arXiv subjects

Costas Busch

Publications and source records attributed to Costas Busch.

25 records · Page 2Linked to original sources

arXiv2010

Oblivious Buy-at-Bulk in Planar Graphs

In the oblivious buy-at-bulk network design problem in a graph, the task is to compute a fixed set of paths for every pair of source-destinations in the graph, such that any set of demands can be routed along these paths. The demands could be aggregated at intermediate edges where the fusion-cost is specified by a canonical (non-negative concave) function $f$. We give a novel algorithm for planar graphs which is oblivious with respect to the demands, and is also oblivious with respect to the fusion function $f$. The algorithm is deterministic and computes the fixed set of paths in polynomial time, and guarantees a $O(\log n)$ approximation ratio for any set of demands and any canonical fusion function $f$, where $n$ is the number of nodes. The algorithm is asymptotically optimal, since it is known that this problem cannot be approximated with better than $Ω(\log n)$ ratio. To our knowledge, this is the first tight analysis for planar graphs, and improves the approximation ratio by a factor of $\log n$ with respect to previously known results.

cs.DS↗

arXiv2010

A Competitive Analysis for Balanced Transactional Memory Workloads

We consider transactional memory contention management in the context of balanced workloads, where if a transaction is writing, the number of write operations it performs is a constant fraction of its total reads and writes. We explore the theoretical performance boundaries of contention management in balanced workloads from the worst-case perspective by presenting and analyzing two new contention management algorithms. The first algorithm Clairvoyant is O(\surd s)-competitive, where s is the number of shared resources. This algorithm depends on explicitly knowing the conflict graph. The second algorithm Non-Clairvoyant is O(\surd s \cdot log n)-competitive, with high probability, which is only a O(log n) factor worse, but does not require knowledge of the conflict graph, where n is the number of transactions. Both of these algorithms are greedy. We also prove that the performance of Clairvoyant is tight since there is no contention management algorithm that is better than O((\surd s)^(1-ε))-competitive for any constant ε> 0, unless NP\subseteq ZPP. To our knowledge, these results are significant improvements over the best previously known O(s) competitive ratio bound.

cs.DC↗

arXiv2010

An Oblivious Spanning Tree for Buy-at-Bulk Network Design Problems

We consider the problem of constructing a single spanning tree for the single-source buy-at-bulk network design problem for doubling-dimension graphs. We compute a spanning tree to route a set of demands (or data) along a graph to or from a designated root node. The demands could be aggregated at (or symmetrically distributed to) intermediate nodes where the fusion-cost is specified by a non-negative concave function $f$. We describe a novel approach for developing an oblivious spanning tree in the sense that it is independent of the number of data sources (or demands) and cost function at intermediate nodes. To our knowledge, this is the first paper to propose a single spanning tree solution to this problem (as opposed to multiple overlay trees). There has been no prior work where the tree is oblivious to both the fusion cost function and the set of sources (demands). We present a deterministic, polynomial-time algorithm for constructing a spanning tree in low doubling graphs that guarantees $\log^{3}D\cdot\log n$-approximation over the optimal cost, where $D$ is the diameter of the graph and $n$ the total number of nodes. With constant fusion-cost function our spanning tree gives a $O(\log^3 D)$-approximation for every Steiner tree to the root.

cs.DS↗

arXiv2010

Bottleneck Routing Games with Low Price of Anarchy

We study {\em bottleneck routing games} where the social cost is determined by the worst congestion on any edge in the network. In the literature, bottleneck games assume player utility costs determined by the worst congested edge in their paths. However, the Nash equilibria of such games are inefficient since the price of anarchy can be very high and proportional to the size of the network. In order to obtain smaller price of anarchy we introduce {\em exponential bottleneck games} where the utility costs of the players are exponential functions of their congestions. We find that exponential bottleneck games are very efficient and give a poly-log bound on the price of anarchy: $O(\log L \cdot \log |E|)$, where $L$ is the largest path length in the players' strategy sets and $E$ is the set of edges in the graph. By adjusting the exponential utility costs with a logarithm we obtain games whose player costs are almost identical to those in regular bottleneck games, and at the same time have the good price of anarchy of exponential games.

cs.GT↗

arXiv2010

Window-Based Greedy Contention Management for Transactional Memory

We consider greedy contention managers for transactional memory for M x N execution windows of transactions with M threads and N transactions per thread. Assuming that each transaction conflicts with at most C other transactions inside the window, a trivial greedy contention manager can schedule them within CN time. In this paper, we show that there are much better schedules. We present and analyze two new randomized greedy contention management algorithms. The first algorithm Offline-Greedy produces a schedule of length O(C + N log(MN)) with high probability, and gives competitive ratio O(log(MN)) for C <= N log(MN). The offline algorithm depends on knowing the conflict graph. The second algorithm Online-Greedy produces a schedule of length O(C log(MN) + N log^2(MN)) with high probability which is only a O(log(NM)) factor worse, but does not require knowledge of the conflict graph. We also give an adaptive version which achieves similar worst-case performance and C is determined on the fly under execution. Our algorithms provide new tradeoffs for greedy transaction scheduling that parameterize window sizes and transaction conflicts within the window.

cs.DC↗

arXiv2009

The Impact of Exponential Utility Costs in Bottleneck Routing Games

We study bottleneck routing games where the social cost is determined by the worst congestion on any edge in the network. Bottleneck games have been studied in the literature by having the player's utility costs to be determined by the worst congested edge in their paths. However, the Nash equilibria of such games are inefficient since the price of anarchy can be very high with respect to the parameters of the game. In order to obtain smaller price of anarchy we explore {\em exponential bottleneck games} where the utility costs of the players are exponential functions on the congestion of the edges in their paths. We find that exponential bottleneck games are very efficient giving a poly-log bound on the price of anarchy: O(log L log |E|), where L is the largest path length in the players strategy sets and E is the set of edges in the graph.

cs.GT↗

arXiv2008

Bicretieria Optimization in Routing Games

Two important metrics for measuring the quality of routing paths are the maximum edge congestion $C$ and maximum path length $D$. Here, we study bicriteria in routing games where each player $i$ selfishly selects a path that simultaneously minimizes its maximum edge congestion $C_i$ and path length $D_i$. We study the stability and price of anarchy of two bicriteria games: - {\em Max games}, where the social cost is $\max(C,D)$ and the player cost is $\max(C_i, D_i)$. We prove that max games are stable and convergent under best-response dynamics, and that the price of anarchy is bounded above by the maximum path length in the players' strategy sets. We also show that this bound is tight in worst-case scenarios. - {\em Sum games}, where the social cost is $C+D$ and the player cost is $C_i+D_i$. For sum games, we first show the negative result that there are game instances that have no Nash-equilibria. Therefore, we examine an approximate game called the {\em sum-bucket game} that is always convergent (and therefore stable). We show that the price of anarchy in sum-bucket games is bounded above by $C^* \cdot D^* / (C^* + D^*)$ (with a poly-log factor), where $C^*$ and $D^*$ are the optimal coordinated congestion and path length. Thus, the sum-bucket game has typically superior price of anarchy bounds than the max game. In fact, when either $C^*$ or $D^*$ is small (e.g. constant) the social cost of the Nash-equilibria is very close to the coordinated optimal $C^* + D^*$ (within a poly-log factor). We also show that the price of anarchy bound is tight for cases where both $C^*$ and $D^*$ are large.

cs.GT↗