13,097 research outputs found
Routing on the Visibility Graph
We consider the problem of routing on a network in the presence of line
segment constraints (i.e., obstacles that edges in our network are not allowed
to cross). Let be a set of points in the plane and let be a set of
non-crossing line segments whose endpoints are in . We present two
deterministic 1-local -memory routing algorithms that are guaranteed to
find a path of at most linear size between any pair of vertices of the
\emph{visibility graph} of with respect to a set of constraints (i.e.,
the algorithms never look beyond the direct neighbours of the current location
and store only a constant amount of additional information). Contrary to {\em
all} existing deterministic local routing algorithms, our routing algorithms do
not route on a plane subgraph of the visibility graph. Additionally, we provide
lower bounds on the routing ratio of any deterministic local routing algorithm
on the visibility graph.Comment: An extended abstract of this paper appeared in the proceedings of the
28th International Symposium on Algorithms and Computation (ISAAC 2017).
Final version appeared in the Journal of Computational Geometr
Edge Routing with Ordered Bundles
Edge bundling reduces the visual clutter in a drawing of a graph by uniting
the edges into bundles. We propose a method of edge bundling drawing each edge
of a bundle separately as in metro-maps and call our method ordered bundles. To
produce aesthetically looking edge routes it minimizes a cost function on the
edges. The cost function depends on the ink, required to draw the edges, the
edge lengths, widths and separations. The cost also penalizes for too many
edges passing through narrow channels by using the constrained Delaunay
triangulation. The method avoids unnecessary edge-node and edge-edge crossings.
To draw edges with the minimal number of crossings and separately within the
same bundle we develop an efficient algorithm solving a variant of the
metro-line crossing minimization problem. In general, the method creates clear
and smooth edge routes giving an overview of the global graph structure, while
still drawing each edge separately and thus enabling local analysis
An ACO Algorithm for Effective Cluster Head Selection
This paper presents an effective algorithm for selecting cluster heads in
mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc
network consists of a cluster head and cluster members which are at one hop
away from the cluster head. The cluster head allocates the resources to its
cluster members. Clustering in MANET is done to reduce the communication
overhead and thereby increase the network performance. A MANET can have many
clusters in it. This paper presents an algorithm which is a combination of the
four main clustering schemes- the ID based clustering, connectivity based,
probability based and the weighted approach. An Ant colony optimization based
approach is used to minimize the number of clusters in MANET. This can also be
considered as a minimum dominating set problem in graph theory. The algorithm
considers various parameters like the number of nodes, the transmission range
etc. Experimental results show that the proposed algorithm is an effective
methodology for finding out the minimum number of cluster heads.Comment: 7 pages, 5 figures, International Journal of Advances in Information
Technology (JAIT); ISSN: 1798-2340; Academy Publishers, Finlan
Optimal fault-tolerant placement of relay nodes in a mission critical wireless network
The operations of many critical infrastructures (e.g., airports) heavily depend on proper functioning of the radio communication network supporting operations. As a result, such a communication network is indeed a mission-critical communication network that needs adequate protection from external electromagnetic interferences. This is usually done through radiogoniometers. Basically, by using at least three suitably deployed radiogoniometers and a gateway gathering information from them, sources of electromagnetic emissions that are not supposed to be present in the monitored area can be localised. Typically, relay nodes are used to connect radiogoniometers to the gateway. As a result, some degree of fault-tolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given fault-tolerance. In this paper address the problem of computing a deployment for relay nodes that minimises the relay node network cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (fault-tolerance). We show that the above problem can be formulated as a Mixed Integer Linear Programming (MILP) as well as a Pseudo-Boolean Satisfiability (PB-SAT) optimisation problem and present experimental results com- paring the two approaches on realistic scenarios
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