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Literatura académica sobre el tema "Dynamic dependence graph"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 4 de febrero de 2022

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Artículos de revistas sobre el tema "Dynamic dependence graph"

Mikov, A. I. "Connectivity of dynamic graphs in multiply connected spaces". Informatization and communication, n.º 2 (30 de abril de 2020): 108–13. http://dx.doi.org/10.34219/2078-8320-2020-11-2-108-113.

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Dynamic geometric graphs are natural mathematical models of many real-world systems placed and moving in space: computer ad hoc networks, transport systems, territorial distributed systems for various purposes. An important property of such graphs is connectivity, which is difficult to maintain during movement due to the presence of obstacles on the ground. In this paper, a model of a multiply connected region with obstacles of the “city blocks” type is constructed and the behavior of the characteristics of dynamic graphs located in such domains is studied. A probabilistic approach to the study of graphs is proposed, in which their characteristics are considered as random processes. For graphs of different scales, dependences of the connectivity probability, the number of components on the parameters of a multiply connected region, and the radius of stable signal reception / transmission were found. The mathematical expectation of the number of components in the starting random geometric graph is found. The significant influence not only of geometrical parameters, but also of the topological characteristics of a multiply-connected domain has been revealed. Graphs of changes in the probability of connectedness of a dynamic graph over time are constructed on the basis of calculating the average value over the set of realizations of the random process of moving network nodes. They are characterized by a periodic component that correlates with the structure of a multiply connected region, and a component that exponentially decreases with time. The dependence of the probability of connectedness of the graph on the direction of the network displacement vector was studied, which turned out to be very significant. The results obtained give an idea of the influence of a multiply-connected domain on the dynamics of graphs, and can be used in control algorithms for mobile distributed systems to ensure their spatial connectivity.

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Zhang, Qi, Jianlong Chang, Gaofeng Meng, Shiming Xiang y Chunhong Pan. "Spatio-Temporal Graph Structure Learning for Traffic Forecasting". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 01 (3 de abril de 2020): 1177–85. http://dx.doi.org/10.1609/aaai.v34i01.5470.

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As an indispensable part in Intelligent Traffic System (ITS), the task of traffic forecasting inherently subjects to the following three challenging aspects. First, traffic data are physically associated with road networks, and thus should be formatted as traffic graphs rather than regular grid-like tensors. Second, traffic data render strong spatial dependence, which implies that the nodes in the traffic graphs usually have complex and dynamic relationships between each other. Third, traffic data demonstrate strong temporal dependence, which is crucial for traffic time series modeling. To address these issues, we propose a novel framework named Structure Learning Convolution (SLC) that enables to extend the traditional convolutional neural network (CNN) to graph domains and learn the graph structure for traffic forecasting. Technically, SLC explicitly models the structure information into the convolutional operation. Under this framework, various non-Euclidean CNN methods can be considered as particular instances of our formulation, yielding a flexible mechanism for learning on the graph. Along this technical line, two SLC modules are proposed to capture the global and local structures respectively and they are integrated to construct an end-to-end network for traffic forecasting. Additionally, in this process, Pseudo three Dimensional convolution (P3D) networks are combined with SLC to capture the temporal dependencies in traffic data. Extensively comparative experiments on six real-world datasets demonstrate our proposed approach significantly outperforms the state-of-the-art ones.

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Jha, Lipika y K. S. Patnaik. "A New Method to Compute Dynamic Slicing using Program Dependence Graph". International Journal of Computer Applications 75, n.º 13 (23 de agosto de 2013): 30–36. http://dx.doi.org/10.5120/13173-0852.

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Deptuła, Adam, Józef Drewniak y Marian A. Partyka. "Analysis of a planetary gear modeled with a contour graph taking into account the method of parametric play structures". Mechanik 90, n.º 7 (10 de julio de 2017): 640–42. http://dx.doi.org/10.17814/mechanik.2017.7.98.

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Previous applications of the graph theory concerned the modeling of gears for dynamic analysis, kinematic analysis, synthesis, structural analysis, gearshift optimization and automatic design based on so-called graph grammars. Some tasks can be performed only by using methods resulting from a graph theory, e.g. enumeration of structural solutions. The contour plot method consists in distinguishing a series of consecutive rigid units of the mechanism, forming a closed loop (so-called contour). At a later stage, it is possible to analyze the obtained contour graph as a directed graph of dependence. The work presents an example of the use of game-tree structures for describing the contour graph of a planetary gear. As a result of the decomposition of the graph in the dependence on each of the vertices, game-tree structures are obtained, which allow calculate algorithmically.

