Decentralized Chernoff Test in Sensor Networks

We propose a decentralized, sequential and adaptive hypothesis test in sensor networks, which extends Chernoff's test to a decentralized setting. We show that the proposed test achieves the same asymptotic optimality of the original one, minimizing the expected cost required to reach a decision plus the expected cost of making a wrong decision, when the observation cost per unit time tends to zero. We also show that the proposed test is parsimonious in terms of communications. Namely, in the regime of vanishing observation cost per unit time, the expected number of channel uses required by each sensor to complete the test converges to four.

• Publication year

  2018

• Venue

  International Symposium on Information Theory

• Publication date

  2018-06-01

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1109/ISIT.2018.8437755
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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