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23
Topology Control and Routing in Ad hoc Networks: A Survey
 SIGACT News
, 2002
"... this article, we review some of the characteristic features of ad hoc networks, formulate problems and survey research work done in the area. We focus on two basic problem domains: topology control, the problem of computing and maintaining a connected topology among the network nodes, and routing. T ..."
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this article, we review some of the characteristic features of ad hoc networks, formulate problems and survey research work done in the area. We focus on two basic problem domains: topology control, the problem of computing and maintaining a connected topology among the network nodes, and routing. This article is not intended to be a comprehensive survey on ad hoc networking. The choice of the problems discussed in this article are somewhat biased by the research interests of the author
Communication on Dynamic Radio Networks
 In preparation
, 2006
"... We study the completion time of distributed broadcast protocols in dynamic radio networks. The dynamic network is modelled by means of adversaries: we consider two of them that somewhat are the extremal cases. We first analyze the weakest one, i.e., an oblivious, memoryless random adversary. At each ..."
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Cited by 35 (7 self)
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We study the completion time of distributed broadcast protocols in dynamic radio networks. The dynamic network is modelled by means of adversaries: we consider two of them that somewhat are the extremal cases. We first analyze the weakest one, i.e., an oblivious, memoryless random adversary. At each time slot t, a graph Gt is selected according to the wellknown random graph model Gn,p. We derive a randomized protocol that has O(log n) completion time. Then, we prove that any randomized protocol has Ω(log n) completion time. This tight bound holds when the protocol knows p. When p is unknown, we present an oblivious homogeneous version of the Bar YehudaGoldreichItai’s randomized protocol having O(log 2 n) completion time and we prove a lower bound Ω(log 2 n/log log n) that holds for any randomized oblivious homogeneous protocol. We emphasize that the above (poly)logarithmic upper bounds also hold when random graphs are sparse and disconnected, i.e., for p = o(lnn/n). We then consider the deterministic worstcase adversary that, at each time slot, can make any network change (thus the strongest adversary). Up to now, it is not even known whether finite expected completion time is achievable against this adversary. We present a simple randomized protocol that works in O(n 2 /log n) completion time. This bound is then shown to be optimal. ∗ Partially supported by the European Union under the Project AEOLUS.
Information spreading in stationary markovian evolving graphs
 In Proc. of the 23rd IEEE International Parallel and Distributed Processing Symposium (IPDPS
, 2009
"... Markovian evolving graphs [2] are dynamicgraph models where the links among a fixed set of nodes change during time according to an arbitrary Markovian rule. They are extremely general and they can well describe important dynamicnetwork scenarios. We study the speed of information spreading in the ..."
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Cited by 34 (9 self)
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Markovian evolving graphs [2] are dynamicgraph models where the links among a fixed set of nodes change during time according to an arbitrary Markovian rule. They are extremely general and they can well describe important dynamicnetwork scenarios. We study the speed of information spreading in the stationary phase by analyzing the completion time of the flooding mechanism. We prove a general theorem that establishes an upper bound on flooding time in any stationary Markovian evolving graph in terms of its nodeexpansion properties. We apply our theorem in two natural and relevant cases of such dynamic graphs: edgeMarkovian evolving graphs [24, 7] where the probability of existence of any edge at time t depends on the existence (or not) of the same edge at time t − 1; geometric Markovian evolving graphs [4, 10, 9] where the Markovian behaviour is yielded by n mobile radio stations, with fixed transmission radius, that perform n independent random walks over a square region of the plane. In both cases, the obtained upper bounds are shown to be nearly tight and, in fact, they turn out to be tight for a large range of the values of the input parameters. 1
The effects of faults on network expansion
 In Proc. 16th ACM Symposium on Parallel Algorithms and Architectures
, 2004
"... We study the problem of how resilient networks are to node faults. Specifically, we investigate the question of how many faults a network can sustain and still contain a large (i.e., linearsized) connected component with approximately the same expansion as the original faultfree network. We use a ..."