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DEPTUŁA, Adam y Marian PARTYKA. "SIMILARITIES AND DIFFERENCES OF COMPLEX PARAMETRIC GAME TREES FOR INVESTIGATIONS OF DYNAMIC PROPERTIES OF MACHINE SYSTEMS". Scientific Journal of the Military University of Land Forces 165, n.º 3 (1 de julio de 2012): 314–25. http://dx.doi.org/10.5604/01.3001.0002.3506.

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The paper concerns the application of dependence graphs and game tree-structures for the analysis and synthesis of the dynamic properties of machine systems. Graph distributions starting from various beginning vertices are presented in this paper. In order to illustrate the acceptable subsystems of parent machine system, similarities and differences between complex parametric trees are also given. It is also possible to find the part common to all the game tree-structures and describe it over separate design or operational parameters.

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Xia, Tong, Junjie Lin, Yong Li, Jie Feng, Pan Hui, Funing Sun, Diansheng Guo y Depeng Jin. "3DGCN: 3-Dimensional Dynamic Graph Convolutional Network for Citywide Crowd Flow Prediction". ACM Transactions on Knowledge Discovery from Data 15, n.º 6 (28 de junio de 2021): 1–21. http://dx.doi.org/10.1145/3451394.

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Crowd flow prediction is an essential task benefiting a wide range of applications for the transportation system and public safety. However, it is a challenging problem due to the complex spatio-temporal dependence and the complicated impact of urban structure on the crowd flow patterns. In this article, we propose a novel framework, 3- D imensional G raph C onvolution N etwork (3DGCN), to predict citywide crowd flow. We first model it as a dynamic spatio-temporal graph prediction problem, where each node represents a region with time-varying flows, and each edge represents the origin–destination (OD) flow between its corresponding regions. As such, OD flows among regions are treated as a proxy for the spatial interactions among regions. To tackle the complex spatio-temporal dependence, our proposed 3DGCN can model the correlation among graph spatial and temporal neighbors simultaneously. To learn and incorporate urban structures in crowd flow prediction, we design the GCN aggregator to be learned from both crowd flow prediction and region function inference at the same time. Extensive experiments with real-world datasets in two cities demonstrate that our model outperforms state-of-the-art baselines by 9.6%∼19.5% for the next-time-interval prediction.

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DJAMEGNI, CLÉMENTIN TAYOU y MAURICE TCHUENTE. "A NEW ALGORITHM FOR DYNAMIC PROGRAMMING ON REGULAR ARRAYS". Parallel Processing Letters 10, n.º 01 (marzo de 2000): 15–27. http://dx.doi.org/10.1142/s0129626400000044.

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Given the real entries w(i, j), 1≤ i < j ≤n, and c(i, i+1), 1≤ i< n, the dynamic programming problem studied here consists of computing the coefficients c ( i , j )= w ( i , j ) + min i < k < j { c ( i , k )+ c ( k , j )}, for 1≤ i< j≤n. We show that this problem can be solved in optimal time T*=2n-1 on a regular array of size n 2/10+ O ( n ). The number of processors required by this new algorithm improves the best previously known bound n 2/10+ O ( n ). The idea introduced here is to apply to the dependence graph associated with the problem a pre-processing that removes long-range communications in order to obtain a new locally connected graph which is suitable for the application of powerful allocation techniques.

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Zhang, Yihe, Sheng Zhang, Jaime S. Ide, Sien Hu, Simon Zhornitsky, Wuyi Wang, Guozhao Dong, Xiaoying Tang y Chiang-shan R. Li. "Dynamic network dysfunction in cocaine dependence: Graph theoretical metrics and stop signal reaction time". NeuroImage: Clinical 18 (2018): 793–801. http://dx.doi.org/10.1016/j.nicl.2018.03.016.

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Alhasan, Abu Mohamed. "Spatiotemporal Graph Imaging Associated with Multilevel Atomic Excitations". Proceedings 67, n.º 1 (11 de noviembre de 2020): 16. http://dx.doi.org/10.3390/asec2020-07886.

