1,220 research outputs found

    Analysis of randomized load distribution for reproduction trees in linear arrays and rings

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    AbstractHigh performance computing requires high quality load distribution of processes of a parallel application over processors in a parallel computer at runtime such that both maximum load and dilation are minimized. The performance of a simple randomized load distribution algorithm that dynamically supports tree-structured parallel computations on two simple static networks, namely, linear arrays and rings, is analyzed in this paper. The algorithm spreads newly created tree nodes to neighboring processors, which actually provides randomized dilation-1 tree embedding in a static network. We develop linear systems of equations that characterize expected loads on all processors, and find their closed form solutions under the reproduction tree model, which can generate trees of arbitrary size and shape. The main contribution of the paper is to show that the above simple randomized algorithm is able to generate high-quality dynamic tree embeddings even in very simple and sparse networks such as linear arrays and rings. In particular, we prove that as tree size becomes large, the asymptotic performance ratio of such a randomized dilation-1 tree embedding is N/(N−1) in linear arrays and is optimal in rings

    Analysis of algorithms for online routing and scheduling in networks

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    We study situations in which an algorithm must make decisions about how to best route and schedule data transfer requests in a communication network before each transfer leaves its source. For some situations, such as those requiring quality of service guarantees, this is essential. For other situations, doing work in advance can simplify decisions in transit and increase the speed of the network. In order to reflect realistic scenarios, we require that our algorithms be online, or make their decisions without knowing future requests. We measure the efficiency of an online algorithm by its competitive ratio, which is the maximum ratio, over all request sequences, of the cost of the online algorithm\u27s solution to that of an optimal solution constructed by knowing all the requests in advance.;We identify and study two distinct variations of this general problem. In the first, data transfer requests are permanent virtual circuit requests in a circuit-switched network and the goal is to minimize the network congestion caused by the route assignment. In the second variation, data transfer requests are packets in a packet-switched network and the goal is to minimize the makespan of the schedule, or the time that the last packet reaches its destination. We present new lower bounds on the competitive ratio of any online algorithm with respect to both network congestion and makespan.;We consider two greedy online algorithms for permanent virtual circuit routing on arbitrary networks with unit capacity links, and prove both lower and upper bounds on their competitive ratios. While these greedy algorithms are not optimal, they can be expected to perform well in many circumstances and require less time to make a decision, when compared to a previously discovered asymptotically optimal online algorithm. For the online packet routing and scheduling problem, we consider an algorithm which simply assigns to each packet a priority based upon its arrival time. No packet is delayed by another packet with a lower priority. We analyze the competitive ratio of this algorithm on linear array, tree, and ring networks

    Seasonality of Prescribed Fire in the Southern Appalachians

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    There has been growing interest in recent decades in using prescribed fire for hazardous fuels reduction and ecological restoration in the southern Appalachian Mountains. The application of prescribed fire in forests of this region has typically occurred in the dormant season, but with managers often looking for more opportunities to burn. In this study, we compared the effects of dormant season and early growing season burn treatments on fire behavior, fuel consumption, and the structure and composition of plant communities in relation to topographic and meteorological influences on fire behavior. Replicated treatments were analyzed using univariate, bivariate, and multivariate methods to quantify and evaluate effects on response variables. Our results indicated that fuel moisture was lower and temperatures were higher in early growing season burns than in dormant season burns. This pattern likely contributed to the greater proportion of plot area burned in the early growing season, reflecting fire spread into parts of the landscape that would remain unburned in the dormant season. Season of burn had few significant effects on understory plant abundance and diversity. In the midstory, early growing season burns were most effective among treatments in reducing shrub density, with the greatest differences concentrated in the smallest size classes. Early growing season burns reduced midstory red maple (Acer rubrum L.) density to a greater extent than dormant season burns, though other mesophytic hardwood species may have responded differently. The combination of environmental gradients of elevation, burn severity, and change in canopy cover best explained changes in midstory community composition. In conclusion, early growing season prescribed burns may result in more variable fire behavior yet can still be expected to achieve a similar level of fuel consumption in comparison to dormant season burns. Burning in the early growing season can expand opportunities for meeting management objectives with prescribed fire and be at least as effective as burning in the dormant season in reducing the abundance of mesophytic hardwoods. Season of burn has implications for fuel consumption and response of vegetation that managers can incorporate in using prescribed fire for restoration of fire-excluded forest communities in the southern Appalachians

    Advances in Evolutionary Algorithms

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    With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field

    Interconnection Networks Embeddings and Efficient Parallel Computations.

