A Distributed TDMA Slot Scheduling Algorithm for Spatially Correlated Contention in WSNs

In WSNs the communication traffic is often time and space correlated, where multiple nodes in a proximity start transmitting simultaneously. Such a situation is known as spatially correlated contention. The random access method to resolve such contention suffers from high collision rate, whereas the traditional distributed TDMA scheduling techniques primarily try to improve the network capacity by reducing the schedule length. Usually, the situation of spatially correlated contention persists only for a short duration, and therefore generating an optimal or suboptimal schedule is not very useful. Additionally, if an algorithm takes very long time to schedule, it will not only introduce additional delay in the data transfer but also consume more energy. In this paper, we present a distributed TDMA slot scheduling (DTSS) algorithm, which considerably reduces the time required to perform scheduling, while restricting the schedule length to the maximum degree of interference graph. The DTSS algorithm supports unicast, multicast, and broadcast scheduling, simultaneously without any modification in the protocol. We have analyzed the protocol for average case performance and also simulated it using Castalia simulator to evaluate its runtime performance. Both analytical and simulation results show that our protocol is able to considerably reduce the time required for scheduling.

Transverse Single Spin Asymmetries and Charmonium Production

We estimate transverse spin single spin asymmetry(TSSA) in the process e + p(up arrow) -> J/psi + X using color evaporation model of charmonium production. We take into account transverse momentum dependent(TMD) evolution of Sivers function and parton distribution function and show that the there is a reduction in the asymmetry as compared to our earlier estimates wherein the Q(2) - evolution was implemented only through DGLAP evolution of unpolarized gluon densities.

Low Complexity Power and Scheduling Policies for Wireless Networks to Provide Quality of Service

We consider optimal power allocation policies for a single server, multiuser system. The power is consumed in transmission of data only. The transmission channel may experience multipath fading. We obtain very efficient, low computational complexity algorithms which minimize power and ensure stability of the data queues. We also obtain policies when the users may have mean delay constraints. If the power required is a linear function of rate then we exploit linearity and obtain linear programs with low complexity.

Performance of OFDM Systems With Best-m Feedback, Scheduling, and Delays for Uniformly Correlated Subchannels

Contemporary cellular standards, such as Long Term Evolution (LTE) and LTE-Advanced, employ orthogonal frequency-division multiplexing (OFDM) and use frequency-domain scheduling and rate adaptation. In conjunction with feedback reduction schemes, high downlink spectral efficiencies are achieved while limiting the uplink feedback overhead. One such important scheme that has been adopted by these standards is best-m feedback, in which every user feeds back its m largest subchannel (SC) power gains and their corresponding indices. We analyze the single cell average throughput of an OFDM system with uniformly correlated SC gains that employs best-m feedback and discrete rate adaptation. Our model incorporates three schedulers that cover a wide range of the throughput versus fairness tradeoff and feedback delay. We show that, for small m, correlation significantly reduces average throughput with best-m feedback. This result is pertinent as even in typical dispersive channels, correlation is high. We observe that the schedulers exhibit varied sensitivities to correlation and feedback delay. The analysis also leads to insightful expressions for the average throughput in the asymptotic regime of a large number of users.

An Implementation of Partitioned Scheduling Scheme for Hard Real-Time Tasks in Multicore Linux with Fair Share for Linux Tasks

The correctness of a hard real-time system depends its ability to meet all its deadlines. Existing real-time systems use either a pure real-time scheduler or a real-time scheduler embedded as a real-time scheduling class in the scheduler of an operating system (OS). Existing implementations of schedulers in multicore systems that support real-time and non-real-time tasks, permit the execution of non-real-time tasks in all the cores with priorities lower than those of real-time tasks, but interrupts and softirqs associated with these non-real-time tasks can execute in any core with priorities higher than those of real-time tasks. As a result, the execution overhead of real-time tasks is quite large in these systems, which, in turn, affects their runtime. In order that the hard real-time tasks can be executed in such systems with minimal interference from other Linux tasks, we propose, in this paper, an integrated scheduler architecture, called SchedISA, which aims to considerably reduce the execution overhead of real-time tasks in these systems. In order to test the efficacy of the proposed scheduler, we implemented partitioned earliest deadline first (P-EDF) scheduling algorithm in SchedISA on Linux kernel, version 3.8, and conducted experiments on Intel core i7 processor with eight logical cores. We compared the execution overhead of real-time tasks in the above implementation of SchedISA with that in SCHED_DEADLINE's P-EDF implementation, which concurrently executes real-time and non-real-time tasks in Linux OS in all the cores. The experimental results show that the execution overhead of real-time tasks in the above implementation of SchedISA is considerably less than that in SCHED_DEADLINE. We believe that, with further refinement of SchedISA, the execution overhead of real-time tasks in SchedISA can be reduced to a predictable maximum, making it suitable for scheduling hard real-time tasks without affecting the CPU share of Linux tasks.