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In this paper, we establish a graph imaging technique to manifest local stabilization within atomic systems of multiple levels. Specifically, we address the interrelation between local stabilization and image entropy. As an example, we consider the mutual interaction of two pair of pulses propagating in a double-Λ configuration. Thus, we have two different sets of two pulses that share the same shape and phase, initially. The first (second) set belongs to lower (upper) -Λ subsystems, respectively. The configuration of two pair of pulses is considered as a dynamical graph model with four nodes. The dynamic transition matrix describes the connectivity matrix in the static graph model. It is to be emphasized that the graph and its image have the same transition matrix. In particular, the graph model exposes the stabilization in terms of the singular-value decomposition of energies for the transition matrix, that is, irrespectively of the structure of the transition matrix. The image model of the graph displays the details of the matrix structure in terms of row and column probabilities. Therefore, it enables one to study conditional probabilities and mutual information inherent in the network of the graph. Furthermore, the graph imaging provides the main row/column contribution to the transition matrix in terms of image entropy. Our results show that image entropy exposes spatial dependence, which is irrelevant to graph entropy.

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Belaid, Ikbel, Fabrice Muller y Maher Benjemaa. "Static Scheduling of Periodic Hardware Tasks with Precedence and Deadline Constraints on Reconfigurable Hardware Devices". International Journal of Reconfigurable Computing 2011 (2011): 1–28. http://dx.doi.org/10.1155/2011/591983.

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Task graph scheduling for reconfigurable hardware devices can be defined as finding a schedule for a set of periodic tasks with precedence, dependence, and deadline constraints as well as their optimal allocations on the available heterogeneous hardware resources. This paper proposes a new methodology comprising three main stages. Using these three main stages, dynamic partial reconfiguration and mixed integer programming, pipelined scheduling and efficient placement are achieved and enable parallel computing of the task graph on the reconfigurable devices by optimizing placement/scheduling quality. Experiments on an application of heterogeneous hardware tasks demonstrate an improvement of resource utilization of 12.45% of the available reconfigurable resources corresponding to a resource gain of 17.3% compared to a static design. The configuration overhead is reduced to 2% of the total running time. Due to pipelined scheduling, the task graph spanning is minimized by 4% compared to sequential execution of the graph.

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Tesis sobre el tema "Dynamic dependence graph"

Pogulis, Jakob. "Generation of dynamic control-dependence graphs for binary programs". Thesis, Linköpings universitet, Databas och informationsteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-110247.

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Dynamic analysis of binary files is an area of computer science that has many purposes. It is useful when it comes to debugging software in a development environment and the developer needs to know which statements affected the value of a specific variable. But it is also useful when analyzing a software for potential vulnerabilities, where data controlled by a malicious user could potentially result in the software executing adverse commands or executing malicious code. In this thesis a tool has been developed to perform dynamic analysis of x86 binaries in order to generate dynamic control-dependence graphs over the execution. These graphs can be used to determine which conditional statements that resulted in a certain outcome. The tool has been developed for x86 Linux systems using the dynamic binary instrumentation framework PIN, developed and maintained by Intel. Techniques for utilizing the additional information about the control flow for a program available during the dynamic analysis in order to improve the control flow information have been implemented and tested. The basic theory of dynamic analysis as well as dynamic slicing is discussed, and a basic overview of the implementation of a dynamic analysis tool is presented. The impact on the performance of the dynamic analysis tool for the techniques used to improve the control flow graph is significant, but approaches to improving the performance are discussed.

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Singh, Saurabh. "Characterizing applications by integrating andimproving tools for data locality analysis and programperformance". The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1492741656429829.

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Singh, Shashank. "Scalable Analysis of Large Dynamic Dependence Graphs". The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1431093345.

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Jhally, Gaganjit Singh. "Sampling of Dynamic Dependence Graphs for Data Locality Analysis". The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1462885420.

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Axelsson, Nils. "Dynamic Programming Algorithms for Semantic Dependency Parsing". Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138594.

