Best upgrade plans for single and multiple source-destination pairs

In this paper, we study Resource Constrained Best Upgrade Plan (BUP) computation in road network databases. Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. In the single-pair version of BUP, the input includes a source and a destination in G, and a budget B (resource constraint). The goal is to identify which upgradable edges should be upgraded so that the shortest path distance between source and destination (in the updated network) is minimized, without exceeding the available budget for the upgrade. In the multiple-pair version of BUP, a set Q of source-destination pairs is given, and the problem is to choose for upgrade those edges that lead to the smallest sum of shortest path distances across all pairs in Q, subject to budget constraint B. In addition to transportation networks, the BUP query arises in other domains too, such as telecommunications. We propose a framework for BUP processing and evaluate it with experiments on large, real road networks.

[1]  E. Bretagne.  Multi-Bid Auctions for Bandwidth Allocation in Communication Networks , 2005 .

[2]  Mark Handley,et al.  Topologically-aware overlay construction and server selection , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[3]  Natashia Boland,et al.  Improved preprocessing, labeling and scaling algorithms for the Weight‐Constrained Shortest Path Problem , 2003, Networks.

[4]  Kyriakos Mouratidis,et al.  Best Upgrade Plans for Large Road Networks , 2013, SSTD.

[5]  Mostafa H. Ammar,et al.  Dynamic Topology Configuration in Service Overlay Networks: A Study of Reconfiguration Policies , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[6]  Celso C. Ribeiro,et al.  A heuristic approach to hard constrained shortest path problems , 1985, Discret. Appl. Math..

[7]  Sibel A. Alumur,et al.  Network hub location problems: The state of the art , 2008, Eur. J. Oper. Res..

[8]  Heng Tao Shen,et al.  Multi-source Skyline Query Processing in Road Networks , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[9]  John N. Tsitsiklis,et al.  Efficiency loss in a network resource allocation game: the case of elastic supply , 2004, IEEE Transactions on Automatic Control.

[10]  Alexandros Nanopoulos,et al.  Continuous range monitoring of mobile objects in road networks , 2008, Data Knowl. Eng..

[11]  Kurt Mehlhorn,et al.  Resource Constrained Shortest Paths , 2000, ESA.

[12]  Sakti Pramanik,et al.  An Efficient Path Computation Model for Hierarchically Structured Topographical Road Maps , 2002, IEEE Trans. Knowl. Data Eng..

[13]  Dongjoo Park,et al.  Upgrading Arc Median Shortest Path Problem for an Urban Transportation Network , 2009 .

[14]  Hans-Peter Kriegel,et al.  Hierarchical Graph Embedding for Efficient Query Processing in Very Large Traffic Networks , 2008, SSDBM.

[15]  Marta M. B. Pascoal,et al.  A new implementation of Yen’s ranking loopless paths algorithm , 2003, 4OR.

[16]  Jeffrey Xu Yu,et al.  Finding time-dependent shortest paths over large graphs , 2008, EDBT '08.

[17]  Edoardo Amaldi,et al.  Optimization Models for the Radio Planning of Wireless Mesh Networks , 2007, Networking.

[18]  Lili Qiu,et al.  Overlay Node Placement: Analysis, Algorithms and Impact on Applications , 2007, 27th International Conference on Distributed Computing Systems (ICDCS '07).

[19]  Li Zhang,et al.  Upgrading arc problem with budget constraint , 2005, ACM-SE 43.

[20]  R. Boorstyn,et al.  Large-Scale Network Topological Optimization , 1977, IEEE Trans. Commun..

[21]  Prasant Mohapatra,et al.  On investigating overlay service topologies , 2007, Comput. Networks.

[22]  Jean C. Walrand,et al.  An efficient Nash-implementation mechanism for network resource allocation , 2010, Autom..

[23]  Timothy J. Lowe,et al.  Upgrading arcs to minimize the maximum travel time in a network , 2006, Networks.

[24]  Danny Raz,et al.  A simple efficient approximation scheme for the restricted shortest path problem , 2001, Oper. Res. Lett..

[25]  Torben Bach Pedersen,et al.  Nearest neighbor queries in road networks , 2003, GIS '03.

[26]  Patrick Maillé,et al.  Multibid auctions for bandwidth allocation in communication networks , 2004, IEEE INFOCOM 2004.

[27]  Ronald L. Rivest,et al.  Introduction to Algorithms, Second Edition , 2001 .

[28]  Michel Minoux,et al.  Networks synthesis and optimum network design problems: Models, solution methods and applications , 1989, Networks.

[29]  Parviz Kermani,et al.  MENTOR: an algorithm for mesh network topological optimization and routing , 1991, IEEE Trans. Commun..

[30]  Refael Hassin,et al.  Approximation Schemes for the Restricted Shortest Path Problem , 1992, Math. Oper. Res..

[31]  Yufei Tao,et al.  Query Processing in Spatial Network Databases , 2003, VLDB.

[32]  Antonio Capone,et al.  Models and Algorithms for the Design of Service Overlay Networks , 2008, IEEE Transactions on Network and Service Management.

[33]  Ronald L. Rivest,et al.  Introduction to Algorithms , 1990 .

[34]  Nicos Christofides,et al.  An algorithm for the resource constrained shortest path problem , 1989, Networks.

[35]  Cyrus Shahabi,et al.  A Road Network Embedding Technique for K-Nearest Neighbor Search in Moving Object Databases , 2003, GeoInformatica.

[36]  Cyrus Shahabi,et al.  A Road Network Embedding Technique for K-Nearest Neighbor Search in Moving Object Databases , 2002, GIS '02.

[37]  Gabriel Y. Handler,et al.  A dual algorithm for the constrained shortest path problem , 1980, Networks.

[38]  Eran Omri,et al.  Optimizing Budget Allocation in Graphs , 2014, CCCG.

[39]  Thomas H. Cormen,et al.  Introduction to algorithms [2nd ed.] , 2001 .