Abstract. A Nash equilibrium of a routing game is a stable state where no (randomizing) user could benefit from a unilateral deviation. We consider the simplest case of the parallel links network, where links are related. The Social Cost of a Nash equilibrium is the expected maximum latency. We seek the worst-case Nash equilibrium [E. Koutsoupias and C. H. Papadimitriou, Comput. Sci. Rev., 3 (2009), pp. 65–69], which maximizes Social Cost. We continue the study of the fully mixed Nash equilibrium conjecture, abbreviated as the FMNE Conjecture, stating that the worst-case Nash equilibrium is the fully mixed Nash equilibrium, where each user assigns strictly positive probability to every link. Through an extensive combinatorial analysis, we confirm the FMNE Conjecture for the two basic cases where there are either (i) two users on related links, or (ii) many users on two identical links.

The problem of performing t tasks on n asynchronous or undependable processors is a basic problem in parallel and distributed computing. We consider an abstraction of this problem called the Write-All problem— using n processors write 1's into all locations of an array of size t. The most efficient known deterministic asynchronous algorithms for this problem are due to Anderson and Woll. The first class of algorithms has work complexity of Ο(t . n ε), for n ≰ ty and any ε > 0, and they are the best known for the full range of processors (n = t). To schedule the work of the processors, the algorithms use sets of q permutations on [q] (q ≰ n) that have certain combinatorial properties. Instantiating such an algorithm for a specific ε either requires substantial pre-processing (exponential in 1/ε2) to find the requisite permutations, or imposes a prohibitive constant (exponential in 1/ε3) hidden by the asymptotic analysis. The second class deals with the specific case of t = nu, u ≰ 2, and these algorithms have work complexity of Ο(t log t). They also use sets of permutations with the same combinatorial properties. However instantiating these algorithms requires exponential in n preprocessing to find the permutations. To alleviate this costly instantiation Kanellakis and Shvartsman proposed a simple way of computing the permutation schedules. They conjectured that their construction has the desired properties but they provided no analysis.

The bipartite crossing number problem is studied and a connection between this problem and the linear arrangement problem is established. A lower bound and an upper bound for the optimal number of crossings are derived, where the main terms are the optimal arrangement values. Two polynomial time approximation algorithms for the bipartite crossing number are obtained. The performance guarantees are O(log n) and O(log 2 n ) times the optimal, respectively, for a large class of bipartite graphs on n vertices. No polynomial time approximation algorithm which could generate a provably good solution had been known. For a tree, a formula is derived that expresses the optimal number of crossings in terms of the optimal value of the linear arrangement and the degrees, resulting in an O(n 1.6 ) time algorithm for computing the bipartite crossing number. The problem of computing a maximum weight biplanar subgraph of an acyclic graph is also studied and a linear time algorithm for solving it is derived. No polynomial time algorithm for this problem was known, and the unweighted version of the problem had been known to be NP-hard, even for planar bipartite graphs of degree at most 3.

We study virtual path layouts in a very popular type of fast interconnection networks, namely asynchronous transfer mode (ATM) networks. One of the main problems in such networks is to construct path layouts that minimize the hop-number (i.e., the number of virtual paths between any two nodes) as a function of the edge congestion c (i.e., the number of virtual paths going through a link). In this paper we construct for any n vertex network H and any c a virtual path layout with hop-number $O(\frac{diam(H)\log\Delta}{\log c})$, where diam(H) is the diameter of the network H and $\Delta$ is its maximum degree. Involving a general lower bound from [E. Kranakis, D. Krizanc, and A. Pelc, Seventh IEEE Symposium on Parallel and Distributed Processing, IEEE Computer Society, 1995, pp. 662--668], we see that these hop-numbers are optimal for bounded degree networks with the diameter O(log n) for any congestion c. In the case of unbounded degree networks (with the diameter O(log n)) these hop-numbers are optimal for any $c\geq\Delta$. For instance, this gives optimal hop-numbers for hypercube related networks. Moreover, we improve known results for paths and meshes and prove optimal hop-numbers for hypercubes.