11,591 research outputs found
Message and time efficient multi-broadcast schemes
We consider message and time efficient broadcasting and multi-broadcasting in
wireless ad-hoc networks, where a subset of nodes, each with a unique rumor,
wish to broadcast their rumors to all destinations while minimizing the total
number of transmissions and total time until all rumors arrive to their
destination. Under centralized settings, we introduce a novel approximation
algorithm that provides almost optimal results with respect to the number of
transmissions and total time, separately. Later on, we show how to efficiently
implement this algorithm under distributed settings, where the nodes have only
local information about their surroundings. In addition, we show multiple
approximation techniques based on the network collision detection capabilities
and explain how to calibrate the algorithms' parameters to produce optimal
results for time and messages.Comment: In Proceedings FOMC 2013, arXiv:1310.459
A Multilevel Approach to Topology-Aware Collective Operations in Computational Grids
The efficient implementation of collective communiction operations has
received much attention. Initial efforts produced "optimal" trees based on
network communication models that assumed equal point-to-point latencies
between any two processes. This assumption is violated in most practical
settings, however, particularly in heterogeneous systems such as clusters of
SMPs and wide-area "computational Grids," with the result that collective
operations perform suboptimally. In response, more recent work has focused on
creating topology-aware trees for collective operations that minimize
communication across slower channels (e.g., a wide-area network). While these
efforts have significant communication benefits, they all limit their view of
the network to only two layers. We present a strategy based upon a multilayer
view of the network. By creating multilevel topology-aware trees we take
advantage of communication cost differences at every level in the network. We
used this strategy to implement topology-aware versions of several MPI
collective operations in MPICH-G2, the Globus Toolkit[tm]-enabled version of
the popular MPICH implementation of the MPI standard. Using information about
topology provided by MPICH-G2, we construct these multilevel topology-aware
trees automatically during execution. We present results demonstrating the
advantages of our multilevel approach by comparing it to the default
(topology-unaware) implementation provided by MPICH and a topology-aware
two-layer implementation.Comment: 16 pages, 8 figure
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