Capacity constrained assignment in spatial databases

Leong Hou U, Man Lung Yiu, Kyriakos Mouratidis, Nikos Mamoulis

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

56 Citations (Scopus)


Given a point set P of customers (e.g., WiFi receivers) and a point set Q of service providers (e.g., wireless access points), where each q ∈ Q has a capacity q.k, the capacity constrained assignment (CCA) is a matching M ⊆ Q × P such that (i) each point q ∈ Q (p ∈ P) appears at most k times (at most once) in M, (ii) the size of M is maximized (i.e., it comprises min{|P|, Σq∈Qq.k} pairs), and (iii) the total assignment cost (i.e., the sum of Euclidean distances within all pairs) is minimized. Thus, the CCA problem is to identify the assignment with the optimal overall quality; intuitively, the quality of q's service to p in a given (q, p) pair is anti-proportional to their distance. Although max-flow algorithms are applicable to this problem, they require the complete distance-based bipartite graph between Q and P. For large spatial datasets, this graph is expensive to compute and it may be too large to fit in main memory. Motivated by this fact, we propose efficient algorithms for optimal assignment that employ novel edge-pruning strategies, based on the spatial properties of the problem. Additionally, we develop approximate (i.e., suboptimal) CCA solutions that provide a trade-off between result accuracy and computation cost, abiding by theoretical quality guarantees. A thorough experimental evaluation demonstrates the efficiency and practicality of the proposed techniques.
Original languageEnglish
Title of host publicationSIGMOD 2008
Subtitle of host publicationProceedings of the ACM SIGMOD International Conference on Management of Data 2008
Number of pages13
Publication statusPublished - 10 Dec 2008
Externally publishedYes
Event2008 ACM SIGMOD International Conference on Management of Data 2008, SIGMOD'08 - Vancouver, BC, Canada
Duration: 9 Jun 200812 Jun 2008


Conference2008 ACM SIGMOD International Conference on Management of Data 2008, SIGMOD'08
CityVancouver, BC


  • Optimal assignment
  • Spatial databases

ASJC Scopus subject areas

  • Software
  • Information Systems


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