2,725 research outputs found

    How Long It Takes for an Ordinary Node with an Ordinary ID to Output?

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    In the context of distributed synchronous computing, processors perform in rounds, and the time-complexity of a distributed algorithm is classically defined as the number of rounds before all computing nodes have output. Hence, this complexity measure captures the running time of the slowest node(s). In this paper, we are interested in the running time of the ordinary nodes, to be compared with the running time of the slowest nodes. The node-averaged time-complexity of a distributed algorithm on a given instance is defined as the average, taken over every node of the instance, of the number of rounds before that node output. We compare the node-averaged time-complexity with the classical one in the standard LOCAL model for distributed network computing. We show that there can be an exponential gap between the node-averaged time-complexity and the classical time-complexity, as witnessed by, e.g., leader election. Our first main result is a positive one, stating that, in fact, the two time-complexities behave the same for a large class of problems on very sparse graphs. In particular, we show that, for LCL problems on cycles, the node-averaged time complexity is of the same order of magnitude as the slowest node time-complexity. In addition, in the LOCAL model, the time-complexity is computed as a worst case over all possible identity assignments to the nodes of the network. In this paper, we also investigate the ID-averaged time-complexity, when the number of rounds is averaged over all possible identity assignments. Our second main result is that the ID-averaged time-complexity is essentially the same as the expected time-complexity of randomized algorithms (where the expectation is taken over all possible random bits used by the nodes, and the number of rounds is measured for the worst-case identity assignment). Finally, we study the node-averaged ID-averaged time-complexity.Comment: (Submitted) Journal versio

    Walks of molecular motors in two and three dimensions

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    Molecular motors interacting with cytoskeletal filaments undergo peculiar random walks consisting of alternating sequences of directed movements along the filaments and diffusive motion in the surrounding solution. An ensemble of motors is studied which interacts with a single filament in two and three dimensions. The time evolution of the probability distribution for the bound and unbound motors is determined analytically. The diffusion of the motors is strongly enhanced parallel to the filament. The analytical expressions are in excellent agreement with the results of Monte Carlo simulations.Comment: 7 pages, 2 figures, to be published in Europhys. Let

    Runtime Distributions and Criteria for Restarts

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    Randomized algorithms sometimes employ a restart strategy. After a certain number of steps, the current computation is aborted and restarted with a new, independent random seed. In some cases, this results in an improved overall expected runtime. This work introduces properties of the underlying runtime distribution which determine whether restarts are advantageous. The most commonly used probability distributions admit the use of a scale and a location parameter. Location parameters shift the density function to the right, while scale parameters affect the spread of the distribution. It is shown that for all distributions scale parameters do not influence the usefulness of restarts and that location parameters only have a limited influence. This result simplifies the analysis of the usefulness of restarts. The most important runtime probability distributions are the log-normal, the Weibull, and the Pareto distribution. In this work, these distributions are analyzed for the usefulness of restarts. Secondly, a condition for the optimal restart time (if it exists) is provided. The log-normal, the Weibull, and the generalized Pareto distribution are analyzed in this respect. Moreover, it is shown that the optimal restart time is also not influenced by scale parameters and that the influence of location parameters is only linear

    Tight Bounds for MIS in Multichannel Radio Networks

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    Daum et al. [PODC'13] presented an algorithm that computes a maximal independent set (MIS) within O(log2n/F+lognpolyloglogn)O(\log^2 n/F+\log n \mathrm{polyloglog} n) rounds in an nn-node multichannel radio network with FF communication channels. The paper uses a multichannel variant of the standard graph-based radio network model without collision detection and it assumes that the network graph is a polynomially bounded independence graph (BIG), a natural combinatorial generalization of well-known geographic families. The upper bound of that paper is known to be optimal up to a polyloglog factor. In this paper, we adapt algorithm and analysis to improve the result in two ways. Mainly, we get rid of the polyloglog factor in the runtime and we thus obtain an asymptotically optimal multichannel radio network MIS algorithm. In addition, our new analysis allows to generalize the class of graphs from those with polynomially bounded local independence to graphs where the local independence is bounded by an arbitrary function of the neighborhood radius.Comment: 37 pages, to be published in DISC 201

    On Profit-Maximizing Pricing for the Highway and Tollbooth Problems

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    In the \emph{tollbooth problem}, we are given a tree \bT=(V,E) with nn edges, and a set of mm customers, each of whom is interested in purchasing a path on the tree. Each customer has a fixed budget, and the objective is to price the edges of \bT such that the total revenue made by selling the paths to the customers that can afford them is maximized. An important special case of this problem, known as the \emph{highway problem}, is when \bT is restricted to be a line. For the tollbooth problem, we present a randomized O(logn)O(\log n)-approximation, improving on the current best O(logm)O(\log m)-approximation. We also study a special case of the tollbooth problem, when all the paths that customers are interested in purchasing go towards a fixed root of \bT. In this case, we present an algorithm that returns a (1ϵ)(1-\epsilon)-approximation, for any ϵ>0\epsilon > 0, and runs in quasi-polynomial time. On the other hand, we rule out the existence of an FPTAS by showing that even for the line case, the problem is strongly NP-hard. Finally, we show that in the \emph{coupon model}, when we allow some items to be priced below zero to improve the overall profit, the problem becomes even APX-hard