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Dependency parsing can be a useful tool to allow computers to parse text. In 2015, Kuhlmann and Jonsson proposed a logical deduction system that parsed to non-crossing dependency graphs with an asymptotic time complexity of O(n3), where “n” is the length of the sentence to parse. This thesis extends the deduction system by Kuhlmann and Jonsson; the extended deduction system introduces certain crossing edges, while maintaining an asymptotic time complexity of O(n4). In order to extend the deduction system by Kuhlmann and Jonsson, fifteen logical item types are added to the five proposed by Kuhlmann and Jonsson. These item types allow the deduction system to intro-duce crossing edges while acyclicity can be guaranteed. The number of inference rules in the deduction system is increased from the 19 proposed by Kuhlmann and Jonsson to 172, mainly because of the larger number of combinations of the 20 item types. The results are a modest increase in coverage on test data (by roughly 10% absolutely, i.e. approx. from 70% to 80%), and a comparable placement to that of Kuhlmann and Jonsson by the SemEval 2015 task 18 metrics. By the method employed to introduce crossing edges, derivational uniqueness is impossible to maintain. It is hard to defien the graph class to which the extended algorithm, QAC, parses, and it is therefore empirically compared to 1-endpoint crossing and graphs with a page number of two or less, compared to which it achieves lower coverage on test data. The QAC graph class is not limited by page number or crossings. The takeaway of the thesis is that extending a very minimal deduction system is not necessarily the best approach, and that it may be better to start off with a strong idea of to which graph class the extended algorithm should parse. Additionally, several alternative ways of extending Kuhlmann and Jonsson are proposed.
Dependensparsning kan vara ett användbart verktyg för att få datorer att kunna läsa text. Kuhlmann och Jonsson kom 2015 fram till ett logiskt deduktionssystem som kan parsa till ickekorsande grafer med en asymptotisk tidskomplexitet O(n3), där "n" är meningens som parsas längd. Detta arbete utökar Kuhlmann och Jonssons deduktionssystem så att det kan introducera vissa korsande bågar, medan en asymptotisk tidskomplexitet O(n4) uppnås. För att tillåta deduktionssystemet att introducera korsande bågar, introduceras 15 nya logiska delgrafstyper, eller item. Dessa item-typer tillåter deduktionssystemet att introducera korsande bågar på ett sådant sätt att acyklicitet bibehålls. Antalet logiska inferensregler tags från Kuhlmanns och Jonssons 19 till 172, på grund av den större mängden kombinationer av de nu 20 item-typerna. Resultatet är en mindre ökning av täckning på testdata (ungefär 10 procentenheter, d v s från cirka 70% till 80%), och jämförbar placering med Kuhlmann och Jonsson enligt måtten från uppgift 18 från SemEval 2015. Härledningsunikhet kan inte garanteras på grund av hur bågar introduceras i det nya deduktionssystemet. Den utökade algoritmen, QAC, parsar till en svårdefinierad grafklass, som jämförs empiriskt med 1-endpoint-crossing-grafer och grafer med pagenumber 2 eller mindre. QAC:s grafklass har lägre täckning än båda dessa, och har ingen högre gräns i pagenumber eller antal korsningar. Slutsatsen är att det inte nödvändigtvis är optimalt att utöka ett mycket minimalt och specifikt deduktionssystem, och att det kan vara bättre att inleda processen med en specifik grafklass i åtanke. Dessutom föreslås flera alternativa metoder för att utöka Kuhlmann och Jonsson.

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Zhu, Xiaoyan. "The dynamic, resource-constrained shortest path problem on an acyclic graph with application in column generation and literature review on sequence-dependent scheduling". Texas A&M University, 2005. http://hdl.handle.net/1969.1/4996.

