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CoolStreaming/DONet: A Datadriven Overlay Network for PeertoPeer Live Media Streaming
 in IEEE Infocom
, 2005
"... This paper presents DONet, a Datadriven Overlay Network for live media streaming. The core operations in DONet are very simple: every node periodically exchanges data availability information with a set of partners, and retrieves unavailable data from one or more partners, or supplies available dat ..."
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Cited by 475 (42 self)
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This paper presents DONet, a Datadriven Overlay Network for live media streaming. The core operations in DONet are very simple: every node periodically exchanges data availability information with a set of partners, and retrieves unavailable data from one or more partners, or supplies available data to partners. We emphasize three salient features of this datadriven design: 1) easy to implement, as it does not have to construct and maintain a complex global structure; 2) efficient, as data forwarding is dynamically determined according to data availability while not restricted by specific directions; and 3) robust and resilient, as the partnerships enable adaptive and quick switching among multisuppliers. We show through analysis that DONet is scalable with bounded delay. We also address a set of practical challenges for realizing DONet, and propose an efficient member and partnership management algorithm, together with an intelligent scheduling algorithm that achieves realtime and continuous distribution of streaming contents.
Stability of Persistence Diagrams
, 2005
"... The persistence diagram of a realvalued function on a topological space is a multiset of points in the extended plane. We prove that under mild assumptions on the function, the persistence diagram is stable: small changes in the function imply only small changes in the diagram. We apply this result ..."
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Cited by 222 (23 self)
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The persistence diagram of a realvalued function on a topological space is a multiset of points in the extended plane. We prove that under mild assumptions on the function, the persistence diagram is stable: small changes in the function imply only small changes in the diagram. We apply this result to estimating the homology of sets in a metric space and to comparing and classifying geometric shapes.
Pajek  analysis and visualization of large networks
 GRAPH DRAWING SOFTWARE
, 2003
"... Pajek is a program, for Windows, for analysis and visualization of large networks having some ten or houndred of thousands of vertices. In Slovenian language pajek means spider. ..."
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Cited by 200 (3 self)
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Pajek is a program, for Windows, for analysis and visualization of large networks having some ten or houndred of thousands of vertices. In Slovenian language pajek means spider.
Minimumenergy broadcast in allwireless networks: Npcompleteness and distribution
 In Proc. of ACM MobiCom
, 2002
"... In allwireless networks a crucial problem is to minimize energy consumption, as in most cases the nodes are batteryoperated. We focus on the problem of poweroptimal broadcast, for which it is well known that the broadcast nature of the radio transmission can be exploited to optimize energy consump ..."
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Cited by 177 (2 self)
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In allwireless networks a crucial problem is to minimize energy consumption, as in most cases the nodes are batteryoperated. We focus on the problem of poweroptimal broadcast, for which it is well known that the broadcast nature of the radio transmission can be exploited to optimize energy consumption. Several authors have conjectured that the problem of poweroptimal broadcast is NPcomplete. We provide here a formal proof, both for the general case and for the geometric one; in the former case, the network topology is represented by a generic graph with arbitrary weights, whereas in the latter a Euclidean distance is considered. We then describe a new heuristic, Embedded Wireless Multicast Advantage. We show that it compares well with other proposals and we explain how it can be distributed. Categories and Subject Descriptors
Algorithmic Aspects of Topology Control Problems for Ad hoc Networks
, 2002
"... Topology control problems are concerned with the assignment of power values to the nodes of an ad~hoc network so that the power assignment leads to a graph topology satisfying some specified properties. This paper considers such problems under several optimization objectives, including minimizing th ..."
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Cited by 120 (6 self)
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Topology control problems are concerned with the assignment of power values to the nodes of an ad~hoc network so that the power assignment leads to a graph topology satisfying some specified properties. This paper considers such problems under several optimization objectives, including minimizing the maximum power and minimizing the total power. A general approach leading to a polynomial algorithm is presented for minimizing maximum power for a class of graph properties called monotone properties. The difficulty of generalizing the approach to properties that are not monotone is discussed. Problems involving the minimization of total power are known to be NPcomplete even for simple graph properties. A general approach that leads to an approximation algorithm for minimizing the total power for some monotone properties is presented. Using this approach, a new approximation algorithm for the problem of minimizing the total power for obtaining a 2nodeconnected graph is obtained. It is shown that this algorithm provides a constant performance guarantee. Experimental results from an implementation of the approximation algorithm are also presented.
