George Karakostas

A 2 + ε approximation algorithm for the k -MST problem

For any ɛ > 0 we give a (2 + ɛ)-approximation algorithm for the problem of finding a minimum tree spanning any k vertices in a graph (k-MST), improving a 3-approximation algorithm by Garg [10]. As in [10] the algorithm extends to a (2 + ɛ)-approximation algorithm for the minimum tour that visits any k vertices, provided the edge costs satisfy the triangle inequality.

Edge pricing of multicommodity networks for heterogeneous selfish users

We examine how the selfish behavior of heterogeneous users in a network can be regulated through economic disincentives, i.e., through the introduction of appropriate taxation. One wants to impose taxes on the edges so that any traffic equilibrium reached by the selfish users who are conscious of both the travel latencies and the taxes will minimize the social cost, i.e., will minimize the total latency. We generalize previous results of Cole, Dodis and Roughgarden that held for a single origin-destination pair to the multicommodity setting. Our approach, which could be of independent interest, is based on the formulation of traffic equilibria as a nonlinear complementarity problem by Aashtiani and Magnanti (1981), We extend this formulation so that each of its solutions will give us a set of taxes that forces the network users to conform, at equilibrium, to a certain prescribed routing. We use the special nature of the prescribed minimum-latency flow in order to reduce the difficult nonlinear complementarity formulation to a pair of primal-dual linear programs. LP duality is then enough to derive our results.

A better approximation ratio for the vertex cover problem

We reduce the approximation factor for Vertex Cover to

Faster approximation schemes for fractional multicommodity flow problems

2 - \theta(\frac{1}{\sqrt{{\rm log} n}})

Approximation schemes for minimum latency problems

(instead of the previous

Stackelberg Strategies for Selfish Routing in General Multicommodity Networks

2- \theta(\frac{{\rm log log} n}{{\rm log}\ n})

Approximation Schemes for Minimum Latency Problems

, obtained by Bar-Yehuda and Even [3], and by Monien and Speckenmeyer[11]). The improvement of the vanishing factor comes as an application of the recent results of Arora, Rao, and Vazirani [2] that improved the approximation factor of the sparsest cut and balanced cut problems. In particular, we use the existence of two big and well-separated sets of nodes in the solution of the semidefinite relaxation for balanced cut, proven in [2]. We observe that a solution of the semidefinite relaxation for vertex cover, when strengthened with the triangle inequalities, can be transformed into a solution of a balanced cut problem, and therefore the existence of big well-separated sets in the sense of [2] translates into the existence of a big independent set.

Equilibria for networks with malicious users

We present fully polynomial approximation schemes for concurrent multicommodity flow problems that run in time independent of the number of commodities k. We show that by modifying the algorithms by Garg & Köönemann [5] and Fleischer [3] we can reduce their running time to a logarithmic dependence on k, and essentially match the running time of [3] for the maximum multicommodity flow problem.

On the existence of optimal taxes for network congestion games with heterogeneous users

The minimum latency problem, also known as the traveling repairman problem, is a variant of the traveling salesman problem in which the starting node of the tour is given and the goal is to minimize the sum of the arrival times at the other nodes. We present a quasi-polynomial time approximation scheme (QPTAS) for this problem when the instance is a weighted tree, when the nodes lie in Rd for some fixed d, and for planar graphs. We also present a polynomial time constant factor approximation algorithm for the general metric case. The currently best polynomial time approximation algorithm for general metrics, due to Goemans and Kleinberg, computes a 3.59approximation.

On the complexity of intersecting finite state automata and NL versus NP

Abstract A natural generalization of the selfish routing setting arises when some of the users obey a central coordinating authority, while the rest act selfishly. Such behavior can be modeled by dividing the users into an α fraction that are routed according to the central coordinator’s routing strategy (Stackelberg strategy), and the remaining 1−α that determine their strategy selfishly, given the routing of the coordinated users. One seeks to quantify the resulting price of anarchy, i.e., the ratio of the cost of the worst traffic equilibrium to the system optimum, as a function of α. It is well-known that for α=0 and linear latency functions the price of anarchy is at most 4/3 (J. ACM 49, 236–259, 2002). If α tends to 1, the price of anarchy should also tend to 1 for any reasonable algorithm used by the coordinator. We analyze two such algorithms for Stackelberg routing, LLF and SCALE. For general topology networks, multicommodity users, and linear latency functions, we show a price of anarchy bound for SCALE which decreases from 4/3 to 1 as α increases from 0 to 1, and depends only on α. Up to this work, such a tradeoff was known only for the case of two nodes connected with parallel links (SIAM J. Comput. 33, 332–350, 2004), while for general networks it was not clear whether such a result could be achieved, even in the single-commodity case. We show a weaker bound for LLF and also some extensions to general latency functions. The existence of a central coordinator is a rather strong requirement for a network. We show that we can do away with such a coordinator, as long as we are allowed to impose taxes (tolls) on the edges in order to steer the selfish users towards an improved system cost. As long as there is at least a fraction α of users that pay their taxes, we show the existence of taxes that lead to the simulation of SCALE by the tax-payers. The extension of the results mentioned above quantifies the improvement on the system cost as the number of tax-evaders decreases.