Peter Sanders

Polynomial time algorithms for multicast network code construction

The famous max-flow min-cut theorem states that a source node s can send information through a network (V, E) to a sink node t at a rate determined by the min-cut separating s and t. Recently, it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediate nodes are allowed to re-encode the information they receive. We demonstrate examples of networks where the achievable rates obtained by coding at intermediate nodes are arbitrarily larger than if coding is not allowed. We give deterministic polynomial time algorithms and even faster randomized algorithms for designing linear codes for directed acyclic graphs with edges of unit capacity. We extend these algorithms to integer capacities and to codes that are tolerant to edge failures.

Simple linear work suffix array construction

A suffix array represents the suffixes of a string in sorted order. Being a simpler and more compact alternative to suffix trees, it is an important tool for full text indexing and other string processing tasks. We introduce the skew algorithm for suffix array construction over integer alphabets that can be implemented to run in linear time using integer sorting as its only nontrivial subroutine: 1. recursively sort suffixes beginning at positions i mod 3 ≠ 0. 2. sort the remaining suffixes using the information obtained in step one. 3. merge the two sorted sequences obtained in steps one and two. The algorithm is much simpler than previous linear time algorithms that are all based on the more complicated suffix tree data structure. Since sorting is a well studied problem, we obtain optimal algorithms for several other models of computation, e.g. external memory with parallel disks, cache oblivious, and parallel. The adaptations for BSP and EREW-PRAM are asymptotically faster than the best previously known algorithms.

Engineering Route Planning Algorithms

Algorithms for route planning in transportation networks have recently undergone a rapid development, leading to methods that are up to three million times faster than Dijkstras algorithm. We give an overview of the techniques enabling this development and point out frontiers of ongoing research on more challenging variants of the problem that include dynamically changing networks, time-dependent routing, and flexible objective functions.

Polynomial time algorithms for network information flow

The famous max-flow min-cut theorem states that a source node s can send information through a network (V,E) to a sink node t at a data rate determined by the min-cut separating s and t. Recently it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediate nodes are allowed to reencode the information they receive. In contrast, we present graphs where without coding the rate must be a factor Ω(log|V|) smaller. However, so far no fast algorithms for constructing appropriate coding schemes were known. Our main result are polynomial time algorithms for constructing coding schemes for multicasting at the maximal data rate.

Linear work suffix array construction

Suffix trees and suffix arrays are widely used and largely interchangeable index structures on strings and sequences. Practitioners prefer suffix arrays due to their simplicity and space efficiency while theoreticians use suffix trees due to linear-time construction algorithms and more explicit structure. We narrow this gap between theory and practice with a simple linear-time construction algorithm for suffix arrays. The simplicity is demonstrated with a C++ implementation of 50 effective lines of code. The algorithm is called DC3, which stems from the central underlying concept of difference cover. This view leads to a generalized algorithm, DC, that allows a space-efficient implementation and, moreover, supports the choice of a space--time tradeoff. For any v ∈ [1,&nradic;], it runs in O(vn) time using O(n/&vradic;) space in addition to the input string and the suffix array. We also present variants of the algorithm for several parallel and hierarchical memory models of computation. The algorithms for BSP and EREW-PRAM models are asymptotically faster than all previous suffix tree or array construction algorithms.

Highway hierarchies hasten exact shortest path queries

We present a new speedup technique for route planning that exploits the hierarchy inherent in real world road networks. Our algorithm preprocesses the eight digit number of nodes needed for maps of the USA or Western Europe in a few hours using linear space. Shortest (i.e. fastest) path queries then take around eight milliseconds to produce exact shortest paths. This is about 2 000 times faster than using Dijkstra’s algorithm.

Route Planning in Transportation Networks

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.

Δ-stepping: a parallelizable shortest path algorithm

The single source shortest path problem for arbitrary directed graphs with n nodes, m edges and nonnegative edge weights can sequentially be solved using O(n ċ log n + m) operations. However, no work-efficient parallel algorithm is known that runs in sublinear time for arbitrary graphs. In this paper we present a rather simple algorithm for the single source shortest path problem. Our new algorithm, which we call Delta-stepping, can be implemented very efficiently in sequential and parallel setting for a large class of graphs. For random edge weights and arbitrary graphs with maximum node degree d, sequential Δ-stepping needs O(n + m + d ċ L) total average-case time, where L denotes the maximum shortest path weight from the source node s to any node reachable from s. For example, this means linear time on directed graphs with constant maximum degree. Our best parallel version for a PRAM takes O(d ċ L ċ log n + log2 n) time and O(n + m + d ċ L ċ log n) work on average. For random graphs, even O(log2 n) time and O(n + m) work on average can be achieved. We also discuss how the algorithm can be adapted to work with nonrandom edge weights and how it can be implemented on distributed memory machines. Experiments indicate that already a simple implementation of the algorithm achieves significant speedup on real machines.

Combining hierarchical and goal-directed speed-up techniques for dijkstra's algorithm

In recent years, highly effective hierarchical and goal-directed speed-up techniques for routing in large road networks have been developed. This article makes a systematic study of combinations of such techniques. These combinations turn out to give the best results in many scenarios, including graphs for unit disk graphs, grid networks, and time-expanded timetables. Besides these quantitative results, we obtain general insights for successful combinations.

Space Efficient Hash Tables With Worst Case Constant Access Time

Abstract We generalize Cuckoo Hashing to d-ary Cuckoo Hashing and show how this yields a simple hash table data structure that stores n elements in (1 + ε)n memory cells, for any constant ε > 0. Assuming uniform hashing, accessing or deleting table entries takes at most d=O (ln (1/ε)) probes and the expected amortized insertion time is constant. This is the first dictionary that has worst case constant access time and expected constant update time, works with (1 + ε)n space, and supports satellite information. Experiments indicate that d = 4 probes suffice for ε ≈ 0.03. We also describe variants of the data structure that allow the use of hash functions that can be evaluated in constant time.