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Cited by 9 (1 self)
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We study the problem of how resilient networks are to node faults. Specifically, we investigate the question of how many faults a network can sustain and still contain a large (i.e., linearsized) connected component with approximately the same expansion as the original faultfree network. We use a pruning technique that culls away those parts of the faulty network that have poor expansion. The faults may occur at random or be caused by an adversary. Our techniques apply in either case. In the adversarial setting, we prove that for every network with expansion α, a large connected component with basically the same expansion as the original network exists for up to a constant times α · n faults. We show this result is tight in the sense that every graph G of size n and uniform expansion α(·) can be broken into components of size o(n) with ω(α(n) · n) faults. Unlike the adversarial case, the expansion of a graph gives a very weak bound on its resilience to random faults. While it is the case, as before, that there are networks of uniform expansion Ω(1 / log n) that are not resilient against a fault probability of a constant times 1 / log n, it is also observed that there are networks of uniform expansion O(1 / √ n) that are resilient against a constant fault probability. Thus, we introduce a different parameter, called the span of a graph, which gives us a more precise handle on the maximum fault probability. We use the span to show the first known results for the effect of random faults on the expansion of ddimensional meshes. 1
Temporal Network Optimization Subject to Connectivity Constraints
, 2013
"... In this work we consider temporal networks, i.e. networks defined by a labeling λ assigning to each edge of an underlying graph G asetofdiscrete timelabels. The labels of an edge, which are natural numbers, indicate the discrete time moments at which the edge is available. We focus on path problem ..."
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Cited by 8 (6 self)
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In this work we consider temporal networks, i.e. networks defined by a labeling λ assigning to each edge of an underlying graph G asetofdiscrete timelabels. The labels of an edge, which are natural numbers, indicate the discrete time moments at which the edge is available. We focus on path problems of temporal networks. In particular, we consider timerespecting paths, i.e. paths whose edges are assigned by λ a strictly increasing sequence of labels. We begin by giving two efficient algorithms for computing shortest timerespecting paths on a temporal network. We then prove that there is a natural analogue of Menger’s theorem holding for arbitrary temporal networks. Finally, we propose two cost minimization parameters for temporal network design. One is the temporality of G, in which the goal is to minimize the maximum number of labels of an edge, and the other is the temporal cost of G, inwhich the goal is to minimize the total number of labels used. Optimization of these parameters is performed subject to some connectivity constraint. We prove several lower and upper bounds for the temporality and the temporal cost of some very basic graph families such as rings, directed acyclic graphs, and trees.
Causality, Influence, and Computation in Possibly Disconnected Synchronous Dynamic Networks
, 2013
"... In this work, we study the propagation of influence and computation in dynamic distributed computing systems that are possibly disconnected at every instant. We focus on a synchronous message passing communication model with broadcast and bidirectional links. Our network dynamicity assumption is a w ..."
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Cited by 6 (6 self)
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In this work, we study the propagation of influence and computation in dynamic distributed computing systems that are possibly disconnected at every instant. We focus on a synchronous message passing communication model with broadcast and bidirectional links. Our network dynamicity assumption is a worstcase dynamicity controlled by an adversary scheduler, which has received much attention recently. We replace the usual (in worstcase dynamic networks) assumption that the network is connected at every instant by minimal temporal connectivity conditions. Our conditions only require that another causal influence occurs within every timewindow of some given length. Based on this basic idea we define several novel metrics for capturing the speed of information spreading in a dynamic network. We present several results that correlate these metrics. Moreover, we investigate termination criteria in networks in which an upper bound on any of these metrics is known. We exploit our termination criteria to provide efficient (and optimal in some cases) protocols that solve the fundamental counting and alltoall token dissemination (or gossip) problems.
802.11 link quality and its prediction  an experimental study
 In PWC
, 2004
"... Abstract. Reliable link quality prediction is an imperative for the efficient operation of mobile adhoc wireless networks (MANETs). In this paper it is shown that popular link quality prediction algorithms for 802.11 MANETs perform much more poorly when applied in real urban environments than they ..."
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Cited by 5 (0 self)
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Abstract. Reliable link quality prediction is an imperative for the efficient operation of mobile adhoc wireless networks (MANETs). In this paper it is shown that popular link quality prediction algorithms for 802.11 MANETs perform much more poorly when applied in real urban environments than they do in corresponding simulations. Our measurements show that the best performing prediction algorithm failed to predict between 18 and 54 percent of the total observed packet loss in the real urban environments examined. Moreover, with this algorithm between 12 and 43 percent of transmitted packets were lost due to the erroneous prediction of link failure. This contrasts sharply with nearperfect accuracy in corresponding simulations. To account for this discrepancy we perform an indepth examination of the factors that influence link quality. We conclude that shadowing is an especially significant and hitherto underestimated factor in link quality prediction in MANETs.
