252,918 research outputs found
Fast Structuring of Radio Networks for Multi-Message Communications
We introduce collision free layerings as a powerful way to structure radio
networks. These layerings can replace hard-to-compute BFS-trees in many
contexts while having an efficient randomized distributed construction. We
demonstrate their versatility by using them to provide near optimal distributed
algorithms for several multi-message communication primitives.
Designing efficient communication primitives for radio networks has a rich
history that began 25 years ago when Bar-Yehuda et al. introduced fast
randomized algorithms for broadcasting and for constructing BFS-trees. Their
BFS-tree construction time was rounds, where is the network
diameter and is the number of nodes. Since then, the complexity of a
broadcast has been resolved to be rounds. On the other hand, BFS-trees have been used as a crucial building
block for many communication primitives and their construction time remained a
bottleneck for these primitives.
We introduce collision free layerings that can be used in place of BFS-trees
and we give a randomized construction of these layerings that runs in nearly
broadcast time, that is, w.h.p. in rounds for any constant . We then use these
layerings to obtain: (1) A randomized algorithm for gathering messages
running w.h.p. in rounds. (2) A randomized -message
broadcast algorithm running w.h.p. in rounds. These
algorithms are optimal up to the small difference in the additive
poly-logarithmic term between and . Moreover, they imply the
first optimal round randomized gossip algorithm
Radio Galaxy Zoo: Knowledge Transfer Using Rotationally Invariant Self-Organising Maps
With the advent of large scale surveys the manual analysis and classification
of individual radio source morphologies is rendered impossible as existing
approaches do not scale. The analysis of complex morphological features in the
spatial domain is a particularly important task. Here we discuss the challenges
of transferring crowdsourced labels obtained from the Radio Galaxy Zoo project
and introduce a proper transfer mechanism via quantile random forest
regression. By using parallelized rotation and flipping invariant Kohonen-maps,
image cubes of Radio Galaxy Zoo selected galaxies formed from the FIRST radio
continuum and WISE infrared all sky surveys are first projected down to a
two-dimensional embedding in an unsupervised way. This embedding can be seen as
a discretised space of shapes with the coordinates reflecting morphological
features as expressed by the automatically derived prototypes. We find that
these prototypes have reconstructed physically meaningful processes across two
channel images at radio and infrared wavelengths in an unsupervised manner. In
the second step, images are compared with those prototypes to create a
heat-map, which is the morphological fingerprint of each object and the basis
for transferring the user generated labels. These heat-maps have reduced the
feature space by a factor of 248 and are able to be used as the basis for
subsequent ML methods. Using an ensemble of decision trees we achieve upwards
of 85.7% and 80.7% accuracy when predicting the number of components and peaks
in an image, respectively, using these heat-maps. We also question the
currently used discrete classification schema and introduce a continuous scale
that better reflects the uncertainty in transition between two classes, caused
by sensitivity and resolution limits
Pileated woodpeckers (Dryocopus pileatus) and saproxylic beetles in partial cut and uncut bottomland hardwood forests
Relative abundance and species richness of saproxylic beetles and nesting, roosting, and foraging ecology of pileated woodpeckers were studied in recent partial cuts and uncut forest during the summers of 2006 and 2007. Relative abundance of saproxylic beetles was greater in one-year old cuts than uncut forest during 2006 but was not consistent during 2007. The number of dead trees, period of capture, and trapping year also influenced beetle abundance. Species richness was similar in partial cuts and uncut forest. Characteristics of habitat used by pileated woodpeckers for nesting and roosting in one-year-old and two-year-old partial cuts and uncut forest were similar. Woodpeckers used five species of trees that were between 42 and 150 cm diameter at breast height (dbh) for nesting (n = 24, 60.5 ± 3.02; mean ± SE) and roosting (n = 15, 70.3 ± 7.03). Baldcypress (Taxodium distichum) was selected in all treatments. Nests (22 of 24) and roosts (12 of 15) were predominantly in boles of live trees (vigorous to decadent). Nest and roost sites contained more trees \u3e50 cm dbh than were available in random plots. Foraging observations were conducted in 20 territories of radio- and non-radio-tagged pileated woodpeckers. Pileated woodpeckers spent the highest proportion of their foraging time excavating (58%), followed by pecking (14%), gleaning (14%), scaling (7%), berry-eating (4%), and probing (3%). They foraged on live boles (41%), dead branches (27%), live branches (13%), dead boles (10%), and vines (9%). Woodpeckers preferred bitter pecan (Carya aquatica), avoided sugarberry (Celtis laevigata), and used overcup oak (Quercus lyrata) in proportion to availability. They avoided dbh classes 10-20, selected dbh classes 50-70, and used dbh classes 30-40 in proportion to their availability in most treatments. In partial cuts, extremely large trees (dbh classes 80-90+) were selected. Pileateds either avoided vigorous and decadent trees for foraging or used them in proportion to their availability. Woodpeckers preferred trees in early stages of decay in all treatments but in two-year-old partial cuts they preferred trees in late stages of decay. Scat of pileated woodpeckers contained Pheidole ants, carpenter (Camponotus) ants, beetles (Coleoptera), and seeds of poison ivy
Joint multicast routing and channel assignment in multiradio multichannel wireless mesh networks using tabu search
Copyright @ 2009 IEEE Computer SocietyThis paper proposes a tabu search (TS) based optimization approach to search a minimum-interference multicast tree which satisfies the end-to-end delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. The path-oriented encoding method is adopted and each candidate solution is represented by a tree data structure (i.e., a set of paths). Since we expect the multicast trees on which the minimum-interference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. The techniques for controlling the tabu search procedure are well developed. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed TS multicast algorithm can produce the multicast trees which have better performance in terms of both the total channel conflict and the tree cost than that of a well known multicast algorithm in wireless mesh networks.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1
