Kcore decomposition of large networks on a single pc. Decomposition techniques in mathematical programming. The proposed algorithms exploit, as much as possible, the topology of the graph to compute all the k cores and maintain them in streaming settings where edge. These nodes are then said to belong to the kth shell. Kcore decomposition of large networks on a single pc vldb. The innermost shell k max, or the core of the network, contains the nodes with the highest degree. Jan 01, 2021 the k core decomposition and algorithms for finding densest subgraphs have proved to be a valuable tool in graph mining and data analysis, with applications encompassing sociology, bioinformatics as well as graph visualization. We present the first distributed and the first streaming algorithms to compute and maintain an approximate kcore decomposition with provable guarantees. It has influenced the microservices architecture by decomposing the systems into distributed. A hierarchical model of metabolic machinery based on the. The main purpose of this report is to explore a distributed algorithm for kcore decomposition on apache giraph. Distributed kcore decomposition and maintenance in large dynamic. Applications in complex networks dense subgraph discovery community detection and evaluation identi. Citeseerx document details isaac councill, lee giles, pradeep teregowda.
In graph theory, a kdegenerate graph is an undirected graph in which every subgraph has a. The kcore decomposition algorithm can reveal a central, wellconnected, core of nodes in a graph. In the following, we outline a distributed algorithm for kcore decomposition of a dynamic graph. The kcore decomposition can be used to reveal structure in a graph. We present a continuous, distributed, kcore decomposition algorithm for. Distributed approximate kcore decomposition and minmax. Bootstrap percolation is a random process studied as an epidemic model and as a model for fault tolerance for distributed computing. In this work, under a distributed model underlying pregel and live distributed systems, we present the first known distributed solutions for core decomposition in probabilistic graphs, where there is an. Eric evanss book domaindriven design has deeply influenced modern architectural thinking, and consequently the organizational modeling. Mobile distributed systems consisting of heterogeneous computing devices require optimal workflow decomposition. Michael roger honeycomb decomposition book, yellow cover with black printing, 7. Makers of the decomposition book over 100 styles in stock made with 100% recycled paper printed with soy ink made in the usa.
Ieee transactions on parallel and distributed systems, 242. Namely, we would like to determine whether a clusterbased, giraph implementation of kcore decomposition that. However, known algorithms for kcore graph decomposition are centralised and unsuitable for use in a distributed routing protocol indeed, it is only recently that attention has been given to the kcore decomposition of dynamic graphs 2. This paper initializes distributed algorithm studies for core decomposition in probabilistic graphs.
Distributed kcore decomposition and maintenance in large. Examples include betweenness, eigenvector and closeness centrality indexes 5,10. This dissertation will follow the notation primarily of the following books. Efficient algorithms to compute k cores exist already, both in centralized and decentralized setting. Distributed kcore decomposition ieee transactions on. A comparative study and algorithmic analysis of workflow. Ipdps represents a unique international gathering of computer scientists from. We present the first distributed and the first streaming algorithms to compute and main tain an approximate k core decomposition with provable guarantees. We present the first distributed and the first streaming. This article presents a comparative study and detailed analysis of workflow decomposition techniques based on graphs, petri nets and topological methods. Among those, kcoreness has found a number of applications in areas as diverse as sociology, proteinomics, graph visualization, and distributed system analysis and design. Hubert chan university of hong kong, mauro sozio telecom paristech, and bintao sun university of hong kong wednesday panel at ipdps 2019. In the case where the large graph resides on a single machines disk, resorting to the distributed approach for kcore decomposition can be. Parallel and streaming algorithms for kcore decomposition.
Finally, the opinion leaders identified are applied to the following clustering based consensus model in lsgdm. It operates on the premise that the input graph is spread across. Breaking the diameter barrier by th chan, mauro sozio and bintao sun get pdf 755 kb. Distributed core decomposition in probabilistic graphs. Mar 28, 2011 among the novel metrics used to study the relative importance of nodes in complex networks, kcore decomposition has found a number of applications in areas as diverse as sociology, proteinomics, graph visualization, and distributed system analysis and design. A distributed kcore decomposition algorithm on spark ieee. Effectiveness of the kcore nodes as seeds for influence. A kcore of a graph g is a maximal connected subgraph of g in which all vertices have degree at least k. A distributed kcore decomposition algorithm on spark aritra mandal, mohammad al hasan, in proceedings of the 2017 ieee international conference on big.
