July 31, 2018 / Leave a comment

Efficient message forwarding in mobile ad hoc network in disaster scenarios is challenging because location information on the boundary and interior nodes is often unavailable. Information related to boundary nodes can be used to design efficient routing protocols as well as to prolong the battery power of devices along the boundary of an ad hoc network. In this article, we developed an algorithm, CWBound, which discovers boundary nodes in a complex non-convex mobile ad hoc (CNCAH) networks.

Experiments show that the CWBound algorithm is at least 3 times faster than other state-of-the-art algorithms, and up to 400 times faster than classical force-directed algorithms. The experiments also confirmed that the CWBound algorithm achieved the highest accuracy (above 97% for 3 out of the 4 types of CNCAH networks) and sensitivity (90%) among the algorithms evaluated.

*The author’s version of a work that was accepted for publication can be downloaded from http://eric.lostcity-studio.com/wp-content/uploads/2019/08/CWBound.pdf.
***
Se-Hang, Cheong**, and Yain-Whar Si. "CWBound: boundary node detection algorithm for complex non-convex mobile ad hoc networks." The Journal of Supercomputing (2018): 1-20.

March 20, 2018 / Leave a comment

A graph layout problem, or visualization problem, refers to a set of nodes and a set of relationships (edges) built on top of this set of nodes, calculating the position of the nodes and drawing each edge as a line or curve.

One of the most important research directions in the visualization technology of graphs is the study of graph layout algorithms. The core content of the graph layout algorithm research is to study how to display the graph structure in a better way. E.g. force-directed algorithms.

The comprehensive workflow for classical force-directed algorithms are summarized below:

- Davidson and Harel Algorithm
- LinLog Algorithm
- Kamada-Kawai Algorithm
- Fruchterman Reingold Algorithm
- ForceAtlas2 Algorithm

*1. Davidson and Harel Algorithm*

*2. LinLog Algorithm*

*3. Kamada-Kawai Algorithm*

*4. Fruchterman Reingold Algorithm*

*5. ForceAtlas2 Algorithm*

November 23, 2017 / Leave a comment

CNCAHNetGenerator is written in Java 7, to enable the creation of CNCAH networks of arbitrary node and edge types.

If you use CNCAH Network Generator for your research/development, please cite the following paper: *Cheong, S.-H., Si, Y.-W., 2016. Accelerating the kamada-kawai algorithm for boundary detection in a mobile ad hoc network. ACM Transactions on Sensor Networks (TOSN) 13 (1), 3.* Download EndNote Format (.enw), Download BibteX Format (.bib)

# License & disclaimer

- CNCAHNetGenerator is freeware and under the LGPL License.
- You may not modify, reverse engineer, decompile, or disassemble the object code portions of this software.
- This software is provided “as is” and without any warranties expressed or implied, including, but not limited to, implied warranties of fitness for a particular purpose, and non-infringement. You expressly acknowledge and agree that use of the Software is at your sole risk.
- In no event shall the author be liable for any damages whatsoever (including, without limitation, damages for loss of business profits, business interruption, loss of business information, or other pecuniary loss) arising out of the use of or inability to use this software or documentation, even if the author has been advised of the possibility of such damages.

# Download

Current: CNCAHNetGenerator version 0.1, from September 14, 2017.

# Documentation

- CNCAHNetGenerator can generate CNCAH networks via the command line or the graphical interface. Example commands are shown in follows:

java -jar CNCAHNetGenerator.jar -help
java -jar CNCAHNetGenerator.jar -n -v 1000 -e 4000 -o star -sf shapes\star.shape
java -jar CNCAHNetGenerator.jar -n -v 1000 -e 4000 -o donut -sf shapes\donut.shape
java -jar CNCAHNetGenerator.jar -n -v 1000 -e 4000 -o smile -sf shapes\smile.shape
java -jar CNCAHNetGenerator.jar -n -v 1000 -e 4000 -o ushape -sf shapes\ushape.shape

November 23, 2017 / Leave a comment

CNCAH shapes generated by the CNCAHNetGenerator. You can download the dataset from here. (more…)

November 23, 2017 / Leave a comment

Force-directed algorithms such as the Kamada-Kawai algorithm have shown promising results for solving the boundary detection problem in a mobile ad hoc network. However, the classical Kamada-Kawai algorithm does not scale well when it is used in networks with large numbers of nodes. It also produces poor results in non-convex networks. To address these problems, this paper proposes an improved version of the Kamada-Kawai algorithm. The proposed extension includes novel heuristics and algorithms that achieve a faster energy level reduction. Our experimental results show that the improved algorithm can significantly shorten the processing time and detect boundary nodes with an acceptable level of accuracy.

*The author’s version of a work that was accepted for publication can be downloaded from Accelerating Kamada-Kawai for boundary detection in Mobile Ad-Hoc network.***
Se-Hang Cheong**, and Yain-Whar Si. "Accelerating the Kamada-Kawai algorithm for boundary detection in a mobile ad hoc network." ACM Transactions on Sensor Networks (TOSN) 13.1 (2016): 3.