Simulation of networks of spiking neurons: A review of tools and strategies
 Journal of Computational Neuroscience
, 2007
"... We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on ..."
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Cited by 108 (29 self)
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We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including HodgkinHuxley type, integrateandfire models, interacting with currentbased or conductancebased synapses, using clockdriven or eventdriven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given
Clustering with Constraints: Feasibility Issues and the kMeans Algorithm
, 2005
"... Recent work has looked at extending the kMeans algorithm to incorporate background information in the form of instance level mustlink and cannotlink constraints. We introduce two ways of specifying additional background information in the form of # and # constraints that operate on all instances ..."
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Cited by 90 (9 self)
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Recent work has looked at extending the kMeans algorithm to incorporate background information in the form of instance level mustlink and cannotlink constraints. We introduce two ways of specifying additional background information in the form of # and # constraints that operate on all instances but which can be interpreted as conjunctions or disjunctions of instance level constraints and hence are easy to implement. We present complexity results for the feasibility of clustering under each type of constraint individually and several types together. A key finding is that determining whether there is a feasible solution satisfying all constraints is, in general, NPcomplete. Thus, an iterative algorithm such as kMeans should not try to find a feasible partitioning at each iteration. This motivates our derivation of a new version of the kMeans algorithm that minimizes the constrained vector quantization error but at each iteration does not attempt to satisfy all constraints. Using standard UCI datasets, we find that using constraints improves accuracy as others have reported, but we also show that our algorithm reduces the number of iterations until convergence. Finally, we illustrate these benefits and our new constraint types on a complex real world object identification problem using the infrared detector on an Aibo robot.
A scalable lockfree stack algorithm
 In SPAA’04: Symposium on Parallelism in Algorithms and Architectures
, 2004
"... The literature describes two high performance concurrent stack algorithms based on combining funnels and elimination trees. Unfortunately, the funnels are linearizable but blocking, and the elimination trees are nonblocking but not linearizable. Neither is used in practice since they perform well o ..."
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Cited by 80 (11 self)
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The literature describes two high performance concurrent stack algorithms based on combining funnels and elimination trees. Unfortunately, the funnels are linearizable but blocking, and the elimination trees are nonblocking but not linearizable. Neither is used in practice since they perform well only at exceptionally high loads. The literature also describes a simple lockfree linearizable stack algorithm that works at low loads but does not scale as the load increases. The question of designing a stack algorithm that is nonblocking, linearizable, and scales well throughout the concurrency range, has thus remained open. This paper presents such a concurrent stack algorithm. It is based on the following simple observation: that a single elimination array used as a backoff scheme for a simple lockfree stack is lockfree, linearizable, and scalable. As our empirical results show, the resulting eliminationbackoff stack performs as well as the simple stack at low loads, and increasingly outperforms all other methods (lockbased and nonblocking) as concurrency increases. We believe its simplicity and scalability make it a viable practical alternative to existing constructions for implementing concurrent stacks.
Relational joins on graphics processors
, 2007
"... We present our novel design and implementation of relational join algorithms for newgeneration graphics processing units (GPUs). The new features of such GPUs include support for writes to random memory locations, efficient interprocessor communication through fast shared memory, and a programming ..."
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Cited by 74 (12 self)
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We present our novel design and implementation of relational join algorithms for newgeneration graphics processing units (GPUs). The new features of such GPUs include support for writes to random memory locations, efficient interprocessor communication through fast shared memory, and a programming model for generalpurpose computing. Taking advantage of these new features, we design a set of dataparallel primitives such as scan, scatter and split, and use these primitives to implement indexed or nonindexed nestedloop, sortmerge and hash joins. Our algorithms utilize the high parallelism as well as the high memory bandwidth of the GPU and use parallel computation to effectively hide the memory latency. We have implemented our algorithms on a PC with an NVIDIA G80 GPU and an Intel P4 dualcore CPU. Our GPUbased algorithms are able to achieve 220 times higher performance than their CPUbased counterparts.