Multidimensional online tracking

  • Authors:
  • Ke Yi;Qin Zhang

  • Affiliations:
  • Hong Kong University of Science and Technology, China;Hong Kong University of Science and Technology, China

  • Venue:
  • ACM Transactions on Algorithms (TALG)
  • Year:
  • 2012

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Abstract

We propose and study a new class of online problems, which we call online tracking. Suppose an observer, say Alice, observes a multivalued function f: Z+ → Zd over time in an online fashion, that is, she only sees f(t) for t≤tnow where tnow is the current time. She would like to keep a tracker, say Bob, informed of the current value of f at all times. Under this setting, Alice could send new values of f to Bob from time to time, so that the current value of f is always within a distance of Δ to the last value received by Bob. We give competitive online algorithms whose communication costs are compared with the optimal offline algorithm that knows the entire f in advance. We also consider variations of the problem where Alice is allowed to send predictions to Bob, to further reduce communication for well-behaved functions. These online tracking problems have a variety of application, ranging from sensor monitoring, location-based services, to publish/subscribe systems.