Role of supersymmetric heavy Higgs boson production in the self-coupling measurement of 125 GeV Higgs boson at the LHC

Measurement of the self-coupling of the 125 GeV Higgs boson is one of the most crucial tasks for a high luminosity run of the LHC, and it can only be measured in the di-Higgs final state. In the minimal supersymmetric standard model, heavy CP even Higgs (H) can decay into a lighter 125 GeV Higgs boson (h) and, therefore, can influence the rate of di-Higgs production. We investigate the role of single H production in the context of measuring the self-coupling of h. We have found that the H -> hh decay can change the value of Higgs (h) self-coupling substantially, in a low tan beta regime where the mass of the heavy Higgs boson lies between 250 and 600 GeV and, depending on the parameter space, it may be seen as an enhancement of the self-coupling of the 125 GeV Higgs boson.

Jet substructure and probes of CP violation in Vh production

We analyse the hVV (V = W, Z) vertex in a model independent way using Vh production. To that end, we consider possible corrections to the Standard Model Higgs Lagrangian, in the form of higher dimensional operators which parametrise the effects of new physics. In our analysis, we pay special attention to linear observables that can be used to probe CP violation in the same. By considering the associated production of a Higgs boson with a vector boson (W or Z), we use jet substructure methods to define angular observables which are sensitive to new physics effects, including an asymmetry which is linearly sensitive to the presence of CP odd effects. We demonstrate how to use these observables to place bounds on the presence of higher dimensional operators, and quantify these statements using a log likelihood analysis. Our approach allows one to probe separately the hZZ and hWW vertices, involving arbitrary combinations of BSM operators, at the Large Hadron Collider.

Production and characterization of bioflocculants for mineral processing applications

A comparative study of two bacterial strains namely, Bacillus licheniformis and Bacillus firmus in the production of bioflocculants was made. The highest bioflocculant yield of 16.55 g/L was obtained from B. licheniformis (L) and 10 g/L from B. firmus (F). The bioflocculants obtained from the bacterial species were water soluble and insoluble in organic solvents. FTIR spectral analysis revealed the presence of hydroxyl, carboxyl and sugar derivatives in the bioflocculants. Thermal characterization by differential scanning calorimetry (DSC) showed the crystalline transition and the melting point (T-m) at 90-100 degrees C. Effects of bioflocculant dosage and pH on the flocculation of clay fines were evaluated. Highest bioflocculation efficiency on kaolin clay suspensions was observed at an optimum bioflocculant dosage of 5 g/L. The optimum pH range for the maximum bioflocculation was at pH 7-9. Bioflocculants exhibited high efficiency in dye decolorization. The maximum Cr (VI) removal was found to be 85 % for L (bioflocculant dosage at 2 g/L). This study demonstrates that microbial bioflocculants find potential applications in mineral processing such as selective flocculation of mineral fines, decolorization of dye solutions and in the remediation of toxic metal solutions. (C) 2015 Elsevier B.V. All rights reserved.

Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

Simplified Mixture Design for Production of Self-Consolidating Concrete

In this work, a methodology to achieve ordinary-, medium-, and high-strength self-consolidating concrete (SCC) with and without mineral additions is proposed. The inclusion of Class F fly ash increases the density of SCC but retards the hydration rate, resulting in substantial strength gain only after 28 days. This delayed strength gain due to the use of fly ash has been considered in the mixture design model. The accuracy of the proposed mixture design model is validated with the present test data and mixture and strength data obtained from diverse sources reported in the literature.

