Link failure detection for maintaining session continuity in packet data networks

A link failure in the path of a virtual circuit in a packet data network will lead to premature disconnection of the circuit by the end-points. A soft failure will result in degraded throughput over the virtual circuit. If these failures can be detected quickly and reliably, then appropriate rerouteing strategies can automatically reroute the virtual circuits that use the failed facility. In this paper, we develop a methodology for analysing and designing failure detection schemes for digital facilities. Based on errored second data, we develop a Markov model for the error and failure behaviour of a T1 trunk. The performance of a detection scheme is characterized by its false alarm probability and the detection delay. Using the Markov model, we analyse the performance of detection schemes that use physical layer or link layer information. The schemes basically rely upon detecting the occurrence of severely errored seconds (SESs). A failure is declared when a counter, that is driven by the occurrence of SESs, reaches a certain threshold.For hard failures, the design problem reduces to a proper choice;of the threshold at which failure is declared, and on the connection reattempt parameters of the virtual circuit end-point session recovery procedures. For soft failures, the performance of a detection scheme depends, in addition, on how long and how frequent the error bursts are in a given failure mode. We also propose and analyse a novel Level 2 detection scheme that relies only upon anomalies observable at Level 2, i.e. CRC failures and idle-fill flag errors. Our results suggest that Level 2 schemes that perform as well as Level 1 schemes are possible.

Distributed intrusion detection in the presence of correlated sensor readings: Signal-space and communication-complexity view-point

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space view-point is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces f(s) and f(g) and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating f(s) and f(g) is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication-complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. Extensions to the multi-party case is straightforward and is briefly discussed. The average case CC of the relevant greaterthan (CT) function is characterized within two bits. Under the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm. 2010 Elsevier B.V. All rights reserved.

Polyaniline modified electrodes for detection of dyes

Polyaniline (PANI) is one of the most extensively used conjugated polymers in the design of electrochemical sensors. In this study, we report electrochemical dye detection based on PANI for the adsorption of both anionic and cationic dyes from solution. The inherent property of PANI to adsorb dyes has been explored for the development of electrochemical detection of dye in solution. The PANI film was grown on electrode via electrochemical polymerization. The as grown PANI film could easily adsorb the dye in the electrolyte solution and form an insulating layer on the PANI coated electrode. As a result, the current intensity of the PANI film was significantly altered. Furthermore, PANI coated stainless steel (SS) electrodes show a change in the current intensity of Fe2+/Fe3+ redox peaks due to the addition of dye in electrolyte solution. PANI films coated on both Pt electrodes and non-expensive SS electrodes showed the concentration of dye adsorbed is directly proportional to the current intensity or potential shift and thus can be used for the quantitative detection of textile dyes at very low concentrations. (C) 2011 Elsevier B.V. All rights reserved.

Transitional intermittency detection by neural network

A neural network has been used to predict the flow intermittency from velocity signals in the transition zone in a boundary layer. Unlike many of the available intermittency detection methods requiring a proper threshold choice in order to distinguish between the turbulent and non-turbulent parts of a signal, a trained neural network does not involve any threshold decision. The intermittency prediction based on the neural network has been found to be very satisfactory.

A fault-tolerant distributed deadlock detection algorithm

In this paper, we propose a new fault-tolerant distributed deadlock detection algorithm which can handle loss of any resource release message. It is based on a token-based distributed mutual exclusion algorithm. We have evaluated and compared the performance of the proposed algorithm with two other algorithms which belong to two different classes, using simulation studies. The proposed algorithm is found to be efficient in terms of average number of messages per wait and average deadlock duration compared to the other two algorithms in all situations, and has comparable or better performance in terms of other parameters.

GNSS Signal Detection Under Noise Uncertainty

High sensitivity detection techniques are required for indoor navigation using Global Navigation Satellite System (GNSS) receivers, and typically, a combination of coherent and non- coherent integration is used as the test statistic for detection. The coherent integration exploits the deterministic part of the signal and is limited due to the residual frequency error, navigation data bits and user dynamics, which are not known apriori. So, non- coherent integration, which involves squaring of the coherent integration output, is used to improve the detection sensitivity. Due to this squaring, it is robust against the artifacts introduced due to data bits and/or frequency error. However, it is susceptible to uncertainty in the noise variance, and this can lead to fundamental sensitivity limits in detecting weak signals. In this work, the performance of the conventional non-coherent integration-based GNSS signal detection is studied in the presence of noise uncertainty. It is shown that the performance of the current state of the art GNSS receivers is close to the theoretical SNR limit for reliable detection at moderate levels of noise uncertainty. Alternate robust post-coherent detectors are also analyzed, and are shown to alleviate the noise uncertainty problem. Monte-Carlo simulations are used to confirm the theoretical predictions.

