Distributed Spiral Optimization in Wireless Sensor Networks without Fusion Centers

A distributed spiral algorithm for distributed optimization in WSN is proposed. By forming a spiral-shape message passing scheme among clusters, without loss of estimation accuracy and convergence speed, the algorithm is proved to converge with a lower total transport cost than the distributed in-cluster algorithm.

[1]  Tijl Grootswagers,et al.  Even neurotypical children are heterogeneous: using multivariate decoding to improve individual subject analysis of lexico-semantic EEG data , 2019, bioRxiv.

[2]  Robert D. Nowak,et al.  Quantized incremental algorithms for distributed optimization , 2005, IEEE Journal on Selected Areas in Communications.

[3]  Mikael Johansson,et al.  On Distributed Optimization Using Peer-to-Peer Communications in Wireless Sensor Networks , 2008, 2008 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[4]  Mung Chiang,et al.  The value of clustering in distributed estimation for sensor networks , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[5]  Robert Nowak,et al.  Distributed optimization in sensor networks , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[6]  Dimitri P. Bertsekas,et al.  Incremental Subgradient Methods for Nondifferentiable Optimization , 2001, SIAM J. Optim..

[7]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.