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This dissertation discusses two independent topics: a resource-constrained shortest-path problem (RCSP) and a literature review on scheduling problems involving sequence-dependent setup (SDS) times (costs). RCSP is often used as a subproblem in column generation because it can be used to solve many practical problems. This dissertation studies RCSP with multiple resource constraints on an acyclic graph, because many applications involve this configuration, especially in column genetation formulations. In particular, this research focuses on a dynamic RCSP since, as a subproblem in column generation, objective function coefficients are updated using new values of dual variables at each iteration. This dissertation proposes a pseudo-polynomial solution method for solving the dynamic RCSP by exploiting the special structure of an acyclic graph with the goal of effectively reoptimizing RCSP in the context of column generation. This method uses a one-time Ã¢ÂÂpreliminaryÃ¢ÂÂ phase to transform RCSP into an unconstrained shortest path problem (SPP) and then solves the resulting SPP after new values of dual variables are used to update objective function coefficients (i.e., reduced costs) at each iteration. Network reduction techniques are considered to remove some nodes and/or arcs permanently in the preliminary phase. Specified techniques are explored to reoptimize when only several coefficients change and for dealing with forbidden and prescribed arcs in the context of a column generation/branch-and-bound approach. As a benchmark method, a label-setting algorithm is also proposed. Computational tests are designed to show the effectiveness of the proposed algorithms and procedures. This dissertation also gives a literature review related to the class of scheduling problems that involve SDS times (costs), an important consideration in many practical applications. It focuses on papers published within the last decade, addressing a variety of machine configurations - single machine, parallel machine, flow shop, and job shop - reviewing both optimizing and heuristic solution methods in each category. Since lot-sizing is so intimately related to scheduling, this dissertation reviews work that integrates these issues in relationship to each configuration. This dissertation provides a perspective of this line of research, gives conclusions, and discusses fertile research opportunities posed by this class of scheduling problems. since, as a subproblem in column generation, objective function coefficients are updated using new values of dual variables at each iteration. This dissertation proposes a pseudo-polynomial solution method for solving the dynamic RCSP by exploiting the special structure of an acyclic graph with the goal of effectively reoptimizing RCSP in the context of column generation. This method uses a one-time

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Al-Hasani, Firas Ali Jawad. "Multiple Constant Multiplication Optimization Using Common Subexpression Elimination and Redundant Numbers". Thesis, University of Canterbury. Electrical and Computer Engineering, 2014. http://hdl.handle.net/10092/9054.

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The multiple constant multiplication (MCM) operation is a fundamental operation in digital signal processing (DSP) and digital image processing (DIP). Examples of the MCM are in finite impulse response (FIR) and infinite impulse response (IIR) filters, matrix multiplication, and transforms. The aim of this work is minimizing the complexity of the MCM operation using common subexpression elimination (CSE) technique and redundant number representations. The CSE technique searches and eliminates common digit patterns (subexpressions) among MCM coefficients. More common subexpressions can be found by representing the MCM coefficients using redundant number representations. A CSE algorithm is proposed that works on a type of redundant numbers called the zero-dominant set (ZDS). The ZDS is an extension over the representations of minimum number of non-zero digits called minimum Hamming weight (MHW). Using the ZDS improves CSE algorithms' performance as compared with using the MHW representations. The disadvantage of using the ZDS is it increases the possibility of overlapping patterns (digit collisions). In this case, one or more digits are shared between a number of patterns. Eliminating a pattern results in losing other patterns because of eliminating the common digits. A pattern preservation algorithm (PPA) is developed to resolve the overlapping patterns in the representations. A tree and graph encoders are proposed to generate a larger space of number representations. The algorithms generate redundant representations of a value for a given digit set, radix, and wordlength. The tree encoder is modified to search for common subexpressions simultaneously with generating of the representation tree. A complexity measure is proposed to compare between the subexpressions at each node. The algorithm terminates generating the rest of the representation tree when it finds subexpressions with maximum sharing. This reduces the search space while minimizes the hardware complexity. A combinatoric model of the MCM problem is proposed in this work. The model is obtained by enumerating all the possible solutions of the MCM that resemble a graph called the demand graph. Arc routing on this graph gives the solutions of the MCM problem. A similar arc routing is found in the capacitated arc routing such as the winter salting problem. Ant colony optimization (ACO) meta-heuristics is proposed to traverse the demand graph. The ACO is simulated on a PC using Python programming language. This is to verify the model correctness and the work of the ACO. A parallel simulation of the ACO is carried out on a multi-core super computer using C++ boost graph library.

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"A Study of Backward Compatible Dynamic Software Update". Doctoral diss., 2015. http://hdl.handle.net/2286/R.I.36032.

