Applying Force-Directed Placer to Wafer Scale Placement

A placement algorithm for discretionary wiring WSI system, WFDP, is proposed in this paper. WFDP employes force-directed placement algorithm. First the relative locations of macro circuit component are determined. In the phase of determining the real location of the circuit component, it avoids the problem of determining the real location of arbitrary component by employing divide-conquer strategy and removing the hierarchical division. Its computation is much more simpler than other homologous algorithm. A simple model used to estimate the quality of placement is also proposed. Although the WFDP is aimed at WSI, it can also be used in the placement of other redundancy-oriented device or system such as RVLSI, etc.

Enhancing Clustering Stability in VANET: A Spectral Clustering Based Approach

Vehicles can establish a collaborative environment cognition through sharing the original or processed sensor data from the vehicular sensors and status map. Clustering in the vehicular ad-hoc network(VANET) is crucial for enhancing the stability of the collaborative environment. In this paper, the problem for clustering is innovatively transformed into a cutting graph problem. A novel clustering algorithm based on the Spectral Clustering algorithm and the improved force-directed algorithm is designed. It takes the average lifetime of all clusters as an optimization goal so that the stability of the entire system can be enhanced. A series of close-to-practical scenarios are generated by the Simulation of Urban Mobility(SUMO). The numerical results indicate that our approach has superior performance in maintaining whole cluster stability.

Simple Algorithms for Network Visualization:A Tutorial

The graph drawing and information visualization communities have developed many sophisticated techniques for visualizing network data, often involving complicated algorithms that are difficult for the uninitiated to learn. This article is intended for beginners who are interested in programming their own network visualizations, or for those curious about some of the basic mechanics of graph visualization. Four easy-to-program network layout techniques are discussed, with details given for implementing each one： force-directed node-link diagrams, arc diagrams, adjacency matrices, and circular layouts. A Java applet demonstrating these layouts, with open source code, is available at http：//www.michaelmcguffin.com/research/simpleNetVis/. The end of this article also briefly surveys research topics in graph visualization, pointing readers to references for further reading.

Planning-oriented optimization strategy for visualizing power distribution networks:from global to local

The spatial distribution of power facilities is uneven,thereby making the topology of geographical wiring diagrams(GWDs)based on the actual coordinates unclear.A single-line diagram has the advantage of a clear topology but it lacks spatial locations.A GWD has the advantage of accurate spatial locations but it lacks a clear topology.Visualizing distribution networks for planning requires both features.We proposed a new planning-oriented method for optimizing the visualization of distribution networks.From the global perspective,we proposed an improved force-directed(FD)algorithm by introducing a space restriction strategy and node–edge repulsion strategy to promote the expansion of the distance between distribution facilities within a limited buffer.We then constructed the constrained Delaunay triangulation to identify the compact districts(CDs)and used a genetic algorithm to optimize the parameters for the improved FD algorithm.A novel visualization evaluation indicator was also proposed for quantitatively assessing the visualizations.From a local perspective,the fisheye algorithm was used to optimize the CDs to further improve the visualization of the distribution network.We verified the proposed methods with real-world data.We used limited spatial displacement in exchange for maximum topology clarity to balance the accurate spatial location and topology clarity.