Improved large-MIMO detection based on damped belief propagation

In this paper, we consider the application of belief propagation (BP) to achieve near-optimal signal detection in large multiple-input multiple-output (MIMO) systems at low complexities. Large-MIMO architectures based on spatial multiplexing (V-BLAST) as well as non-orthogonal space-time block codes(STBC) from cyclic division algebra (CDA) are considered. We adopt graphical models based on Markov random fields (MRF) and factor graphs (FG). In the MRF based approach, we use pairwise compatibility functions although the graphical models of MIMO systems are fully/densely connected. In the FG approach, we employ a Gaussian approximation (GA) of the multi-antenna interference, which significantly reduces the complexity while achieving very good performance for large dimensions. We show that i) both MRF and FG based BP approaches exhibit large-system behavior, where increasingly closer to optimal performance is achieved with increasing number of dimensions, and ii) damping of messages/beliefs significantly improves the bit error performance.

Data rectification and detection of trend shifts in jet engine path measurements using median filters and fuzzy logic

Filtering methods are explored for removing noise from data while preserving sharp edges that many indicate a trend shift in gas turbine measurements. Linear filters are found to be have problems with removing noise while preserving features in the signal. The nonlinear hybrid median filter is found to accurately reproduce the root signal from noisy data. Simulated faulty data and fault-free gas path measurement data are passed through median filters and health residuals for the data set are created. The health residual is a scalar norm of the gas path measurement deltas and is used to partition the faulty engine from the healthy engine using fuzzy sets. The fuzzy detection system is developed and tested with noisy data and with filtered data. It is found from tests with simulated fault-free and faulty data that fuzzy trend shift detection based on filtered data is very accurate with no false alarms and negligible missed alarms.

Performance analysis of the random early detection algorithm

In this article we consider a finite queue with its arrivals controlled by the random early detection algorithm. This is one of the most prominent congestion avoidance schemes in the Internet routers. The aggregate arrival stream from the population of transmission control protocol sources is locally considered stationary renewal or Markov modulated Poisson process with general packet length distribution. We study the exact dynamics of this queue and provide the stability and the rates of convergence to the stationary distribution and obtain the packet loss probability and the waiting time distribution. Then we extend these results to a two traffic class case with each arrival stream renewal. However, computing the performance indices for this system becomes computationally prohibitive. Thus, in the latter half of the article, we approximate the dynamics of the average queue length process asymptotically via an ordinary differential equation. We estimate the error term via a diffusion approximation. We use these results to obtain approximate transient and stationary performance of the system. Finally, we provide some computational examples to show the accuracy of these approximations.

Prevalence of, and antigenic variation in, serotype G10 rotaviruses and detection of serotype G3 strains in diarrheic calves: Implications for the origin of G10P11 or P11 type reassortant asymptomatic strains in newborn children in India

Previous studies have shown predominant association of G10P11 type bovine rotavirus-derived reassortant strains with asymptomatic infections in newborn children in India. To understand the epidemiological and genetic basis for the origin of these strains in humans, the relative frequencies of different serotypes among bovine rotaviruses (BRVs) isolated from southern, western and central regions of the country were determined by subgroup and serotype analysis as well as nucleotide (nt) sequence analysis of the genes encoding the outer capsid proteins VP4 and VP7. Since the human G10P11 asymptomatic neonatal strain I321 possessed NSP1 from a human rotavirus, to determine its genetic origin in the bovine strains, comparative analysis of partial gene sequences from representative G10P11 strains was also carried out. The following observations were of great epidemiological significance, (i) G10P11 strains predominated in all the three regions with frequencies ranging between 55.6% and 85.2%. In contrast to the high prevalence of G6 strains in other countries, only one G6 strain was detected in this study and G8 strains represented 5.8% of the isolates, (ii) among the G10 strains, in serotyping ELISA, four patterns of reactivity were observed that appeared to correlate with the differences in electropherotypic patterns and amino acid (aa) sequence of the VP7, (iii) surprisingly, strains belonging to serotype G3 were detected more frequently (10.7%) than those of serotypes G6 and G8 combined, while strains representing the new serotype (G15) were observed in a single farm in Bangalore, and (iv) about 3.9% of the isolates were nontypeable as they exhibited high cross-reactivity to the serotyping MAbs used in the study. Comparative analysis of the VP7 gene sequence from the prototype G3 MAb-reactive bovine strain J63 revealed greatest sequence relatedness (87.6% nt and 96.0% aa) with that of serotype G3 rhesus-monkey strain RRV. It also exhibited high sequence homology with the VP7 from several animal and animal rotavirus-related human G3 strains (Simian SA11; equine ERV316 and FI-14. canine CU-1 and K9; porcine 4F; Feline Cat2 and human HCR3, YO and AU1). Partial nucleotide sequence analysis of the NSP1 gene of J63 showed greatest nt sequence homology (95.9%) to the NSP1 gene allele of the Indian G8 strain, isolated from a diarrheic child, which is likely to have been transmitted directly from cattle and 92.6% homology to that of the bovine G8 strain A5-10 suggesting the likely origin of J63 by gene reassortment between a bovine G8 strain and a G3 animal strain. Prevalence of G10P11 strains in cattle and G10P11 or P11 type reassortant strains in asymptomatic neonates as well as detection of G8P[1] strains in diarrheic children support our hypothesis for bidirectional transmission of rotaviruses between humans and cattle and origin of novel strains catalyzed by the age-old traditions and socio-economic conditions in India.

