## Proceedings of the Eighth Workshop on Algorithm Engineering and Experiments and the Third Workshop on Analytic Algorithmics and CombinatoricsThe annual Workshop on Algorithm Engineering and Experiments (ALENEX) provides a forum for the presentation of original research in all aspects of algorithm engineering, including the implementation and experimental evaluation of algorithms and data structures. The workshop was sponsored by SIAM, the Society for Industrial and Applied Mathematics, and SIGACT, the ACM Special Interest Group on Algorithms and Computation Theory. The aim of ANALCO is to provide a forum for the presentation of original research in the analysis of algorithms and associated combinatorial structures. |

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### Contents

Summorizing Spotid Doto Stredms Using ClusterHulls | 26 |

4 DistOnceSensitive Bloom Filters | 49 |

The Art of Proximity Sedrching | 65 |

Using Markov Chains to Design Algorithms for BoundedSpoce OnLine Bin Cover | 75 |

Doto Reduction Exoct ond Heuristic Algorithms for Clique Cover | 86 |

Fast Reconfiguration of Doto Placement in Parallel Disks | 95 |

ForceDirected Approoches to Sensor Locolzotion | 108 |

Compoct Routing on Power Low Grophs with Additive Stretch | 119 |

Engineering MultiLevel Overloy Grophs for ShortestPoth Queries | 156 |

17 Optimol Incremental Sorting | 171 |

Deterministic Rondom Wolks | 185 |

Bindry Trees Left ond Right Paths WKB Exponsions ond Poinlevé Tronscendents | 198 |

New Results onc Open Problems for Deletion Chonnels | 222 |

A RondomSurfer WebGroph Model | 238 |

Exploring the Average Values of Booleon Functions vid Asymptotics dnd Experimentotion | 253 |

Random Portitions with Ports in the Ronge of d Polynomid | 273 |

Efficient PointtoPoint Shortest Path Algorithms | 129 |

Distributed Routing in SmollWorld Networks | 144 |

### Common terms and phrases

algorithm analysis applications approach approximation arrangement assigned assume average bins bound called clique close clusters complexity component compute connected consider constant construction containing convex cost cover data sets data structure defined demand denote depth direction disk distance distribution edges efficient elements error estimate exact example existing expected experiments face Figure function given graph hulls implementation improve initial input instances landmarks layout Lemma length maps measures method Minkowski sum networks nodes Note observed obtained optimal parameter performance planar points position practical preprocessing present probability problem Proof query random range reach REAL require respect round routing Rule running sample scheme selected shape shortest path space step stream structure Table takes tasks Theorem tion tree University values vertex vertices walk