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abstract: Dynamic software update (DSU) enables a program to update while it is running. DSU aims to minimize the loss due to program downtime for updates. Usually DSU is done in three steps: suspending the execution of an old program, mapping the execution state from the old program to a new one, and resuming execution of the new program with the mapped state. The semantic correctness of DSU depends largely on the state mapping which is mostly composed by developers manually nowadays. However, the manual construction of a state mapping does not necessarily ensure sound and dependable state mapping. This dissertation presents a methodology to assist developers by automating the construction of a partial state mapping with a guarantee of correctness. This dissertation includes a detailed study of DSU correctness and automatic state mapping for server programs with an established user base. At first, the dissertation presents the formal treatment of DSU correctness and the state mapping problem. Then the dissertation presents an argument that for programs with an established user base, dynamic updates must be backward compatible. The dissertation next presents a general definition of backward compatibility that specifies the allowed changes in program interaction between an old version and a new version and identified patterns of code evolution that results in backward compatible behavior. Thereafter the dissertation presents formal definitions of these patterns together with proof that any changes to programs in these patterns will result in backward compatible update. To show the applicability of the results, the dissertation presents SitBack, a program analysis tool that has an old version program and a new one as input and computes a partial state mapping under the assumption that the new version is backward compatible with the old version. SitBack does not handle all kinds of changes and it reports to the user in incomplete part of a state mapping. The dissertation presents a detailed evaluation of SitBack which shows that the methodology of automatic state mapping is promising in deal with real world program updates. For example, SitBack produces state mappings for 17-75% of the changed functions. Furthermore, SitBack generates automatic state mapping that leads to successful DSU. In conclusion, the study presented in this dissertation does assist developers in developing state mappings for DSU by automating the construction of state mappings with a correctness guarantee, which helps the adoption of DSU ultimately.
Dissertation/Thesis
Doctoral Dissertation Computer Science 2015

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Libros sobre el tema "Dynamic dependence graph"

Vladas, Sidoravicius y Smirnov S. (Stanislav) 1970-, eds. Probability and statistical physics in St. Petersburg: St. Petersburg School in Probability and Statistical Physics : June 18-29, 2012 : St. Petersburg State University, St. Petersburg, Russia. Providence, Rhode Island: American Mathematical Society, 2015.

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Capítulos de libros sobre el tema "Dynamic dependence graph"

Yeolekar, Anand. "Improving Dynamic Inference with Variable Dependence Graph". En Runtime Verification, 301–6. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11164-3_25.

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Xie, Wenhao, Shuxin Wang, Yanzhi Wei, Yonglin Zhao y Xianghua Fu. "Dynamic Knowledge Graph Completion with Jointly Structural and Textual Dependency". En Algorithms and Architectures for Parallel Processing, 432–48. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60239-0_29.

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Wasserrab, Daniel y Andreas Lochbihler. "Formalizing a Framework for Dynamic Slicing of Program Dependence Graphs in Isabelle/HOL". En Lecture Notes in Computer Science, 294–309. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-71067-7_24.

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Wu, Tianjun y Yuexiang Yang. "AppWalker: Efficient and Accurate Dynamic Analysis of Apps via Concolic Walking Along the Event-Dependency Graph". En Lecture Notes in Computer Science, 85–94. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49145-5_9.

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Meddeber, Meriem y Belabbas Yagoubi. "Dynamic Dependent Tasks Assignment for Grid Computing". En Applications and Developments in Grid, Cloud, and High Performance Computing, 58–73. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2065-0.ch004.

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A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management. Task assignment as a part of resource management has a considerable effect on the grid middleware performance. In grid computing, task execution time is dependent on the machine to which it is assigned, and task precedence constraints are represented by a directed acyclic graph. This paper proposes a hybrid assignment strategy of dependent tasks in Grids which integrate static and dynamic assignment technologies. Grid computing is considered a set of clusters formed by a set of computing elements and a cluster manager. The main objective is to arrive at a method of task assignment that could achieve minimum response time and reduce the transfer cost, inducing by the tasks transfer respecting the dependency constraints.

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Meddeber, Meriem y Belabbas Yagoubi. "Dynamic Dependent Tasks Assignment for Grid Computing". En Grid and Cloud Computing, 551–65. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0879-5.ch301.

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Trappenberg, Thomas P. "Cyclic models and recurrent neural networks". En Fundamentals of Machine Learning, 183–205. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198828044.003.0009.

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This chapter discusses models with cyclic dependencies. There are two principle architectures that are discussed. The first principle architecture of cyclic graphs comprises directed graphs similar to the Bayesian networks except that they include loops. Formally, such networks represent dynamical systems in the wider context and therefore represent some form of temporal modeling. The second type of models have connections between neurons that are bi-directional. These types of networks will be discussed in the context of stochastic units in the second half of this chapter.