Very large array detection of radio recombination lines from the radio nucleus of NGC 253: Ionization by a weak active galactic nucleus, an obscured super star cluster, or a compact supernova remnant?

We have imaged the H92alpha and H75alpha radio recombination line (RRL) emissions from the starburst galaxy NGC 253 with a resolution of similar to4 pc. The peak of the RRL emission at both frequencies coincides with the unresolved radio nucleus. Both lines observed toward the nucleus are extremely wide, with FWHMs of similar to200 km s(-1). Modeling the RRL and radio continuum data for the radio nucleus shows that the lines arise in gas whose density is similar to10(4) cm(-3) and mass is a few thousand M., which requires an ionizing flux of (6-20) x 10(51) photons s(-1). We consider a supernova remnant (SNR) expanding in a dense medium, a star cluster, and also an active galactic nucleus (AGN) as potential ionizing sources. Based on dynamical arguments, we rule out an SNR as a viable ionizing source. A star cluster model is considered, and the dynamics of the ionized gas in a stellar-wind driven structure are investigated. Such a model is only consistent with the properties of the ionized gas for a cluster younger than similar to10(5) yr. The existence of such a young cluster at the nucleus seems improbable. The third model assumes the ionizing source to be an AGN at the nucleus. In this model, it is shown that the observed X-ray flux is too weak to account for the required ionizing photon flux. However, the ionization requirement can be explained if the accretion disk is assumed to have a big blue bump in its spectrum. Hence, we favor an AGN at the nucleus as the source responsible for ionizing the observed RRLs. A hybrid model consisting of an inner advection-dominated accretion flow disk and an outer thin disk is suggested, which could explain the radio, UV, and X-ray luminosities of the nucleus.

Development of recombinant coat protein antibody based IC-RT-PCR for detection and discrimination of sugarcane streak mosaic virus isolates from Southern India

Sugarcane streak mosaic virus (SCSMV), causes mosaic disease of sugarcane and is thought to belong to a new undescribed genus in the family Potyviridae. The coat protein (CP) gene from the Andhra Pradesh (AP) isolate of SCSMV (SCSMV AP) was cloned and expressed in Escherichia coli. The recombinant coat protein was used to raise high quality antiserum. The CP antiserum was used to develop an immunocapture reverse transcription-polymerase chain reaction (IC-RT-PCR) based assay for the detection and discrimination of SCSMV isolates in South India. The sequence of the cloned PCR products encoding 3'untranslated region (UTR) and CP regions of the virus isolates from three different locations in South India viz. Tanuku (Coastal Andhra Pradesh), Coimbatore (Tamil Nadu) and Hospet (Karnataka) was compared with that of SCSMV AP The analysis showed that they share 89.4, 89.5 and 90% identity respectively at the nucleotide level. This suggests that the isolates causing mosaic disease of sugarcane in South India are indeed strains of SCSMV In addition, the sensitivity of the IC-RT-PCR was compared with direct antigen coating-enzyme linked immunosorbent assay (DAC-ELISA) and dot-blot immunobinding assays and was found to be more sensitive and hence could be used to detect the presence of virus in sugarcane breeding, germplasm centres and in quarantine programs.