Selecting Spatially-Relevant Information Providers

The on-demand binding between applications and information providers in loosely-coupled sensor-enabled systems raises the challenge for selecting the providers (i.e., sensor networks) supplying the most “relevant” sensory information. This paper focuses on spatial relevancy of sensory information determined by the quality and value of the desired and provided information. Specifically, the paper introduces a metric for spatial relevancy based on the concepts of quality of information (QoI) functions. We introduce expansion-proof descriptions of the QoI functions and we use those along with the the relevancy metric to (a) identify the most relevant provider among a collection of sensory information providers; and (b) select multiple providers with the objective to: (b:1) identify the minimum number of providers that cumulatively maximizes relevancy; and (b:2) considering the cost in engaging with providers, select the subset of providers that cumulatively maximizes the overall relevancy subject to a budgetary constraint. The performance and robustness of the proposed solutions are studied both analytically and by simulation for a number of provider topologies.

By: George Tychogiorgos, Chatschik Bisdikian

Published in: RC25321 in 2012


This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.


Questions about this service can be mailed to .