Skip to main content
SpringerLink
Log in

Probabilistic quantization of unbiased broadcast gossip algorithms for consensus in distributed networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

In this paper, probabilistic quantization on Unbiased Broadcast Gossip Algorithms (UBGA) is introduced to adapt to the limited bandwidth of distributed network channels. This innovative quantized consensus algorithm is called Quantized UBGA (QUBGA). By briefly describing the graph and time model, and reviewing UBGA, it is proved that QUBGA can converge in expectation and in the second moment for strongly connected digraphs. Furthermore, it is proved that the convergence rate of QUBGA is related to quantized resolution and topology structure. Performance analysis results are consistent with theoretical analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

References

  1. Aysal, T. C., Coates, M. J., & Rabbat, M. G. (2008). Distributed average consensus with dithered quantization. IEEE Transactions on Signal Processing, 56(10), 4905–4918. https://doi.org/10.1109/TSP.2008.927071.

    Article  MathSciNet  MATH  Google Scholar 

  2. Aysal, T. C., Yildiz, M. E., Sarwate, A. D., & Scaglione, A. (2009). Broadcast gossip algorithms for consensus. IEEE Transactions on Signal Processing, 57(7), 2748–2761. https://doi.org/10.1109/TSP.2009.2016247.

    Article  MathSciNet  MATH  Google Scholar 

  3. Boyd, S., Ghosh, A., Prabhakar, B., & Shah, D. (2006). Randomized gossip algorithms. IEEE Transactions on Information Theory, 52(6), 2508–2530. https://doi.org/10.1109/TIT.2006.874516.

    Article  MathSciNet  MATH  Google Scholar 

  4. Cai, K., & Ishii, H. (2011). Quantized consensus and averaging on gossip digraphs. IEEE Transactions on Automatic Control, 56(9), 2087–2100. https://doi.org/10.1109/TAC.2011.2107630.

    Article  MathSciNet  MATH  Google Scholar 

  5. Charalambous, T., Rabbat, M. G., Johansson, M., & Hadjicostis, C. N. (2016). Distributed finite-time computation of digraph parameters: Left-eigenvector, out-degree and spectrum. IEEE Transactions on Control of Network Systems, 3(2), 137–148. https://doi.org/10.1109/TCNS.2015.2428411.

    Article  MathSciNet  MATH  Google Scholar 

  6. Franceschelli, M., Giua, A., & Seatzu, C. (2011). Distributed averaging in sensor networks based on broadcast gossip algorithms. IEEE Sensors Journal, 11(3), 808–817. https://doi.org/10.1109/JSEN.2010.2064295.

    Article  Google Scholar 

  7. Kashyap, A., Basar, T., & Srikant, R. (2006). Quantized consensus. In: Proceedings of IEEE international symposium on information theory (pp. 635–639). https://doi.org/10.1109/ISIT.2006.261862.

  8. Lavaei, J., & Murray, R. M. (2012). Quantized consensus by means of gossip algorithm. IEEE Transactions on Automatic Control, 57(1), 19–32. https://doi.org/10.1109/TAC.2011.2160593.

    Article  MathSciNet  MATH  Google Scholar 

  9. Mazzarella, L., Sarlette, A., & Ticozzi, F. (2015). Consensus for quantum networks: Symmetry from gossip interactions. IEEE Transactions on Automatic Control, 60(1), 158–172. https://doi.org/10.1109/TAC.2014.2336351.

    Article  MathSciNet  MATH  Google Scholar 

  10. Mingxiao, D., Xiaofeng, M., Zhe, Z., Xiangwei, W., & Qijun, C. (2017). A review on consensus algorithm of blockchain. In: Proceedings of IEEE international conference on systems, man, and cybernetics (SMC) (pp. 2567–2572). Banff, Canada. https://doi.org/10.1109/SMC.2017.8123011.

  11. Shang, S., Cuff, P., Hui, P., & Kulkarni, S. (2015). An upper bound on the convergence time for quantized consensus of arbitrary static graphs. IEEE Transactions on Automatic Control, 60(4), 1127–1132. https://doi.org/10.1109/TAC.2014.2342071.

    Article  MathSciNet  MATH  Google Scholar 

  12. Wan, Y., Yan, J., Lin, Z., Sheth, V., & Das, S. K. (2018). On the structural perspective of computational effectiveness for quantized consensus in layered uav networks. IEEE Transactions on Control of Network Systems. https://doi.org/10.1109/TCNS.2018.2813926.

    Google Scholar 

  13. Wang, N., Li, D., & Yin, Z. (2012). Broadcast gossip algorithm with quantization. In: Proceedings of 9th international conference on fuzzy systems and knowledge discovery (pp. 2143–2147). https://doi.org/10.1109/FSKD.2012.6234197.

  14. Wu, S., & Rabbat, M. G. (2013). Broadcast gossip algorithms for consensus on strongly connected digraphs. IEEE Transactions on Signal Processing, 61(16), 3959–3971. https://doi.org/10.1109/TSP.2013.2264056.

    Article  MathSciNet  MATH  Google Scholar 

  15. Yeow, K., Gani, A., Ahmad, R. W., Rodrigues, J. J. P. C., & Ko, K. (2018). Decentralized consensus for edge-centric internet of things: A review, taxonomy, and research issues. IEEE Access, 6, 1513–1524. https://doi.org/10.1109/ACCESS.2017.2779263.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, 150001, China

    Shaochuan Wu, Yuming Wei, Yulong Gao & Wenbin Zhang

Authors
  1. Shaochuan Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuming Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yulong Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wenbin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shaochuan Wu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The work was supported by the National Science Foundation of China under Grant No. 61671173.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, S., Wei, Y., Gao, Y. et al. Probabilistic quantization of unbiased broadcast gossip algorithms for consensus in distributed networks. Wireless Netw (2019). https://doi.org/10.1007/s11276-019-01969-w

Download citation

  • Published:

  • DOI: https://doi.org/10.1007/s11276-019-01969-w

Keywords

Search

Navigation