been observed and have an important impact on quantitative trait loci (QTL) mapping studies. Such variations on porcine chromosome X (SSC-X) and on other mammalian chromosome X are rarely explored. The emerging assembly of pig sequence provides exact physical location of many markers, facilitating the study of a fine-scale recombination landscape of the pig genome by comparing a clone-based physical map to a genetic map. Using large offspring of F₁females from two large-scale resource populations (Large White ♂ × Chinese Meishan ♀, and White Duroc ♂ × Chinese Erhualian ♀), we were able to evaluate the heterogeneity in θ for a specific interval among individual F₁females.</p> <p>Results</p> <p>Alignments between the cytogenetic map, radiation hybrid (RH) map, genetic maps and clone map of SSC-X with the physical map of human chromosome X (HSA-X) are presented. The most likely order of 60 markers on SSC-X is inferred. The average recombination rate across SSC-X is of ~1.27 cM/Mb. However, almost no recombination occurred in a large region of ~31 Mb extending from the centromere to Xq21, whereas in the surrounding regions and in the Xq telomeric region a recombination rate of 2.8-3.3 cM/Mb was observed, more than twice the chromosome-wide average rate. Significant differences in θ among F₁females within each population were observed for several chromosomal intervals. The largest variation was observed in both populations in the interval <it>UMNP71-SW1943</it>, or more precisely in the subinterval <it>UMNP891-UMNP93</it>. The individual variation in θ over this subinterval was found associated with F₁females' maternal haplotypes (Chinese pig haplotypes) and independent of paternal haplotype (European pig haplotypes). The θ between <it>UMNP891 </it>and <it>UMNP93 </it>for haplotype 1122 and 4311 differed by more than fourteen-fold (10.3% vs. 0.7%).</p> <p>Conclusions</p> <p>This study reveals marked regional, individual and haplotype-specific differences in recombination rate on SSC-X. Lack of recombination in such a large region makes it impossible to narrow QTL interval using traditional fine-mapping approaches. The relationship between recombination variation and haplotype polymorphism is shown for the first time in pigs.</p

Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs

Background: Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations.[br/] Results: Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait.[br/] Conclusions: Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major-effect mutations on the least affected traits, but is one order of magnitude lower than effect on variance of traits primarily affected by these causative mutations. This suggests that uncovering physiological traits directly affected by genetic polymorphisms would be an appropriate approach for further characterization of QTLs

Phenotypic prediction based on metabolomic data : lasso vs Bolasso, primary data vs wavelet transformation

International audienceUnderstanding the relations between various 'omics data (such as metabolomics or genomics data) and phenotypes of interest is one of the current major challenges in biology. This question can be addressed by trying to learn a way to predict the phenotype value from the omic from joint observations of the omic and of the phenotype. In this paper, we focus on the prediction of a phenotype related to the quality of the meat from metabolomic data. As metabolomic data are high dimensional data and as, conjointly, the number of observations is often restricted, model selection methods are a way both to obtain a relevant solution to the prediction problem but also to select the most important metabolomes related to the phenotype under study. During the past years, model selection has know a growing interest in the statistical community: the first - and also probably the most known - selection method has been introducted by \citep{Tibshirani:1996} under the name of LASSO. Several variants of this original approach has then been proposed such as, recently, a bootstraped LASSO, named BOLASSO, introduced in (Bach, 2009). The proposal of this paper is to combine a wavelet representation of the metabolome spectra (see (Mallat, 1999) and (Antonini, 1992) for a complete introduction to wavelets) with the BOLASSO approach. We compare this methodology to more classical methods using either the original spectra as predictors (instead of the wavelet representation) or the original LASSO to select the model. The following section deals with the methodological description of the approach whereas the next one details the experiments and results

Progeny-testing of full-sibs IBD in a SSC2 QTL region highlights epistatic interactions for fatness traits in pigs

