Distributed sensor failure detection in sensor networks

We investigate the problem of distributed sensors' failure detection in networks with a small number of defective sensors, whose measurements differ significantly from the neighbor measurements. We build on the sparse nature of the binary sensor failure signals to propose a novel distributed detection algorithm based on gossip mechanisms and on Group Testing (GT), where the latter has been used so far in centralized detection problems. The new distributed GT algorithm estimates the set of scattered defective sensors with a low complexity distance decoder from a small number of linearly independent binary messages exchanged by the sensors. We first consider networks with one defective sensor and determine the minimal number of linearly independent messages needed for its detection with high probability. We then extend our study to the multiple defective sensors detection by modifying appropriately the message exchange protocol and the decoding procedure. We show that, for small and medium sized networks, the number of messages required for successful detection is actually smaller than the minimal number computed theoretically. Finally, simulations demonstrate that the proposed method outperforms methods based on random walks in terms of both detection performance and convergence rate.

Approximate decoding approaches for network coded correlated data

This paper considers a framework where data from correlated sources are transmitted with the help of network coding in ad hoc network topologies. The correlated data are encoded independently at sensors and network coding is employed in the intermediate nodes in order to improve the data delivery performance. In such settings, we focus on the problem of reconstructing the sources at decoder when perfect decoding is not possible due to losses or bandwidth variations. We show that the source data similarity can be used at decoder to permit decoding based on a novel and simple approximate decoding scheme. We analyze the influence of the network coding parameters and in particular the size of finite coding fields on the decoding performance. We further determine the optimal field size that maximizes the expected decoding performance as a trade-off between information loss incurred by limiting the resolution of the source data and the error probability in the reconstructed data. Moreover, we show that the performance of the approximate decoding improves when the accuracy of the source model increases even with simple approximate decoding techniques. We provide illustrative examples showing how the proposed algorithm can be deployed in sensor networks and distributed imaging applications.

2013 Doctoral Workshop on Distributed Systems

The Doctoral Workshop on Distributed Systems was held at Les Plans-sur-Bex, Switzerland, from June 26-28, 2013. Ph.D. students from the Universities of Neuchâtel and Bern as well as the University of Applied Sciences of Fribourg presented their current research work and discussed recent research results. This technical report includes the extended abstracts of the talks given during the workshop.

A distributed, semiotic-inductive and human-Oriented approach to web-scale knowledge retrieval

Web-scale knowledge retrieval can be enabled by distributed information retrieval, clustering Web clients to a large-scale computing infrastructure for knowledge discovery from Web documents. Based on this infrastructure, we propose to apply semiotic (i.e., sub-syntactical) and inductive (i.e., probabilistic) methods for inferring concept associations in human knowledge. These associations can be combined to form a fuzzy (i.e.,gradual) semantic net representing a map of the knowledge in the Web. Thus, we propose to provide interactive visualizations of these cognitive concept maps to end users, who can browse and search the Web in a human-oriented, visual, and associative interface.

Interaction between effects of genes coding for dopamine and glutamate transmission on striatal and parahippocampal function

The genes for the dopamine transporter (DAT) and the D-Amino acid oxidase activator (DAOA or G72) have been independently implicated in the risk for schizophrenia and in bipolar disorder and/or their related intermediate phenotypes. DAT and G72 respectively modulate central dopamine and glutamate transmission, the two systems most robustly implicated in these disorders. Contemporary studies have demonstrated that elevated dopamine function is associated with glutamatergic dysfunction in psychotic disorders. Using functional magnetic resonance imaging we examined whether there was an interaction between the effects of genes that influence dopamine and glutamate transmission (DAT and G72) on regional brain activation during verbal fluency, which is known to be abnormal in psychosis, in 80 healthy volunteers. Significant interactions between the effects of G72 and DAT polymorphisms on activation were evident in the striatum, parahippocampal gyrus, and supramarginal/angular gyri bilaterally, the right insula, in the right pre-/postcentral and the left posterior cingulate/retrosplenial gyri (P < 0.05, FDR-corrected across the whole brain). This provides evidence that interactions between the dopamine and the glutamate system, thought to be altered in psychosis, have an impact in executive processing which can be modulated by common genetic variation.

Genetic testing for TMEM154 mutations associated with lentivirus susceptibility in sheep.

In sheep, small ruminant lentiviruses cause an incurable, progressive, lymphoproliferative disease that affects millions of animals worldwide. Known as ovine progressive pneumonia virus (OPPV) in the U.S., and Visna/Maedi virus (VMV) elsewhere, these viruses reduce an animal's health, productivity, and lifespan. Genetic variation in the ovine transmembrane protein 154 gene (TMEM154) has been previously associated with OPPV infection in U.S. sheep. Sheep with the ancestral TMEM154 haplotype encoding glutamate (E) at position 35, and either form of an N70I variant, were highly-susceptible compared to sheep homozygous for the K35 missense mutation. Our current overall aim was to characterize TMEM154 in sheep from around the world to develop an efficient genetic test for reduced susceptibility. The average frequency of TMEM154 E35 among 74 breeds was 0.51 and indicated that highly-susceptible alleles were present in most breeds around the world. Analysis of whole genome sequences from an international panel of 75 sheep revealed more than 1,300 previously unreported polymorphisms in a 62 kb region containing TMEM154 and confirmed that the most susceptible haplotypes were distributed worldwide. Novel missense mutations were discovered in the signal peptide (A13V) and the extracellular domains (E31Q, I74F, and I102T) of TMEM154. A matrix-assisted laser desorption/ionization-time-of flight mass spectrometry (MALDI-TOF MS) assay was developed to detect these and six previously reported missense and two deletion mutations in TMEM154. In blinded trials, the call rate for the eight most common coding polymorphisms was 99.4% for 499 sheep tested and 96.0% of the animals were assigned paired TMEM154 haplotypes (i.e., diplotypes). The widespread distribution of highly-susceptible TMEM154 alleles suggests that genetic testing and selection may improve the health and productivity of infected flocks.

