6,259 research outputs found
Shortest, Fastest, and Foremost Broadcast in Dynamic Networks
Highly dynamic networks rarely offer end-to-end connectivity at a given time.
Yet, connectivity in these networks can be established over time and space,
based on temporal analogues of multi-hop paths (also called {\em journeys}).
Attempting to optimize the selection of the journeys in these networks
naturally leads to the study of three cases: shortest (minimum hop), fastest
(minimum duration), and foremost (earliest arrival) journeys. Efficient
centralized algorithms exists to compute all cases, when the full knowledge of
the network evolution is given.
In this paper, we study the {\em distributed} counterparts of these problems,
i.e. shortest, fastest, and foremost broadcast with termination detection
(TDB), with minimal knowledge on the topology.
We show that the feasibility of each of these problems requires distinct
features on the evolution, through identifying three classes of dynamic graphs
wherein the problems become gradually feasible: graphs in which the
re-appearance of edges is {\em recurrent} (class R), {\em bounded-recurrent}
(B), or {\em periodic} (P), together with specific knowledge that are
respectively (the number of nodes), (a bound on the recurrence
time), and (the period). In these classes it is not required that all pairs
of nodes get in contact -- only that the overall {\em footprint} of the graph
is connected over time.
Our results, together with the strict inclusion between , , and ,
implies a feasibility order among the three variants of the problem, i.e.
TDB[foremost] requires weaker assumptions on the topology dynamics than
TDB[shortest], which itself requires less than TDB[fastest]. Reversely, these
differences in feasibility imply that the computational powers of ,
, and also form a strict hierarchy
A general route to the synthesis of surfactant-free, solvent-dispersible ternary and quaternary chalcogenide nanocrystals
A general route to the synthesis of surfactant-free CuInS2 (CIS), Cu2CoSnS4 (CCTS) and Cu2ZnSnS4 (CZTS) nanocrystals dispersible in low boiling point solvents is proposed. These nanocrystal inks should be of great interest to the fabrication of thin film absorbers of chalcogenide solar cells
DĂ©couverte remarquable dans une grotte du sud-ouest du Maroc : Siagona taggadertensis n.sp. (Carabidae : Siagoninae)
[EN] Five species of the genus Siagona Latreille 1804 (Carabidae: Siagoninae) are known from Morocco. Siagona taggadertensis n. sp., a remarkable species of Carabidae from a Moroccan cave is described. This insect is spectacular by its large size (one of the largest species of the genus), its
external morphology, which isolates it from all the north african representant of the genus, and for the conditions of its discovery: its only known from the remains of six specimens, all of them found in the
cave of Taggadert, western Atlas. Hypotheses concerning the ecology of this species are discussed.[FR] Le genre Siagona Latreille 1804 (Carabidae: Siagoninae), compte 5 espèces au Maroc. Siagona taggadertensis n. sp., remarquable espèce collectée dans une grotte marocaine est décrite. Cet insecte est spectaculaire tant par sa grande taille, sa morphologie externe qui l’isole au premier coup d’oeil des représentants nord africains du genre Siagona, que par les conditions de sa découverte : aucun des spécimens n’ont été collectés en dehors de la grotte de Taggadert, Atlas occidental. Des hypothèses concernant l’écologie de cette espèce sont fournies.AF was supported by a postdoctoral Research
Fellowship from the Alexander von Humboldt Foundation.Peer reviewe
Goal-oriented test data generation for pointer programs
Goal-oriented test data generation; Constraint Logic Programming; Static Single Assignment formInternational audienceAutomatic test data generation leads to the identification of input values on which a selected path or a selected branch is executed within a program (path-oriented vs goal-oriented methods). In both cases, several approaches based on constraint solving exist, but in the presence of pointer variables only path-oriented methods have been proposed. Pointers are responsible for the existence of conditional aliasing problems that usually provoke the failure of the goal-oriented test data generation process. In this paper, we propose an overall constraint-based method that exploits the results of an intraprocedural points-to analysis and provides two specific constraint combinators for automatically generating goal-oriented test data. This approach correctly handles multi-levels stack-directed pointers that are mainly used in C programs. The method has been fully implemented in the test data generation tool INKA and first experiences in applying it to a variety of existing programs are presented
On the Feasibility of Maintenance Algorithms in Dynamic Graphs
Near ubiquitous mobile computing has led to intense interest in dynamic graph
theory. This provides a new and challenging setting for algorithmics and
complexity theory. For any graph-based problem, the rapid evolution of a
(possibly disconnected) graph over time naturally leads to the important
complexity question: is it better to calculate a new solution from scratch or
to adapt the known solution on the prior graph to quickly provide a solution of
guaranteed quality for the changed graph?
In this paper, we demonstrate that the former is the best approach in some
cases, but that there are cases where the latter is feasible. We prove that,
under certain conditions, hard problems cannot even be approximated in any
reasonable complexity bound --- i.e., even with a large amount of time, having
a solution to a very similar graph does not help in computing a solution to the
current graph. To achieve this, we formalize the idea as a maintenance
algorithm. Using r-Regular Subgraph as the primary example we show that
W[1]-hardness for the parameterized approximation problem implies the
non-existence of a maintenance algorithm for the given approximation ratio.
Conversely we show that Vertex Cover, which is fixed-parameter tractable, has a
2-approximate maintenance algorithm. The implications of NP-hardness and
NPO-hardness are also explored
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