Introductionin the last few years, a number of metrics and methods have been introduced for studying the relative importance of nodes within complex network structures. Distributed approximate kcore decomposition and minmax edge. Recently, distributed processing of large dynamic graphs has become very popular, especially in certain domains such as social network analysis, web graph analysis and spatial network analysis. Dec 10, 2012 the kcore decomposition can be used to reveal structure in a graph. Whether one examines ecological networks 1 3, financial networks 4 7, social networks 8, 9, neural networks 10, 11, or beyond, the identification of the features of these networks that characterise their robustness and resilience against external shocks is an important problem in network science today. It is straightforward to implement using a centralised algorithm with complete knowledge of the graph, but no distributed kcore decomposition algorithm has been published. Index terms distributed algorithms, coreness, round complexity i. The experimental results show that the performance and scalability of bladyg are satisfying for largescale dynamic graphs. Section 4 introduces several new algorithms for incremental maintenance of a graphs kcore decomposition. Core decomposition has been proven to be a useful primitive for a wide range of graph analyses, but it has been rarely studied in probabilistic graphs, especially in a distributed environment. By paul jakma, hewlett packard enterprise, colin s perkins, paul jakma, marcin orczyk, colin perkins and marwan fayed. In proceedings of the 30th annual acm sigactsigops symposium on principles of distributed computing, podc 11, pages 207208, new york, ny, usa, 2011. Abstract and figures among the novel metrics used to study the relative importance of nodes in complex networks, kcore decomposition has found a number of applications in areas as diverse as. The kcore decomposition is a fundamental primitive in many machine learning and data mining applications.
This has led to interest in distributed algorithms for graph decomposition. Distributed k core decompositionseveral novel metrics have been proposed in recent literature in order to. The degeneracy of a graph is the smallest value of k for which it is kdegenerate. Algorithmour distributed algorithm is based on the property of locality of the kcore decomposition. The network shown here has undergone the kshell decomposition described above. Distributed graph processing, dynamic graphs, akka framework, graph partitioning, kcore decomposition. Pdf distributed kcore decomposition francesco pellegrini. This paper proposes new distributed algorithms for the computation of the kcore decomposition of a network, with the purpose of i enabling the runtime computation of kcores in live distributed systems and ii allowing the decomposition, over a set of connected machines, of very large graphs, that cannot be hosted in a single machine. Efficient algorithms to compute kcores exist already.
This is an implementation with optimizations of the algorithm in. Ipdps is an international forum for engineers and scientists from around the world to present their latest research findings in all aspects of parallel computation. Core decomposition, maintenance and applications springerlink. May 20, 2019 data and distributed domain driven architecture convergence domain oriented data decomposition and ownership. We continually work to add attractive, useful, welldesigned and earthfriendly products to our growing line, which evolves on a regular basis. This method assigns an index k s to each node, which is the rank of the node in the network, according to its importance. A kcore layer is the maximal subgraph obtained by recursively removing all nodes with a degree lower than k until all nodes in the remaining graph have a degree larger than or equal to k 11, 12. Among the novel metrics used to study the relative importance of nodes in complex networks, kcore decomposition has found a number of applications in areas as diverse as sociology, proteinomics, graph visualization, and distributed system analysis and design. In this context, many distributed parallel graph processing systems have been proposed, such as pregel, powergraph. They were also more likely to act as connector hubs, having links distributed. A kcore decompositionbased opinion leaders identifying method. The kcore decomposition 9 consists in identifying particular subsets of the graph, called kcores, each one obtained by recursively removing all the. Introduction the kcore decomposition and algorithms for.
