Cloud-Cluster Architecture for Detection in Intermittently Connected Sensor Networks

Michal Yemini, Stephanie Gil, Andrea J. Goldsmith

Research output: Contribution to journalArticlepeer-review

Abstract

We consider a centralized detection problem where sensors experience noisy measurements and intermittent connectivity to a centralized fusion center. The sensors collaborate locally within predefined sensor clusters and fuse their noisy sensor data to reach a common local estimate of the detected event in each cluster. The connectivity of each sensor cluster is intermittent and depends on the available communication opportunities of the sensors to the fusion center. Upon receiving the estimates from all the connected sensor clusters the fusion center fuses the received estimates to make a final determination regarding the occurrence of the event across the deployment area. We refer to this hybrid communication scheme as a cloud-cluster architecture. We propose a method for optimizing the decision rule for each cluster and analyzing the expected detection performance resulting from our hybrid scheme. Our method is tractable and addresses the high computational complexity caused by heterogeneous sensors’ and clusters’ detection quality, heterogeneity in their communication opportunities, and non-convexity of the loss function. Our analysis shows that clustering the sensors provides resilience to noise in the case of low sensor communication probability with the cloud. For larger clusters, a steep improvement in detection performance is possible even for a low communication probability by using our cloud-cluster architecture.

Original languageEnglish (US)
Pages (from-to)1
Number of pages1
JournalIEEE Transactions on Wireless Communications
DOIs
StateAccepted/In press - 2022

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Keywords

  • Cloud computing
  • Computer architecture
  • Decision making
  • Loss measurement
  • Noise measurement
  • Robot sensing systems
  • Wireless communication

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