Joint QoS multicast routing and channel assignment in multiradio multichannel wireless mesh networks using intelligent computational methods
Copyright @ 2010 Elsevier B.V. All rights reserved.In this paper, the quality of service multicast routing and channel assignment (QoS-MRCA) problem is investigated. It is proved to be a NP-hard problem. Previous work separates the multicast tree construction from the channel assignment. Therefore they bear severe drawback, that is, channel assignment cannot work well with the determined multicast tree. In this paper, we integrate them together and solve it by intelligent computational methods. First, we develop a unified framework which consists of the problem formulation, the solution representation, the fitness function, and the channel assignment algorithm. Then, we propose three separate algorithms based on three representative intelligent computational methods (i.e., genetic algorithm, simulated annealing, and tabu search). These three algorithms aim to search minimum-interference multicast trees which also satisfy the end-to-end delay constraint and optimize the usage of the scarce radio network resource in wireless mesh networks. To achieve this goal, the optimization techniques based on state of the art genetic algorithm and the techniques to control the annealing process and the tabu search procedure are well developed separately. Simulation results show that the proposed three intelligent computational methods based multicast algorithms all achieve better performance in terms of both the total channel conflict and the tree cost than those comparative references.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1
Joint multicast routing and channel assignment in multiradio multichannel wireless mesh networks using simulated annealing
This is the post-print version of the article - Copyright @ 2008 Springer-VerlagThis paper proposes a simulated annealing (SA) algorithm based optimization approach to search a minimum-interference multicast tree which satisfies the end-to-end delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. In the proposed SA multicast algorithm, the path-oriented encoding method is adopted and each candidate solution is represented by a tree data structure (i.e., a set of paths). Since we anticipate the multicast trees on which the minimum-interference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. The techniques for controlling the annealing process are well developed. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed SA based multicast algorithm can produce the multicast trees which have better performance in terms of both the total channel conflict and the tree cost than that of a well known multicast algorithm in wireless mesh networks.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1
A genetic-inspired joint multicast routing and channel assignment algorithm in wireless mesh networks
Copyright @ 2008 IEEEThis paper proposes a genetic algorithm (GA) based optimization approach to search a minimum-interference multicast tree which satis¯es the end-to-end delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. The path-oriented en- coding method is used and each chromosome is represented by a tree data structure (i.e., a set of paths). Since we expect the multicast trees on which the minimum-interference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. Crossover and mutation are well designed to adapt to the tree structure. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed GA based multicast algorithm achieves better performance in terms of both the total channel conflict and the tree cost than that of a well known algorithm
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On the Computational Power of Radio Channels
Radio networks can be a challenging platform for which to develop distributed algorithms, because the network nodes must contend for a shared channel. In some cases, though, the shared medium is an advantage rather than a disadvantage: for example, many radio network algorithms cleverly use the shared channel to approximate the degree of a node, or estimate the contention. In this paper we ask how far the inherent power of a shared radio channel goes, and whether it can efficiently compute "classicaly hard" functions such as Majority, Approximate Sum, and Parity.
Using techniques from circuit complexity, we show that in many cases, the answer is "no". We show that simple radio channels, such as the beeping model or the channel with collision-detection, can be approximated by a low-degree polynomial, which makes them subject to known lower bounds on functions such as Parity and Majority; we obtain round lower bounds of the form Omega(n^{delta}) on these functions, for delta in (0,1). Next, we use the technique of random restrictions, used to prove AC^0 lower bounds, to prove a tight lower bound of Omega(1/epsilon^2) on computing a (1 +/- epsilon)-approximation to the sum of the nodes\u27 inputs. Our techniques are general, and apply to many types of radio channels studied in the literature
Monte-Carlo Modeling of Non-Gravitational Heating Processes in Galaxy Clusters
We consider non-gravitational heating effects on galaxy clusters on the basis
of the Monte-Carlo modeling of merging trees of dark matter halos combined with
the thermal evolution of gas inside each halo. Under the assumption of
hydrostatic equilibrium and the isothermal gas profiles, our model takes
account of the metallicity evolution, metallicity-dependent cooling of gas,
supernova energy feedback, and heating due to jets of radio galaxies in a
consistent manner. The observed properties of galaxy clusters can be explained
in models with higher non-gravitational heating efficiency than that in the
conventional model. Possibilities include jet heating by the Fanaroff-Riley
Type II radio galaxies, and the enhanced star formation efficiency and/or
supernova energy feedback, especially at high redshifts.Comment: 29 pages, 12 figures. To appear in PASJ, February 25, 200
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