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    To obtain a greater performance, many processors are allowed to cooperate to solve a single problem. These processors communicate via an interconnection network or a bus. The most essential function of the underlying interconnection network is the efficient interchanging of messages between processes in different processors. Parallel machines based on the hypercube topology have gained a great respect in parallel computation because of its many attractive properties. Many versions of the hypercube have been introduced by many researchers mainly to enhance communications. The twisted hypercube is one of the most attractive versions of the hypercube. It preserves the important features of the hypercube and reduces its diameter by a factor of two. This dissertation investigates relations and transformations between various interconnection networks and the twisted hypercube and explore its efficiency in parallel computation. The capability of the twisted hypercube to simulate complete binary trees, complete quad trees, and rings is demonstrated and compared with the hypercube. Finally, the fault-tolerance of the twisted hypercube is investigated. We present optimal algorithms to simulate rings in a faulty twisted hypercube environment and compare that with the hypercube

    Computer Aided Verification

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    This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book

    Fifth Biennial Report : June 1999 - August 2001

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    Security Infrastructure Technology for Integrated Utilization of Big Data

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    This open access book describes the technologies needed to construct a secure big data infrastructure that connects data owners, analytical institutions, and user institutions in a circle of trust. It begins by discussing the most relevant technical issues involved in creating safe and privacy-preserving big data distribution platforms, and especially focuses on cryptographic primitives and privacy-preserving techniques, which are essential prerequisites. The book also covers elliptic curve cryptosystems, which offer compact public key cryptosystems; and LWE-based cryptosystems, which are a type of post-quantum cryptosystem. Since big data distribution platforms require appropriate data handling, the book also describes a privacy-preserving data integration protocol and privacy-preserving classification protocol for secure computation. Furthermore, it introduces an anonymization technique and privacy risk evaluation technique. This book also describes the latest related findings in both the living safety and medical fields. In the living safety field, to prevent injuries occurring in everyday life, it is necessary to analyze injury data, find problems, and implement suitable measures. But most cases don’t include enough information for injury prevention because the necessary data is spread across multiple organizations, and data integration is difficult from a security standpoint. This book introduces a system for solving this problem by applying a method for integrating distributed data securely and introduces applications concerning childhood injury at home and school injury. In the medical field, privacy protection and patient consent management are crucial for all research. The book describes a medical test bed for the secure collection and analysis of electronic medical records distributed among various medical institutions. The system promotes big-data analysis of medical data with a cloud infrastructure and includes various security measures developed in our project to avoid privacy violations

    NATURAL AND ANTHROPOGENIC DRIVERS OF TREE EVOLUTIONARY DYNAMICS

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    Species of trees inhabit diverse and heterogeneous environments, and often play important ecological roles in such communities. As a result of their vast ecological breadth, trees have become adapted to various environmental pressures. In this dissertation I examine various environmental factors that drive evolutionary dynamics in threePinusspecies in California and Nevada, USA. In chapter two, I assess the role of management influence of thinning, fire, and their interaction on fine-scale gene flow within fire-suppressed populations of Pinus lambertiana, a historically dominant and ecologically important member of mixed-conifer forests of the Sierra Nevada, California. Here, I find evidence that treatment prescription differentially affects fine-scale genetic structure and effective gene flow in this species. In my third chapter, I describe the development of a dense linkage map for Pinus balfouriana which I use in chapter four to assess the quantitative trait locus (QTL) landscape of water-use efficiency across two isolated ranges of the species. I find evidence that precipitation-related variables structure the geographical range of P. balfouriana, that traits related to water-use efficiency are heritable and differentiated across populations, and associated QTLs underlying this phenotypic variation explain large proportions of total variation. In chapter five, I assess evidence for local adaptation to the eastern Sierra Nevada rain shadow within P. albicaulisacross fine spatial scales of the Lake Tahoe Basin, USA. Here, genetic variation of traits related to water availability were structured more so across populations than neutral variation, and loci identified by genome-wide association methods show elevated signals of local adaptation that track soil water availability. In chapter six, I review theory related to polygenic local adaptation and literature of genotype-phenotype associations in trees. I find that evidence suggests a polygenic basis for many traits important to conservation and industry, and I suggest paths forward to best describing such genetic bases in tree species. Overall, my results show that spatial and genetic structure of trees are often driven by their environment, and that ongoing selective pressures driven by environmental change will continue to be important in these systems
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