81 research outputs found

    A powerful heuristic for telephone gossiping

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    A refined heuristic for computing schedules for gossiping in the telephone model is presented. The heuristic is fast: for a network with n nodes and m edges, requiring R rounds for gossiping, the running time is O(R n log(n) m) for all tested classes of graphs. This moderate time consumption allows to compute gossiping schedules for networks with more than 10,000 PUs and 100,000 connections. The heuristic is good: in practice the computed schedules never exceed the optimum by more than a few rounds. The heuristic is versatile: it can also be used for broadcasting and more general information dispersion patterns. It can handle both the unit-cost and the linear-cost model. Actually, the heuristic is so good, that for CCC, shuffle-exchange, butterfly de Bruijn, star and pancake networks the constructed gossiping schedules are better than the best theoretically derived ones. For example, for gossiping on a shuffle-exchange network with 2^{13} PUs, the former upper bound was 49 rounds, while our heuristic finds a schedule requiring 31 rounds. Also for broadcasting the heuristic improves on many formerly known results. A second heuristic, works even better for CCC, butterfly, star and pancake networks. For example, with this heuristic we found that gossiping on a pancake network with 7! PUs can be performed in 15 rounds, 2 fewer than achieved by the best theoretical construction. This second heuristic is less versatile than the first, but by refined search techniques it can tackle even larger problems, the main limitation being the storage capacity. Another advantage is that the constructed schedules can be represented concisely

    Lower bounds on systolic gossip

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    AbstractGossiping is an extensively investigated information dissemination process in which each processor has a distinct item of information and has to collect all the items possessed by the other processors. In this paper we provide an innovative and general lower bound technique relying on the novel notion of delay digraph of a gossiping protocol and on the use of matrix norm methods. Such a technique is very powerful and allows the determination of new and significantly improved lower bounds in many cases. In fact, we derive the first general lower bound on the gossiping time of systolic protocols, i.e., constituted by a periodic repetition of simple communication steps. In particular, given any network of n processors and any systolic period s, in the directed and the undirected half-duplex cases every s-systolic gossip protocol takes at least log(n)/log(1/λ)−O(loglog(n)) time steps, where λ is the unique solution between 0 and 1 of λ·p⌊s/2⌋(λ)·p⌈s/2⌉(λ)=1, with pi(λ)=1+λ2+⋯+λ2i−2 for any integer i>0. We then provide improved lower bounds in the directed and half-duplex cases for many well-known network topologies, such as Butterfly, de Bruijn, and Kautz graphs. All the results are extended also to the full-duplex case. Our technique is very general, as for s→∞ it allows the determination of improved results even for non-systolic protocols. In fact, for general networks, as a simple corollary it yields a lower bound only an O(loglog(n)) additive factor far from the general one independently proved in [Proc. 1st ACM Symposium on Parallel Algorithms and Architectures (SPAA), 1989, p. 318; Topics in Combinatorics and Graph Theory (1990) 451; SIAM Journal on Computing 21(1) (1992) 111; Discrete Applied Mathematics 42 (1993) 75] for all graphs and any (non-systolic) gossip protocol. Moreover, for specific networks, it significantly improves with respect to the previously known results, even in the full-duplex case. Correspondingly, better lower bounds on the gossiping time of non-systolic protocols are determined in the directed, half-duplex and full-duplex cases for Butterfly, de Bruijn, and Kautz graphs. Even if in this paper we give only a limited number of examples, our technique has wide applicability and gives a general framework that often allows to get improved lower bounds on the gossiping time of systolic and non-systolic protocols in the directed, half-duplex and full-duplex cases

    Broadcasting in DMA-bound bounded degree graphs

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    AbstractBroadcasting is an information dissemination process in which a message is to be sent from a single originator to all members of a network by placing calls over the communication lines of the network. In [2], Bermond, Hell, Liestman and Peters studied the effect, on broadcasting capabilities, of placing an upper bound on the graph's degree. In this paper, we generalize their results allowing calls to involve more than two participants. We give lower bounds and construct bounded degree graphs which allow rapid broadcasting. Our constructions use the nation of compounding graphs in de Bruijin digraphs. We also obtain asymptotic upper and lower bounds for broadcast time, as the maximum degree increases

