Kerri Morgan

Improved Optimal and Approximate Power Graph Compression for Clearer Visualisation of Dense Graphs

Drawings of highly connected (dense) graphs can be very difficult to read. Power Graph Analysis offers an alternate way to draw a graph in which sets of nodes with common neighbours are shown grouped into modules. An edge connected to the module then implies a connection to each member of the module. Thus, the entire graph may be represented with much less clutter and without loss of detail. A recent experimental study has shown that such lossless compression of dense graphs makes it easier to follow paths. However, computing optimal power graphs is difficult. In this paper, we show that computing the optimal power-graph with only one module is NP-hard and therefore likely NP-hard in the general case. We give an ILP model for power graph computation and discuss why ILP and CP techniques are poorly suited to the problem. Instead, we are able to find optimal solutions much more quickly using a custom search method. We also show how to restrict this type of search to allow only limited back-tracking to provide a heuristic that has better speed and better results than previously known heuristics.

Approximation algorithms for the maximum induced planar and outerplanar subgraph problems.

The task of finding the largest subset of vertices of a graph that induces a planar subgraph is known as the Maximum Induced Planar Subgraph problem (MIPS). In this paper, some new approximation algorithms for MIPS are introduced. The results of an extensive study of the performance of these and existing MIPS approximation algorithms on randomly generated graphs are presented. Efficient algorithms for finding large induced outerplanar graphs are also given. One of these algorithms is shown to find an induced outerplanar subgraph with at least 3n/(d + 5/3) vertices for graphs of n vertices with maximum degree at most d. The results presented in this paper indicate that most existing algorithms perform substantially better than the existing lower bounds indicate.

Practical adaptive search trees with performance bounds

Dynamic binary search trees are a fundamental class of dictionary data structure. Amongst these, the splay tree is space efficient and has amortized running-time bounds. In practice, splay trees perform best when the access sequence has regions of atypical items. Continuing a tradition started by Sleator and Tarjan themselves, we introduce a relaxed version, the α-Frequent Tree, that performs fewer rotations than the standard splay tree. We prove that the α-frequent trees inherit many of the distribution-sensitive properties of splay trees. Meanwhile, Conditional Rotation trees [Cheetham et al.] maintain access counters - one at each node - and have an excellent experimental reputation. By adding access counters to α-frequent trees, we create Splay Conditional Rotation (SCR) trees. These have the experimental performance of other counter-based trees, and the amortized bounds of splay trees.

An infinite family of 2-connected graphs that have reliability factorisations

The reliability polynomial (G,p) gives the probability that a graph is connected given each edge may fail independently with probability 1p. Two graphs are reliability equivalent if they have the same reliability polynomial. It is well-known that the reliability polynomial can factorise into the reliability polynomials of the blocks of a graph. We give an infinite family of graphs that have no cutvertex but factorise into reliability polynomials of graphs of smaller order.Brown and Colbourn commented that it was not known if there exist pairs of reliability equivalent graphs with different chromatic numbers. We show that there are infinitely many pairs of reliability equivalent graphs where one graph in each pair has chromatic number 3 and the other graph has chromatic number 4.