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"Pacific Salmon Environmental and Life History Models: Advancing Science for Sustainable Salmon in the Future". En Pacific Salmon Environmental and Life History Models: Advancing Science for Sustainable Salmon in the Future, editado por Peter Fritz Baker. American Fisheries Society, 2009. http://dx.doi.org/10.47886/9781934874097.ch10.

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<em>Abstract.</em>—The basic idea of stock-production theory is to regard a cohort of organisms at some life stage as a function of a corresponding cohort at some earlier life stage (a “stock-production relationship”). Stock-production relations were originally introduced for theoretical purposes, to clarify the role of density-dependence in population dynamics, but have been found to be useful in the construction of concrete models for specific populations. This chapter discusses generalizations of the stock-production approach which greatly extend its range of applicability. First, it is observed that the appropriate language for describing life-histories is that of periodic directed acyclic graphs. In the present formulation, population dynamics are regarded as processes on such graphs. Second, whereas it is customary to represent a cohort at a life stage by a single number, such as the number of individuals or total biomass, it is often important to keep track of additional information, such as age structure or spatial distribution. This can be done by using objects of more complex mathematical type, such as vectors, sets, or statistical distributions, in place of simple numbers. Theoretical and practical issues involved in implementing models with this architecture, relationships with other approaches such as individual-based models (IBM), and opportunities this general framework presents for smoothly and flexibly integrating disparate methodologies, are discussed.

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Ali, Ihtisham y Susmit Bagchi. "A Comparative Study and Algorithmic Analysis of Workflow Decomposition in Distributed Systems". En Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing, 2282–315. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5339-8.ch112.

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Workflow is an essential mechanism for the automation of processes in distributed transactional systems, including mobile distributed systems. The workflow modeling enables the composition of process activities along with respective conditions, data flow and control flow dependencies. The workflow partitioning methods are used to create sub-partitions by grouping processes on the basis of activities, data flow and control flow dependencies. Mobile distributed systems consisting of heterogeneous computing devices require optimal workflow decomposition. In general, the workflow partitioning is a NP-complete problem. This article presents a comparative study and detailed analysis of workflow decomposition techniques based on graphs, petri nets and topological methods. A complete taxonomy of the basic decomposition techniques is presented. A detailed qualitative and quantitative analysis of these decomposition techniques are explained. The comparative analysis presented in this article provides an insight to inherent algorithmic complexities of respective decomposition approaches. The qualitative parametric analysis would help in determining the suitability of workflow applicability in different computing environments involving static and dynamic nodes. Furthermore, the authors have presented a novel framework for workflow decomposition based on multiple parametric parameters for mobile distributed systems.

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Zhang, K. y D. Shasha. "Tree Pattern Matching". En Pattern Matching Algorithms. Oxford University Press, 1997. http://dx.doi.org/10.1093/oso/9780195113679.003.0014.

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Most of this book is about stringology, the study of strings. So why this chapter on trees? Why not graphs or geometry or something else? First, trees generalize strings in a very direct sense: a string is simply a tree with a single leaf. This has the unsurprising consequence that many of our algorithms specialize to strings and the happy consequence that some of those algorithms are as efficient as the best string algorithms. From the point of view of “treeology”, there is the additional pragmatic advantage of this relationship between trees and strings: some techniques from strings carry over to trees, e.g., suffix trees, and others show promise though we don’t know of work that exploits it. So, treeology provides a good example area for applications of stringologic techniques. Second, some of our friends in stringology may wonder whether there is some easy reduction that can take any tree edit problem, map it to strings, solve it in the string domain and then map it back. We don’t believe there is, because, as you will see, tree editing seems inherently to have more data dependence than string editing. (Specifically, the dynamic programming approach to string editing is always a local operation depending on the left, upper, and upper left neighbor of a cell. In tree editing, the upper left neighbor is usually irrelevant — instead the relevant cell depends on the tree topology.) That is a belief not a theorem, so we would like to state right at the outset the key open problem of treeology: can all tree edit problems on ordered trees (trees where the order among the siblings matters) be reduced efficiently to string edit problems and back again?. The rest of this chapter proceeds on the assumption that this question has a negative response. In particular, we discuss the best known algorithms for tree editing and several variations having to do with subtree removal, variable length don’t cares, and alignment. We discuss both sequential and parallel algorithms.