    Optimal Initialization and Gossiping Algorithms for Random Radio Networks

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    The initialization problem, also known as naming, consists to give a unique identifier ranging from 11 to nn to a set of nn indistinguishable nodes in a given network. We consider a network where nn nodes (processors) are randomly deployed in a square (resp. cube) XX. We assume that the time is slotted and the network is synchronous, two nodes are able to communicate if they are within distance at most of rr of each other (rr is the transmitting/receiving range). Moreover, if two or more neighbors of a processor uu transmit concurrently at the same time slot, then uu would not receive either messages. We suppose also that the anonymous nodes know neither the topology of the network nor the number of nodes in the network. Under this extremal scenario, we first show how the transmitting range of the deployed processors affects the typical characteristics of the network. Then, by allowing the nodes to transmit at various ranges we design sub-linear randomized initialization protocols~: In the two, resp. three, dimensional case, our randomized initialization algorithms run in O(n1/2logn1/2)O(n^{1/2} \log{n}^{1/2}), resp. O(n1/3logn2/3)O(n^{1/3} \log{n}^{2/3}), time slots. These latter protocols are based upon an optimal gossiping algorithm which is of independent interest

    Multiple message broadcasting and gossiping in the dynamically orientable graphs

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    This research investigates the problems of gossiping and multiple message broadcasting in dynamically orientable graphs of different network topologies. These are new problems never attempted before. Dynamically orientable graphs and six different network topologies are considered: paths, cycles, stars, binary trees, complete trees and two-dimensional grids. Information dissemination in graphs that are dynamically orientable requires that number of messages sent in each direction along an edge be balanced and therefore necessitates a different approach in gossiping and multiple message broadcasting.;The obvious upper bound for gossiping and multiple message broadcasting in dynamically orientable graphs is twice the best known time for gossiping and multiple message broadcasting in classical graphs. This is obtained by inserting an additional time step t\u27 after each time step t in the classical graph algorithm in which all calls of time step t are repeated with messages moving along the same edges but in the opposite direction to reset the bias of these edges. Finding better bounds for gossiping and multiple message broadcasting in dynamically orientable graphs is the goal of this research.;For each network topology an algorithm is proposed to perform gossiping and multiple message broadcasting. For some network topologies proposed algorithms for dynamically orientable graphs achieved the same upper bound as it is known for classical graphs, for example, gossiping in dynamically orientable grid graphs. In some cases the best time is the twice the best known time for gossiping and multiple message broadcasting in classical graphs, for example, gossiping in dynamically orientable star graphs. In other cases, good time bounds are achieved that are very close to the upper bounds in classical graphs, for example, multiple message broadcasting in dynamically orientable grid graphs. Multiple message broadcasting in dynamically orientable cycle graphs is also a good example of close upper bounds. As number of messages increases bounds become very close to each other

    Broadcasting in Hyper-cylinder graphs

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    Broadcasting in computer networking means the dissemination of information, which is known initially only at some nodes, to all network members. The goal is to inform every node in the minimal time possible. There are few models for broadcasting; the simplest and the historical model is called the Classical model. In the Classical model, dissemination happens in synchronous rounds, wherein a node may only inform one of its neighbors. The broadcast question is: What is the minimum number of rounds needed for broadcasting, and what broadcast scheme achieves it? For general graphs, these questions are NP-hard, and it is known to be at least 3 - ε inapproximable for any real ε > 0. Even for some very restricted classes of graphs, the questions remain as an NP-hard problem. Little is known about broadcasting in restricted graphs, and only a few classes have a polynomial solution. Parallel and distributed computing is one of the important domains which relies on efficient broadcasting. Hypercube and torus are the most used network topology in this domain. The widespread use is not only due to their simplicity but also is for their efficiency and high robustness (e.g., fault tolerance) while having an acceptable number of links. In this thesis, it is observed that the Cartesian product of a number of path and cycle graphs produces a valuable set of topologies, we called hyper-cylinders, which contain hypercube and Torus as well. Any hyper-cylinder shares many of the beneficial features of hypercube and torus and might be a suitable substitution in some cases. Some hyper-cylinders are also similar to other practically used topologies such as cube-connected cycles. In this thesis, the effect of the Cartesian product on broadcasting and broadcasting of hyper-cylinders under the Classical and Messy models is studied. This will add a valuable class of graphs to the limited classes of graphs which have a polynomially computable broadcast time. In the end, the relation between worst-case originators and diameters in trees is studied, which may help in the broadcast study of a larger class of graphs where any tree is allowed instead of a path in the Cartesian product

