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822
Dense Subgraphs on Dynamic Networks
"... Abstract. In distributed networks, it is often useful for the nodes to be aware of dense subgraphs, e.g., such a dense subgraph could reveal dense subtructures in otherwise sparse graphs (e.g. the World Wide Web or social networks); these might reveal community clusters or dense regions for possibly ..."
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Cited by 2 (0 self)
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for possibly maintaining good communication infrastructure. In this work, we address the problem of selfawareness of nodes in a dynamic network with regards to graph density, i.e., we give distributed algorithms for maintaining dense subgraphs that the member nodes are aware of. The only knowledge
GPSR: Greedy perimeter stateless routing for wireless networks
 MOBICOM
, 2000
"... We present Greedy Perimeter Stateless Routing (GPSR), a novel routing protocol for wireless datagram networks that uses the positions of touters and a packer's destination to make packet forwarding decisions. GPSR makes greedy forwarding decisions using only information about a router's i ..."
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Cited by 2290 (8 self)
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with that of Dynamic Source Routing. Our simulations demonstrate GPSR's scalability on densely deployed wireless networks.
A new approach to the maximum flow problem
 JOURNAL OF THE ACM
, 1988
"... All previously known efficient maximumflow algorithms work by finding augmenting paths, either one path at a time (as in the original Ford and Fulkerson algorithm) or all shortestlength augmenting paths at once (using the layered network approach of Dinic). An alternative method based on the pre ..."
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Cited by 672 (33 self)
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to be shortest paths. The algorithm and its analysis are simple and intuitive, yet the algorithm runs as fast as any other known method on dense. graphs, achieving an O(n³) time bound on an nvertex graph. By incorporating the dynamic tree data structure of Sleator and Tarjan, we obtain a version
ASCENT: Adaptive selfconfiguring sensor networks topologies
, 2004
"... Advances in microsensor and radio technology will enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. The low pernode cost will allow these wireless networks of sensors and actuators to be densely distributed. The nodes in these dense networks w ..."
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Cited by 449 (15 self)
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Advances in microsensor and radio technology will enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. The low pernode cost will allow these wireless networks of sensors and actuators to be densely distributed. The nodes in these dense networks
The Average Distance in a Random Graph with Given Expected Degrees
"... Random graph theory is used to examine the “smallworld phenomenon”– any two strangers are connected through a short chain of mutual acquaintances. We will show that for certain families of random graphs with given expected degrees, the average distance is almost surely of order log n / log ˜ d whe ..."
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Cited by 289 (13 self)
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having some mild constraints for the average distance and maximum degree). In particular, these graphs contain a dense subgraph, that we call the core, having n c / log log n vertices. Almost all vertices are within distance log log n of the core although there are vertices at distance log n from
Criterions for locally dense subgraphs
"... Community detection is one of the most investigated problems in the field of complex networks. Although several methods were proposed, there is still no precise definition of communities. As a step towards a definition, I highlight two necessary properties of communities, separation and internal co ..."
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Community detection is one of the most investigated problems in the field of complex networks. Although several methods were proposed, there is still no precise definition of communities. As a step towards a definition, I highlight two necessary properties of communities, separation and inter
Matched filtering for subgraph detection in dynamic networks
 in Proc. SSP
, 2011
"... Graphs are highdimensional, nonEuclidean data, whose utility spans a wide variety of disciplines. While their nonEuclidean nature complicates the application of traditional signal processing paradigms, it is desirable to seek an analogous detection framework. In this paper we present a matched fi ..."
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Cited by 9 (7 self)
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filtering method for graph sequences, extending to a dynamic setting a previous method for the detection of anomalously dense subgraphs in a large background. In simulation, we show that this temporal integration technique enables the detection of weak subgraph anomalies than are not detectable
Structure and tie strengths in mobile communication networks
 Proc. Natl. Acad. Sci. (USA
, 2007
"... We examine the communication patterns of millions of anonymized mobile phone users. Based on call records, we construct a communication network where vertices are subscribers and edge weights are defined as aggregated duration of calls, reflecting the strengths of social ties between callers. We obs ..."
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Cited by 239 (13 self)
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observe a coupling between tie strengths and network topology: at the ”local ” level, strong ties are associated with densely connected network neighbourhoods, providing the first largescale confirmation of the Granovetter hypothesis. Based on fragmentation analysis, weak ties are seen to play
Computing communities in large networks using random walks
 J. of Graph Alg. and App. bf
, 2004
"... Dense subgraphs of sparse graphs (communities), which appear in most realworld complex networks, play an important role in many contexts. Computing them however is generally expensive. We propose here a measure of similarities between vertices based on random walks which has several important advan ..."
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Cited by 226 (3 self)
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Dense subgraphs of sparse graphs (communities), which appear in most realworld complex networks, play an important role in many contexts. Computing them however is generally expensive. We propose here a measure of similarities between vertices based on random walks which has several important
Fast Hierarchy Construction for Dense Subgraphs
"... ABSTRACT Discovering dense subgraphs and understanding the relations among them is a fundamental problem in graph mining. We want to not only identify dense subgraphs, but also build a hierarchy among them (e.g., larger but sparser subgraphs formed by two smaller dense subgraphs). Peeling algorithm ..."
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ABSTRACT Discovering dense subgraphs and understanding the relations among them is a fundamental problem in graph mining. We want to not only identify dense subgraphs, but also build a hierarchy among them (e.g., larger but sparser subgraphs formed by two smaller dense subgraphs). Peeling
Results 1  10
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822