this information; none of them can unfortunately be efficiently implemented in a distributed environment. In this paper we present protocols, based on a new strategy, that allow the efficient computation of all the optimal swap edges under several optimization criteria.

pheromone they deposit on the edges of the TSP graph while building solutions. We study the ACS by running experiments to understand its operation. The results show that the ACS outperforms other nature-inspired algorithms such as simulated annealing and evolutionary computation, and we conclude comparing

of probability distributions — are best studied in the general setting. Working with exponential family representations, and exploiting the conjugate duality between the cumulant function and the entropy for exponential families, we develop general variational representations of the problems of computing

keys for all pairs of nodes is not viable due to the large number of sensors and the limited memory of sensor nodes. A new key distribution approach was proposed by Eschenauer and Gligor [11] to achieve secrecy for node-to-node communication: sensor nodes receive a random subset of keys from a key pool

edge in the spanner T, a best swap edge that minimizes the stretch of the new tree. We show how all these best swap edges

spreads, with most of the remainder attributable to a single systematic factor. Similarly, Duffie and Singleton (1999) find that both credit-risk and liquidity factors are necessary to explain innovations in U.S. swap rates. However, when analyzing the residuals they are unable to find explanatory factors

swapping. We propose a distributed algorithm that efficiently computes all of these swap links, and we explain how to route messages across swap edges with a compact routing scheme. Finally, we consider the computation of swap edges in an arbitrary spanning tree, where swap edges are chosen to minimize

swapping. We propose a distributed algorithm that efficiently computes all of these swap links, and we explain how to route messages across swap edges with a compact routing scheme.

, each of which captures a different feature channel. Our features include the distribution of edges, dense and sparse visual words, and feature descriptors at different levels of spatial organization. Such a powerful classifier cannot be tested on all image sub-windows in a reasonable amount of time

Abstract. We consider the problem of computing the best swap edges of a shortest-path tree Tr rooted in r. That is, given a single link failure: if the path is not affected by the failed link, then the message will be delivered through that path; otherwise, we want to guarantee that, when