Shape sensitive geometric monitoring

Daniel Keren, Izchak Sharfman, Assaf Schuster, Avishay Livne

Research output: Contribution to journalArticlepeer-review


An important problem in distributed, dynamic databases is to continuously monitor the value of a function defined on the nodes, and check that it satisfies some threshold constraint. We introduce a monitoring method, based on a geometric interpretation of the problem, which enables to define local constraints at the nodes. It is guaranteed that as long as none of these constraints is violated, the value of the function did not cross the threshold. We generalize previous work on geometric monitoring, and solve two problems which seriously hampered its performance: as opposed to the constraints used so far, which depend only on the current values of the local data, here we incorporate their temporal behavior. Also, the new constraints are tailored to the geometric properties of the specific monitored function. In addition, we extend the concept of safe zones for the monitoring problem, and show that previous work on geometric monitoring is a special case of the proposed extension. Experimental results on real data reveal that the new approach reduces communication by up to three orders of magnitude in comparison to existing approaches, and considerably narrows the gap between achievable results and a newly defined lower bound on communication complexity.

Original languageEnglish
Article number5765956
Pages (from-to)1520-1535
Number of pages16
JournalIEEE Transactions on Knowledge and Data Engineering
Issue number8
StatePublished - 2012

Bibliographical note

Funding Information:
This submission greatly benefited from the remarks of three anonymous reviewers. The preliminary version of this work appeared in PODS 2008. Research partially supported by the European Commission under ICT-FP7-LIFT-255951 (Local Inference in Massively Distributed Systems).


  • Data streams
  • data modeling
  • distributed systems
  • geometric monitoring
  • shape

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics


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