    On the form of growing strings

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    Patterns and forms adopted by Nature, such as the shape of living cells, the geometry of shells and the branched structure of plants, are often the result of simple dynamical paradigms. Here we show that a growing self-interacting string attached to a tracking origin, modeled to resemble nascent polypeptides in vivo, develops helical structures which are more pronounced at the growing end. We also show that the dynamic growth ensemble shares several features of an equilibrium ensemble in which the growing end of the polymer is under an effective stretching force. A statistical analysis of native states of proteins shows that the signature of this non-equilibrium phenomenon has been fixed by evolution at the C-terminus, the growing end of a nascent protein. These findings suggest that a generic non-equilibrium growth process might have provided an additional evolutionary advantage for nascent proteins by favoring the preferential selection of helical structures.Comment: 4 pages, 3 figures. Accepted for publication in Phys. Rev. Let

    Afadin orients cell division to position the tubule lumen in developing renal tubules

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    In many types of tubules, continuity of the lumen is paramount to tubular function, yet how tubules generate lumen continuity in vivo is not known. We recently found the F-actin binding protein Afadin is required for lumen continuity in developing renal tubules, though its mechanism of action remains unknown. Here we demonstrate Afadin is required for lumen continuity by orienting the mitotic spindle during cell division. Using an in vitro 3D cyst model, we find Afadin localizes to the cell cortex adjacent to the spindle poles and orients the mitotic spindle. In tubules, cell division may be oriented relative to two axes, longitudinal and apical-basal. Unexpectedly, in vivo examination of early stage developing nephron tubules reveals cell division is not oriented in the longitudinal (or planar polarized) axis. However, cell division is oriented perpendicular to the apical-basal axis. Absence of Afadin in vivo leads to misorientation of apical-basal cell division in nephron tubules. Together these results support a model whereby Afadin determines lumen placement by directing apical-basal spindle orientation, which generates a continuous lumen and normal tubule morphogenesis

    Computing in Additive Networks with Bounded-Information Codes

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    This paper studies the theory of the additive wireless network model, in which the received signal is abstracted as an addition of the transmitted signals. Our central observation is that the crucial challenge for computing in this model is not high contention, as assumed previously, but rather guaranteeing a bounded amount of \emph{information} in each neighborhood per round, a property that we show is achievable using a new random coding technique. Technically, we provide efficient algorithms for fundamental distributed tasks in additive networks, such as solving various symmetry breaking problems, approximating network parameters, and solving an \emph{asymmetry revealing} problem such as computing a maximal input. The key method used is a novel random coding technique that allows a node to successfully decode the received information, as long as it does not contain too many distinct values. We then design our algorithms to produce a limited amount of information in each neighborhood in order to leverage our enriched toolbox for computing in additive networks

    The Potential of Restarts for ProbSAT

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    This work analyses the potential of restarts for probSAT, a quite successful algorithm for k-SAT, by estimating its runtime distributions on random 3-SAT instances that are close to the phase transition. We estimate an optimal restart time from empirical data, reaching a potential speedup factor of 1.39. Calculating restart times from fitted probability distributions reduces this factor to a maximum of 1.30. A spin-off result is that the Weibull distribution approximates the runtime distribution for over 93% of the used instances well. A machine learning pipeline is presented to compute a restart time for a fixed-cutoff strategy to exploit this potential. The main components of the pipeline are a random forest for determining the distribution type and a neural network for the distribution's parameters. ProbSAT performs statistically significantly better than Luby's restart strategy and the policy without restarts when using the presented approach. The structure is particularly advantageous on hard problems.Comment: Eurocast 201

    Household-level risk factors for secondary influenza-like illness in a rural area of Bangladesh

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    This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Objective To describe household‐level risk factors for secondary influenza‐like illness (ILI), an important public health concern in the low‐income population of Bangladesh. Methods Secondary analysis of control participants in a randomised controlled trial evaluating the effect of handwashing to prevent household ILI transmission. We recruited index‐case patients with ILI – fever (<5 years); fever, cough or sore throat (≥5 years) – from health facilities, collected information on household factors and conducted syndromic surveillance among household contacts for 10 days after resolution of index‐case patients’ symptoms. We evaluated the associations between household factors at baseline and secondary ILI among household contacts using negative binomial regression, accounting for clustering by household. Results Our sample was 1491 household contacts of 184 index‐case patients. Seventy‐one percentage reported that smoking occurred in their home, 27% shared a latrine with one other household and 36% shared a latrine with >1 other household. A total of 114 household contacts (7.6%) had symptoms of ILI during follow‐up. Smoking in the home (RRadj 1.9, 95% CI: 1.2, 3.0) and sharing a latrine with one household (RRadj 2.1, 95% CI: 1.2, 3.6) or >1 household (RRadj 3.1, 95% CI: 1.8–5.2) were independently associated with increased risk of secondary ILI. Conclusion Tobacco use in homes could increase respiratory illness in Bangladesh. The mechanism between use of shared latrines and household ILI transmission is not clear. It is possible that respiratory pathogens could be transmitted through faecal contact or contaminated fomites in shared latrines
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