628 research outputs found
Applications of Geometric Algorithms to Reduce Interference in Wireless Mesh Network
In wireless mesh networks such as WLAN (IEEE 802.11s) or WMAN (IEEE 802.11),
each node should help to relay packets of neighboring nodes toward gateway
using multi-hop routing mechanisms. Wireless mesh networks usually intensively
deploy mesh nodes to deal with the problem of dead spot communication. However,
the higher density of nodes deployed, the higher radio interference occurred.
This causes significant degradation of system performance. In this paper, we
first convert network problems into geometry problems in graph theory, and then
solve the interference problem by geometric algorithms. We first define line
intersection in a graph to reflect radio interference problem in a wireless
mesh network. We then use plan sweep algorithm to find intersection lines, if
any; employ Voronoi diagram algorithm to delimit the regions among nodes; use
Delaunay Triangulation algorithm to reconstruct the graph in order to minimize
the interference among nodes. Finally, we use standard deviation to prune off
those longer links (higher interference links) to have a further enhancement.
The proposed hybrid solution is proved to be able to significantly reduce
interference in a wireless mesh network in O(n log n) time complexity.Comment: 24 Pages, JGraph-Hoc Journal 201
Towards a Scalable Dynamic Spatial Database System
With the rise of GPS-enabled smartphones and other similar mobile devices,
massive amounts of location data are available. However, no scalable solutions
for soft real-time spatial queries on large sets of moving objects have yet
emerged. In this paper we explore and measure the limits of actual algorithms
and implementations regarding different application scenarios. And finally we
propose a novel distributed architecture to solve the scalability issues.Comment: (2012
Improved Incremental Randomized Delaunay Triangulation
We propose a new data structure to compute the Delaunay triangulation of a
set of points in the plane. It combines good worst case complexity, fast
behavior on real data, and small memory occupation.
The location structure is organized into several levels. The lowest level
just consists of the triangulation, then each level contains the triangulation
of a small sample of the levels below. Point location is done by marching in a
triangulation to determine the nearest neighbor of the query at that level,
then the march restarts from that neighbor at the level below. Using a small
sample (3%) allows a small memory occupation; the march and the use of the
nearest neighbor to change levels quickly locate the query.Comment: 19 pages, 7 figures Proc. 14th Annu. ACM Sympos. Comput. Geom.,
106--115, 199
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