This technique 1 allows the decomposition, over a set of connected machines, of very large graphs, when size does not allow storing and processing them on a single host, and 2 enables the runtime. Parallel maximum clique algorithms with applications to. A distributed kcore decomposition algorithm on spark. Theory, algorithms and applications the vldb journal, 2019 fragkiskos d.
Decomposition book is our most recognizable product, but we have expanded the decomposition brand into other stationery categories and beyond. Hadoopbased distributed kshell decomposition for social. Nevertheless, the resolution of kcore decomposition is quite coarse. The kcore decomposition is an algorithm that splits a network into hierarchically ordered substructures see s7 file. Pdf distributed kcore decomposition of dynamic graphs. This paper proposes new distributed algorithms for the computation of the kcoreness of a network, a process also known as kcore decomposition. Nov 18, 2019 this paper initializes distributed algorithm studies for core decomposition in probabilistic graphs. Section 5 provides discussions on implementation details. It operates on the premise that the input graph is spread across multiple cluster nodes or hosts. The kcore of a graph is the maximal subgraph with minimum degree at least k. Dec 14, 2017 a distributed kcore decomposition algorithm on spark abstract. Why peeling kcore and ktruss decomposition algo rithms have been. This paper proposes new distributed algorithms for the computation of the kcoreness of a network, a process also known as k core decomposition.
To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior speci. A kcore of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. Many of the networks to be analysed are large andor geographically distributed. Hadoopbased distributed kshell decomposition for social networks. Thanks to its linear time complexity, kcore decomposition method is scalable to large reallife networks as long as the input graph fits in the main memory. We present a continuous, distributed, kcore decomposition algorithm for dynamic. This paper proposes new distributed algorithms for the computation of the k core decomposition of a network, with the purpose of i enabling. Journal of parallel and distributed computing 106, 7991. Distributed processing of large, dynamic graphs has recently received considerable attention, especially in domains such as the analytics of social networks, web graphs and spatial networks.
All intext references underlined in blue are linked to publications on researchgate, letting. Abstract distributed processing of large, dynamic graphs has recently received considerable attention, especially in domains such as the analytics of social networks, web graphs and spatial networks. They use a thinklikeanode paradigm, and the proposed method uses a messaging paradigm to solve the k nuclear decomposition, which greatly reduces the io cost. A graph processing framework for large dynamic graphs. Simply put, the k core of a graph g is the maximal induced subgraph gk, where the. In this work, we propose distributed kcore decomposition and maintenance algorithms for large dynamic graphs. Distributed algorithm to compute the k core decomposition, executed by.
We demonstrate the s core decomposition approach on two random networks er and configuration model with scalefree degree distribution. Locating influential nodes in complex networks ncbi nih. It consists of selecting a random subset of active cells from a lattice or other space, and then considering the kcore of the induced subgraph of this subset. A comparative study and algorithmic analysis of workflow decomposition in distributed systems. We study three open source java projects over a 10year period and demonstrate, using different metrics, that the kcore decomposition of the network can help. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed. The degeneracy of a graph is a measure of how sparse it is, and is within a constant factor of other sparsity. Kcore robustness in ecological and financial networks. One example is kcore decomposition which captures the degree of connectedness in social graphs. Workflow is an essential mechanism for the automation of processes in distributed transactional systems, including mobile distributed systems.
This paper proposes new distributed algorithms for the computation of the kcore decomposition of a network, with the purpose of i. Fast and scalable distributed tensor decompositions. Distributed kcore decomposition of dynamic graphs core. Distributed kcore decomposition, kcore maintenance, dynamic graphs, akka framework work primarily done while the author was at the university of trento. Statistical models for cores decomposition of an undirected random. Mapreducebased distributed kshell decomposition for online social networks. Apr 24, 2012 distributed kcore decomposition abstract. Efficient algorithms to compute k cores exist already. Complex network analysis comprises a popular set of tools for the analysis of online social networks. We demonstrate that our techniques reduce the overall communication and execution time of tensor decomposition methods when they are used for analyzing datasets of varied size from real application. At each step of the algorithm, nodes with degree equal to or less than k are removed iteratively until none remain. Distributed approximate kcore decomposition and minmax edge orientation.
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