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Actas de conferencias sobre el tema "Dynamic dependence graph"

Beszedes, Arpad, Tamas Gergely y Tibor Gyimothy. "Graph-Less Dynamic Dependence-Based Dynamic Slicing Algorithms". En 2006 Sixth IEEE International Workshop on Source Code Analysis and Manipulation. IEEE, 2006. http://dx.doi.org/10.1109/scam.2006.17.

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Zhou, Xiaoming, Xingming Sun, Guang Sun y Ying Yang. "A Combined Static and Dynamic Software Birthmark Based on Component Dependence Graph". En 2008 Fourth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP). IEEE, 2008. http://dx.doi.org/10.1109/iih-msp.2008.145.

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Garg, Sankalp, Navodita Sharma, Woojeong Jin y Xiang Ren. "Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution". En Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/386.

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Time series prediction is an important problem in machine learning. Previous methods for time series prediction did not involve additional information. With a lot of dynamic knowledge graphs available, we can use this additional information to predict the time series better. Recently, there has been a focus on the application of deep representation learning on dynamic graphs. These methods predict the structure of the graph by reasoning over the interactions in the graph at previous time steps. In this paper, we propose a new framework to incorporate the information from dynamic knowledge graphs for time series prediction. We show that if the information contained in the graph and the time series data are closely related, then this inter-dependence can be used to predict the time series with improved accuracy. Our framework, DArtNet, learns a static embedding for every node in the graph as well as a dynamic embedding which is dependent on the dynamic attribute value (time-series). Then it captures the information from the neighborhood by taking a relation specific mean and encodes the history information using RNN. We jointly train the model link prediction and attribute prediction. We evaluate our method on five specially curated datasets for this problem and show a consistent improvement in time series prediction results. We release the data and code of model DArtNet for future research.

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Hammer, Christian, Martin Grimme y Jens Krinke. "Dynamic path conditions in dependence graphs". En the 2006 ACM SIGPLAN symposium. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1111542.1111552.

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Minh Le, Thao, Vuong Le, Svetha Venkatesh y Truyen Tran. "Dynamic Language Binding in Relational Visual Reasoning". En Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/114.

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We present Language-binding Object Graph Network, the first neural reasoning method with dynamic relational structures across both visual and textual domains with applications in visual question answering. Relaxing the common assumption made by current models that the object predicates pre-exist and stay static, passive to the reasoning process, we propose that these dynamic predicates expand across the domain borders to include pair-wise visual-linguistic object binding. In our method, these contextualized object links are actively found within each recurrent reasoning step without relying on external predicative priors. These dynamic structures reflect the conditional dual-domain object dependency given the evolving context of the reasoning through co-attention. Such discovered dynamic graphs facilitate multi-step knowledge combination and refinements that iteratively deduce the compact representation of the final answer. The effectiveness of this model is demonstrated on image question answering demonstrating favorable performance on major VQA datasets. Our method outperforms other methods in sophisticated question-answering tasks wherein multiple object relations are involved. The graph structure effectively assists the progress of training, and therefore the network learns efficiently compared to other reasoning models.

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Malburg, Jan, Tino Flenker y Gorschwin Fey. "Property mining using dynamic dependency graphs". En 2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC). IEEE, 2017. http://dx.doi.org/10.1109/aspdac.2017.7858327.

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Lonnberg, Jan, Mordechai Ben-Ari y Lauri Malmi. "Visualising concurrent programs with dynamic dependence graphs". En 2011 6th IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT). IEEE, 2011. http://dx.doi.org/10.1109/vissof.2011.6069456.

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Sun, Tong y John Walker. "Hierarchical Dependence Graphs for Dynamic JDF Workflows". En 2006 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icsmc.2006.385289.

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Popov, Anton I., Igor Y. Popov, Dmitri S. Nikiforov y Irina V. Blinova. "Time-dependent metric graph: Wave dynamics". En CENTRAL EUROPEAN SYMPOSIUM ON THERMOPHYSICS 2019 (CEST). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5114299.

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Mak, Jonathan y Alan Mycroft. "Limits of parallelism using dynamic dependency graphs". En the Seventh International Workshop. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/2134243.2134253.

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Informes sobre el tema "Dynamic dependence graph"

Miller, Allan. Nonpreemptive run-time scheduling issues on a multitasked, multiprogrammed multiprocessor with dependencies, bidimensional tasks, folding and dynamic graphs. Office of Scientific and Technical Information (OSTI), mayo de 1987. http://dx.doi.org/10.2172/5546139.

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