    Random Geometric Graphs and the Initialization Problem for Wireless Networks

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    32 pages. Tutorial invitéInternational audienceThe initialization problem, also known as naming, assigns one unique identifier (ranging from 1 to nn) to a set of n indistinguishable nodes (stations or processors) in a given wireless network NN. NN is composed of nn nodes randomly deployed within a square (or a cube) XX. We assume the time to be slotted and NN to be synchronous; two nodes are able to communicate if they are within a distance at most rr of each other (rr is the transmitting/receiving range). Moreover, if two or more neighbors of a processor uu transmit concurrently at the same round, uu does not receive either messages. After the analysis of various critical transmitting/sensing ranges for connectivity and coverage of randomly deployed sensor networks, we design sub-linear randomized initialization and gossip algorithms achieving O(n1/2log(n)1/2)O(n^1/2 \log(n)^1/2) and O(n1/3log(n)2/3)roundsinthetwodimensionalandthethreedimensionalcases,respectively.Next,weproposeenergyefficientinitializationandgossipalgorithmsrunninginO(n^1/3 \log(n)^2/3) rounds in the two-dimensional and the three-dimensional cases, respectively. Next, we propose energy-efficient initialization and gossip algorithms running in O(n^3/4 \log (n)^1/4)rounds,withnostationbeingawakeformorethanO(n1/4log(n)3/4) rounds, with no station being awake for more than O(n^1/4 \log (n)^3/4) rounds

    Fault-free longest paths in star networks with conditional link faults

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    AbstractThe star network, which belongs to the class of Cayley graphs, is one of the most versatile interconnection networks for parallel and distributed computing. In this paper, adopting the conditional fault model in which each node is assumed to be incident with two or more fault-free links, we show that an n-dimensional star network can tolerate up to 2n−7 link faults, and be strongly (fault-free) Hamiltonian laceable, where n≥4. In other words, we can embed a fault-free linear array of length n!−1 (n!−2) in an n-dimensional star network with up to 2n−7 link faults, if the two end nodes belong to different partite sets (the same partite set). The result is optimal with respect to the number of link faults tolerated. It is already known that under the random fault model, an n-dimensional star network can tolerate up to n−3 faulty links and be strongly Hamiltonian laceable, for n≥3

    Extremal Properties of Three Dimensional Sensor Networks with Applications

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    In this paper, we analyze various critical transmitting/sensing ranges for connectivity and coverage in three-dimensional sensor networks. As in other large-scale complex systems, many global parameters of sensor networks undergo phase transitions: For a given property of the network, there is a critical threshold, corresponding to the minimum amount of the communication effort or power expenditure by individual nodes, above (resp. below) which the property exists with high (resp. a low) probability. For sensor networks, properties of interest include simple and multiple degrees of connectivity/coverage. First, we investigate the network topology according to the region of deployment, the number of deployed sensors and their transmitting/sensing ranges. More specifically, we consider the following problems: Assume that nn nodes, each capable of sensing events within a radius of rr, are randomly and uniformly distributed in a 3-dimensional region R\mathcal{R} of volume VV, how large must the sensing range be to ensure a given degree of coverage of the region to monitor? For a given transmission range, what is the minimum (resp. maximum) degree of the network? What is then the typical hop-diameter of the underlying network? Next, we show how these results affect algorithmic aspects of the network by designing specific distributed protocols for sensor networks
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