<p>Abstract</p> <p>Background</p> <p>Many QTL have been detected in pigs, but very few of them have been fine-mapped up to the causal mutation. On SSC2, the <it>IGF2</it>-intron3-G3072A mutation has been described as the causative polymorphism for a QTL underlying muscle mass and backfat deposition, but further studies have demonstrated that at least one additional QTL should segregate downstream of this mutation. A marker-assisted backcrossing design was set up in order to confirm the segregation of this second locus, reduce its confidence interval and better understand its mode of segregation.</p> <p>Results</p> <p>Five recombinant full-sibs, with genotype G/G at the <it>IGF2 </it>mutation, were progeny-tested. Only two of them displayed significant QTL for fatness traits although four inherited the same paternal and maternal chromosomes, thus exhibiting the same haplotypic contrast in the QTL region. The hypothesis of an interaction with another region in the genome was proposed to explain these discrepancies and after a genome scan, four different regions were retained as potential interacting regions with the SSC2 QTL. A candidate interacting region on SSC13 was confirmed by the analysis of an F2 pedigree, and in the backcross pedigree one haplotype in this region was found to mask the SSC2 QTL effect.</p> <p>Conclusions</p> <p>Assuming the hypothesis of interactions with other chromosomal regions, the QTL could be unambiguously mapped to a 30 cM region delimited by recombination points. The marker-assisted backcrossing design was successfully used to confirm the segregation of a QTL on SSC2 and, because full-sibs that inherited the same alleles from their two parents were analysed, the detection of epistatic interactions could be performed between alleles and not between breeds as usually done with the traditional Line-Cross model. Additional analyses of other recombinant sires should provide more information to further improve the fine-mapping of this locus, and confirm or deny the interaction identified between chromosomes 2 and 13.</p

Detection of quantitative trait loci for carcass composition traits in pigs

A quantitative trait locus (QTL) analysis of carcass composition data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. A total of 488 F2 males issued from six F1 boars and 23 F1 sows, the progeny of six LW boars and six MS sows, were slaughtered at approximately 80 kg live weight and were submitted to a standardised cutting of the carcass. Fifteen traits, i.e. dressing percentage, loin, ham, shoulder, belly, backfat, leaf fat, feet and head weights, two backfat thickness and one muscle depth measurements, ham + loin and back + leaf fat percentages and estimated carcass lean content were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half/full sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Additional analyses were performed to search for multiple linked QTL and imprinting effects. Significant gene effects were evidenced for both leanness and fatness traits in the telomeric regions of SSC 1q and SSC 2p, on SSC 4, SSC 7 and SSC X. Additional significant QTL were identified for ham weight on SSC 5, for head weight on SSC 1 and SSC 7, for feet weight on SSC 7 and for dressing percentage on SSC X. LW alleles were associated with a higher lean content and a lower fat content of the carcass, except for the fatness trait on SSC 7. Suggestive evidence of linked QTL on SSC 7 and of imprinting effects on SSC 6, SSC 7, SSC 9 and SSC 17 were also obtained

Recharging <i>vs</i>. Replacing Sensor Nodes Using Mobile Robots for Network Maintenance

International audienceWireless sensor networks (WSNs) have been of very high interest for the research community since years, but the quest for deploying a self-sustained network and effectively prolonging its lifetime has not found a satisfactory answer yet. Two main approaches can be identified that target this objective: either "recharging'' or "replacing'' the sensor nodes that are running out of energy. Of particular interest are solutions where mobile robots are used to execute the above mentioned tasks to automatically and autonomously maintain the WSN, thus reducing human intervention.Recently, the progress in wireless power transfer techniques has boosted research activities in the direction of battery recharging, with high expectations for its application to WSNs. Similarly, also sensor replacement techniques have been widely studied as a means to provide service continuity in the network. Objective of this paper is to investigate the limitations and the advantages of these two research directions. Key decision points must be identified for effectively supporting WSN self-maintenance: (i) which sensor nodes have to be recharged/replaced; (ii) in which order the mobile robot is serving (i.e., recharging/replacing) the nodes and by following which path; (iii) how much energy is delivered to a sensor when recharged. The influence that a set of parameters, relative to both the sensors and the mobile robot, on the decisions will be considered. Centralized and distributed solutions are compared in terms of effectiveness in prolonging the network lifetime and in allowing network self-sustainability. The performance evaluation in a variety of scenarios and network settings offers the opportunity to draw conclusions and to discuss the boundaries for one technique being preferable to the other