Prioritized Gossip in Vehicular Networks
, 2010
"... We present a method for using real world mobility traces to identify tractable theoretical models for the study of distributed algorithms in mobile networks. We validate the method by deriving a vehicular ad hoc network model from a large corpus of position data generated by Bostonarea taxicabs. Un ..."
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Cited by 5 (2 self)
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We present a method for using real world mobility traces to identify tractable theoretical models for the study of distributed algorithms in mobile networks. We validate the method by deriving a vehicular ad hoc network model from a large corpus of position data generated by Bostonarea taxicabs. Unlike previous work, our model does not assume global connectivity or eventual stability; it instead assumes only that some subset of processes are connected through transient paths (e.g., paths that exist over time). We use this model to study the problem of prioritized gossip, in which processes attempt to disseminate messages of different priority. Specifically, we present CabChat, a distributed prioritized gossip algorithm that leverages an interesting connection to the classic Tower of Hanoi problem to schedule the broadcast of packets of different priorities. Whereas previous studies of gossip leverage strong connectivity or stabilization assumptions to prove the time complexity of global termination, in our model, with its weak assumptions, we instead analyze CabChat with respect to its ability to deliver a high proportion of high priority messages over the transient paths that happen to exist in a given execution.
Naming and counting in anonymous unknown dynamic networks
 In 15th International Symposium on Stabilization, Safety, and Security of Distributed Systems (SSS
, 2013
"... Abstract. In this work, we study the fundamental naming and counting problems (and some variations) in networks that are anonymous, unknown, and possibly dynamic. In counting, nodes must determine the size of the network n and in naming they must end up with unique identities. By anonymous we mean ..."
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Cited by 4 (4 self)
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Abstract. In this work, we study the fundamental naming and counting problems (and some variations) in networks that are anonymous, unknown, and possibly dynamic. In counting, nodes must determine the size of the network n and in naming they must end up with unique identities. By anonymous we mean that all nodes begin from identical states apart possibly from a unique leader node and by unknown that nodes have no a priori knowledge of the network (apart from some minimal knowledge when necessary) including ignorance of n. Network dynamicity is modeled by the 1interval connectivity model [KLO10], in which communication is synchronous and a (worstcase) adversary chooses the edges of every round subject to the condition that each instance is connected. We first focus on static networks with broadcast where we prove that, without a leader, counting is impossible to solve and that naming is impossible to solve even with a leader and even if nodes know n. These impossibilities carry over to dynamic networks as well. We also show that a unique leader suffices in order to solve counting in linear time. Then we focus on dynamic networks with broadcast. We conjecture that dynamicity renders nontrivial computation impossible. In view of this, we let the nodes know an upper bound on the maximum degree that will ever appear and show that in this case the nodes can obtain an upper bound on n. Finally, we replace broadcast with onetoeach, in which a node may send a different message to each of its neighbors. Interestingly, this natural variation is proved to be computationally equivalent to a fullknowledge model, in which unique names exist and the size of the network is known. 1
Ephemeral Networks with Random Availability of Links: Diameter and Connectivity
, 2014
"... In this work we consider temporal networks, the links of which are available only at random times (randomly available temporal networks). Our networks are ephemeral: their links appear sporadically, only at certain times, within a given maximum time (lifetime of the net). More specifically, our tem ..."
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Cited by 4 (0 self)
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In this work we consider temporal networks, the links of which are available only at random times (randomly available temporal networks). Our networks are ephemeral: their links appear sporadically, only at certain times, within a given maximum time (lifetime of the net). More specifically, our temporal networks notion concerns networks, whose edges (arcs) are assigned one or more random discretetime labels drawn from a set of natural numbers. The labels of an edge indicate the discrete moments in time at which the edge is available. In such networks, information (e.g., messages) have to follow temporal paths, i.e., paths, the edges of which are assigned a strictly increasing sequence of labels. We first examine a very hostile network: a clique, each edge of which is known to be available only