9,685 research outputs found
Tight Bounds for Maximal Identifiability of Failure Nodes in Boolean Network Tomography
We study maximal identifiability, a measure recently introduced in Boolean
Network Tomography to characterize networks' capability to localize failure
nodes in end-to-end path measurements. We prove tight upper and lower bounds on
the maximal identifiability of failure nodes for specific classes of network
topologies, such as trees and -dimensional grids, in both directed and
undirected cases. We prove that directed -dimensional grids with support
have maximal identifiability using monitors; and in the
undirected case we show that monitors suffice to get identifiability of
. We then study identifiability under embeddings: we establish relations
between maximal identifiability, embeddability and graph dimension when network
topologies are model as DAGs. Our results suggest the design of networks over
nodes with maximal identifiability using
monitors and a heuristic to boost maximal identifiability on a given network by
simulating -dimensional grids. We provide positive evidence of this
heuristic through data extracted by exact computation of maximal
identifiability on examples of small real networks
A Unified approach to concurrent and parallel algorithms on balanced data structures
Concurrent and parallel algorithms are different. However, in the case of dictionaries, both kinds of algorithms share many
common points. We present a unified approach emphasizing these points. It is based on a careful analysis of the sequential
algorithm, extracting from it the more basic facts, encapsulated later on as local rules. We apply the method to the
insertion algorithms in AVL trees. All the concurrent and parallel insertion algorithms have two main phases. A
percolation phase, moving the keys to be inserted down, and a rebalancing phase. Finally, some other algorithms and
balanced structures are discussed.Postprint (published version
Architectural Considerations for a Self-Configuring Routing Scheme for Spontaneous Networks
Decoupling the permanent identifier of a node from the node's
topology-dependent address is a promising approach toward completely scalable
self-organizing networks. A group of proposals that have adopted such an
approach use the same structure to: address nodes, perform routing, and
implement location service. In this way, the consistency of the routing
protocol relies on the coherent sharing of the addressing space among all nodes
in the network. Such proposals use a logical tree-like structure where routes
in this space correspond to routes in the physical level. The advantage of
tree-like spaces is that it allows for simple address assignment and
management. Nevertheless, it has low route selection flexibility, which results
in low routing performance and poor resilience to failures. In this paper, we
propose to increase the number of paths using incomplete hypercubes. The design
of more complex structures, like multi-dimensional Cartesian spaces, improves
the resilience and routing performance due to the flexibility in route
selection. We present a framework for using hypercubes to implement indirect
routing. This framework allows to give a solution adapted to the dynamics of
the network, providing a proactive and reactive routing protocols, our major
contributions. We show that, contrary to traditional approaches, our proposal
supports more dynamic networks and is more robust to node failures
Route Planning in Transportation Networks
We survey recent advances in algorithms for route planning in transportation
networks. For road networks, we show that one can compute driving directions in
milliseconds or less even at continental scale. A variety of techniques provide
different trade-offs between preprocessing effort, space requirements, and
query time. Some algorithms can answer queries in a fraction of a microsecond,
while others can deal efficiently with real-time traffic. Journey planning on
public transportation systems, although conceptually similar, is a
significantly harder problem due to its inherent time-dependent and
multicriteria nature. Although exact algorithms are fast enough for interactive
queries on metropolitan transit systems, dealing with continent-sized instances
requires simplifications or heavy preprocessing. The multimodal route planning
problem, which seeks journeys combining schedule-based transportation (buses,
trains) with unrestricted modes (walking, driving), is even harder, relying on
approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4,
previously published by Microsoft Research. This work was mostly done while
the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at
Microsoft Research Silicon Valle
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