Linking carbon metabolism to carotenoid production in mycobacteria using Raman spectroscopy

Bacteria can utilize multiple sources of carbon for growth, and for pathogenic bacteria like Mycobacterium tuberculosis, this ability is crucial for survival within the host. In addition, phenotypic changes are seen in mycobacteria grown under different carbon sources. In this study, we use Raman spectroscopy to analyze the biochemical components present in M. smegmatis cells when grown in three differently metabolized carbon sources. Our results show that carotenoid biosynthesis is enhanced when M. smegmatis is grown in glucose compared to glycerol and acetate. We demonstrate that this difference is most likely due to transcriptional upregulation of the carotenoid biosynthesis operon (crt) mediated by higher levels of the stress-responsive sigma factor SigF. Moreover, we find that increased SigF and carotenoid levels correlate with greater resistance of glucose-grown cells to oxidative stress. Thus, we demonstrate the use of Raman spectroscopy in unraveling unknown aspects of mycobacterial physiology and describe a novel effect of carbon source variation on mycobacteria.

Dynamics of Cricket Sound Production

The clever designs of natural transducers are a great source of inspiration for man-made systems. At small length scales, there are many transducers in nature that we are now beginning to understand and learn from. Here, we present an example of such a transducer that is used by field crickets to produce their characteristic song. This transducer uses two distinct components-a file of discrete teeth and a plectrum that engages intermittently to produce a series of impulses forming the loading, and an approximately triangular membrane, called the harp, that acts as a resonator and vibrates in response to the impulse-train loading. The file-and-plectrum act as a frequency multiplier taking the low wing beat frequency as the input and converting it into an impulse-train of sufficiently high frequency close to the resonant frequency of the harp. The forced vibration response results in beats producing the characteristic sound of the cricket song. With careful measurements of the harp geometry and experimental measurements of its mechanical properties (Young's modulus determined from nanoindentation tests), we construct a finite element (FE) model of the harp and carry out modal analysis to determine its natural frequency. We fine tune the model with appropriate elastic boundary conditions to match the natural frequency of the harp of a particular species-Gryllus bimaculatus. We model impulsive loading based on a loading scheme reported in literature and predict the transient response of the harp. We show that the harp indeed produces beats and its frequency content matches closely that of the recorded song. Subsequently, we use our FE model to show that the natural design is quite robust to perturbations in the file. The characteristic song frequency produced is unaffected by variations in the spacing of file-teeth and even by larger gaps. Based on the understanding of how this natural transducer works, one can design and fabricate efficient microscale acoustic devices such as microelectromechanical systems (MEMS) loudspeakers.

Wireless scheduling with partial channel state information: large deviations and optimality

We consider a server serving a time-slotted queued system of multiple packet-based flows, where not more than one flow can be serviced in a single time slot. The flows have exogenous packet arrivals and time-varying service rates. At each time, the server can observe instantaneous service rates for only a subset of flows ( selected from a fixed collection of observable subsets) before scheduling a flow in the subset for service. We are interested in queue length aware scheduling to keep the queues short. The limited availability of instantaneous service rate information requires the scheduler to make a careful choice of which subset of service rates to sample. We develop scheduling algorithms that use only partial service rate information from subsets of channels, and that minimize the likelihood of queue overflow in the system. Specifically, we present a new joint subset-sampling and scheduling algorithm called Max-Exp that uses only the current queue lengths to pick a subset of flows, and subsequently schedules a flow using the Exponential rule. When the collection of observable subsets is disjoint, we show that Max-Exp achieves the best exponential decay rate, among all scheduling algorithms that base their decision on the current ( or any finite past history of) system state, of the tail of the longest queue. To accomplish this, we employ novel analytical techniques for studying the performance of scheduling algorithms using partial state, which may be of independent interest. These include new sample-path large deviations results for processes obtained by non-random, predictable sampling of sequences of independent and identically distributed random variables. A consequence of these results is that scheduling with partial state information yields a rate function significantly different from scheduling with full channel information. In the special case when the observable subsets are singleton flows, i.e., when there is effectively no a priori channel state information, Max-Exp reduces to simply serving the flow with the longest queue; thus, our results show that to always serve the longest queue in the absence of any channel state information is large deviations optimal.

Prediction of Fatigue Life in Plain Concrete Using Entropy Production

An energy approach within the framework of thermodynamics is used to model the fatigue process in plain concrete. Fatigue crack growth is an irreversible process associated with an irreversible entropy gain. A closed-form expression for entropy generated during fatigue in terms of energy dissipated is derived using principles of dimensional analysis and self-similarity. An increase in compliance is considered as a measure of damage accumulated during fatigue. The entropy at final fatigue failure is shown to be independent of loading and geometry and is proposed as a material property. A relationship between energy dissipated and number of cycles of fatigue loading is obtained. (C) 2015 American Society of Civil Engineers.