A Distributed Hybrid Event-Time-Driven Scheme for Optimization over Sensor Networks

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

9 Scopus Citations
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Original languageEnglish
Pages (from-to)7199-7208
Journal / PublicationIEEE Transactions on Industrial Electronics
Issue number9
Online published10 Oct 2018
Publication statusPublished - Sep 2019


Motivated by application to sensor networks, this paper studies distributed algorithms for solving optimization problems such as on sensor data gathering, network utility, and mobile vehicle localization. A type of distributed hybrid optimization algorithms based on the coordinate descent method is presented and analyzed. The proposed optimization algorithms differ from the existing ones since the hybrid driven scheme allows more choices of actuation time on sensor nodes. Applying the proposed algorithms, each sensor node is driven in a hybrid event-time manner, which removes the requirement of strict time synchronization, and allows a tradeoff between communications and computation performances. The convergence and optimality results are established for the hybrid optimization algorithms, and illustrative examples are given to verify the theoretical results, showing the tradeoff between communications and computation performances.

Research Area(s)

  • Distributed algorithm, hybrid event-time-driven scheme, optimization, sensor network