Arik Motskin

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—We study the distributed desynchronization problem for graphs with arbitrary topology. Motivated by the severe computational limitations of sensor networks, we present a randomized algorithm for network desynchronization that uses an extremely lightweight model of computation, while being robust to link volatility and node failure. These techniques also(More)
—We propose an interference-aware MAC protocol using a simple transmission strategy motivated by a game-theoretic approach. We formulate a channel access game, which considers nodes concurrently transmitting in nearby clusters, incorporating a realistic wireless communication model-the SINR model. Under inter-cluster interference, we derive a decentralized(More)
We develop a mathematical optimization model at the intersection of homeland security and immigration, that chooses various immigration enforcement decision variables to minimize the probability that a terrorist can successfully enter the United States across the U.S.-Mexico border. Included are a discrete choice model for the probability that a potential(More)
—We consider the problem of distributing time-sensitive information from a collection of sources to mobile users traversing a wireless mesh network. Our strategy is to distributively select a set of well-placed nodes (warehouses) to act as intermediaries between the information sources and clusters of users. Warehouses are selected via the distributed(More)
We propose algorithms for efficiently maintaining a constant-approximate minimum connected dominating set (MCDS) of a geometric graph under node insertions and deletions. Assuming that two nodes are adjacent in the graph iff they are within a fixed geometric distance, we show that an O(1)-approximate MCDS of a graph in R d with n nodes can be maintained(More)
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