|Appears in Collections:||Computing Science and Mathematics Technical Reports|
|Title:||Network Boundary Identification using Local Information|
Mouftah, Hussein T
|Citation:||Fayed M & Mouftah HT (2007) Network Boundary Identification using Local Information. TR-2007-05. School of Information Technology & Engineering, University of Ottawa.|
|Publisher:||School of Information Technology & Engineering, University of Ottawa|
|Abstract:||Detection of nodes on the network boundary is necessary for correct operation in many wireless applications. Many virtual coordinate constructions rely on the furthest set of nodes as beacons, and sensing applications may find useful the knowledge of the network edge. In this paper we propose local convex view (lcv) as a means to identify nodes close to the network edge. It is based on the idea that -hulls can capture the shape of a set of points, and motivated by the hypothesis that some structural information relevant to the network is buried within view of many nodes. The lcv differs from most previous methods in that it is a localized algorithm. Nodes using lcv establish neighbourhood coordinates where no location information is available a priori. In those cases where needed information is missing, we adopt a simple probabilistic model to decide the boundary status of a node. We identify two metrics for evaluation, and compare via simulation the performance of lcv against two methods with similar properties. In our experiments we find lcv to be consistent in its performance, and resilient to the impediments facing other methods.|
University of Ottawa
|Network Boundary Identification.pdf||Fulltext - Published Version||437.72 kB||Adobe PDF||Under Embargo until 3000-12-01 Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.