The long non-coding RNA NEAT1 is increased in IUGR placentas, leading to potential new hypotheses of IUGR origin/development.

INTRODUCTION Intrauterine Growth Restriction (IUGR) is a multifactorial disease defined by an inability of the fetus to reach its growth potential. IUGR not only increases the risk of neonatal mortality/morbidity, but also the risk of metabolic syndrome during adulthood. Certain placental proteins have been shown to be implicated in IUGR development, such as proteins from the GH/IGF axis and angiogenesis/apoptosis processes. METHODS Twelve patients with term IUGR pregnancy (birth weight < 10th percentile) and 12 CTRLs were included. mRNA was extracted from the fetal part of the placenta and submitted to a subtraction method (Clontech PCR-Select cDNA Subtraction). RESULTS One candidate gene identified was the long non-coding RNA NEAT1 (nuclear paraspeckle assembly transcript 1). NEAT1 is the core component of a subnuclear structure called paraspeckle. This structure is responsible for the retention of hyperedited mRNAs in the nucleus. Overall, NEAT1 mRNA expression was 4.14 (±1.16)-fold increased in IUGR vs. CTRL placentas (P = 0.009). NEAT1 was exclusively localized in the nuclei of the villous trophoblasts and was expressed in more nuclei and with greater intensity in IUGR placentas than in CTRLs. PSPC1, one of the three main proteins of the paraspeckle, co-localized with NEAT1 in the villous trophoblasts. The expression of NEAT1_2 mRNA, the long isoform of NEAT1, was only modestly increased in IUGR vs. CTRL placentas. DISCUSSION/CONCLUSION The increase in NEAT1 and its co-localization with PSPC1 suggests an increase in paraspeckles in IUGR villous trophoblasts. This could lead to an increased retention of important mRNAs in villous trophoblasts nuclei. Given that the villous trophoblasts are crucial for the barrier function of the placenta, this could in part explain placental dysfunction in idiopathic IUGR fetuses.

The polarized distribution of poly(A+)-mRNA-induced functional ion channels in the Xenopus oocyte plasma membrane is prevented by anticytoskeletal drugs

Foreign mRNA was expressed in Xenopus laevis oocytes. Newly expressed ion currents localized in defined plasma membrane areas were measured using the two-electrode voltage clamp technique in combination with a specially designed chamber, that exposed only part of the surface on the oocytes to channel agonists or inhibitors. Newly expressed currents were found to be unequally distributed in the surface membrane of the oocyte. This asymmetry was most pronounced during the early phase of expression, when channels could almost exclusively be detected in the animal hemisphere of the oocyte. 4 d after injection of the mRNA, or later, channels could be found at a threefold higher density at the animal than at the vegetal pole area. The pattern of distribution was observed to be similar with various ion channels expressed from crude tissue mRNA and from cRNAs coding for rat GABAA receptor channel subunits. Electron microscopical analysis revealed very similar microvilli patterns at both oocyte pole areas. Thus, the asymmetric current distribution is not due to asymmetric surface structure. Upon incubation during the expression period in either colchicine or cytochalasin D, the current density was found to be equal in both pole areas. The inactive control substance beta-lumicolchicine had no effect on the asymmetry of distribution. Colchicine was without effect on the amplitude of the expressed whole cell current. Our measurements reveal a pathway for plasma membrane protein expression endogenous to the Xenopus oocyte, that may contribute to the formation and maintenance of polarity of this highly organized cell.

Decoding Delay Minimization in Inter-Session Network Coding

Intra-session network coding has been shown to offer significant gains in terms of achievable throughput and delay in settings where one source multicasts data to several clients. In this paper, we consider a more general scenario where multiple sources transmit data to sets of clients over a wireline overlay network. We propose a novel framework for efficient rate allocation in networks where intermediate network nodes have the opportunity to combine packets from different sources using randomized network coding. We formulate the problem as the minimization of the average decoding delay in the client population and solve it with a gradient-based stochastic algorithm. Our optimized inter-session network coding solution is evaluated in different network topologies and is compared with basic intra-session network coding solutions. Our results show the benefits of proper coding decisions and effective rate allocation for lowering the decoding delay when the network is used by concurrent multicast sessions.

SLA-Driven Simulation of Multi-Tenant Scalable Cloud-Distributed Enterprise Information Systems

Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators.

Interactive free viewpoint video streaming using prioritized network coding

In free viewpoint applications, the images are captured by an array of cameras that acquire a scene of interest from different perspectives. Any intermediate viewpoint not included in the camera array can be virtually synthesized by the decoder, at a quality that depends on the distance between the virtual view and the camera views available at decoder. Hence, it is beneficial for any user to receive camera views that are close to each other for synthesis. This is however not always feasible in bandwidth-limited overlay networks, where every node may ask for different camera views. In this work, we propose an optimized delivery strategy for free viewpoint streaming over overlay networks. We introduce the concept of layered quality-of-experience (QoE), which describes the level of interactivity offered to clients. Based on these levels of QoE, camera views are organized into layered subsets. These subsets are then delivered to clients through a prioritized network coding streaming scheme, which accommodates for the network and clients heterogeneity and effectively exploit the resources of the overlay network. Simulation results show that, in a scenario with limited bandwidth or channel reliability, the proposed method outperforms baseline network coding approaches, where the different levels of QoE are not taken into account in the delivery strategy optimization.