Equivalence on Quadratic Lyapunov Function Based Algorithms in Stochastic Networks

Publications

Share / Export Citation / Email / Print / Text size:

International Journal of Advanced Network, Monitoring and Controls

Xi'an Technological University

Subject: Computer Science, Software Engineering

GET ALERTS

eISSN: 2470-8038

DESCRIPTION

0
Reader(s)
0
Visit(s)
0
Comment(s)
0
Share(s)

SEARCH WITHIN CONTENT

FIND ARTICLE

Volume / Issue / page

Related articles

VOLUME 2 , ISSUE 3 (September 2017) > List of articles

Equivalence on Quadratic Lyapunov Function Based Algorithms in Stochastic Networks

Li Hu / Gao Lu / Liu Jiaqi / Wang Shangyue

Keywords : Component, Lyapunov optimization, QLA, Lyapunov function, Backlog-utility performanc, Stochastic network optimization

Citation Information : International Journal of Advanced Network, Monitoring and Controls. Volume 2, Issue 3, Pages 179-185, DOI: https://doi.org/10.1109/iccnea.2017.56

License : (CC BY-NC-ND 4.0)

Published Online: 11-April-2018

ARTICLE

ABSTRACT

Quadratic Lyapunov function based Algorithms (QLAs) for stochastic network optimization problems, which are cross-layer scheduling algorithms designed by Lyapunov optimization technique, have been widely used and studied. In this paper, we investigate the performance of using Lyapunov drift and perturbation in QLAs. By analyzing attraction points and utility performance of four variants of OQLA (Original QLA), we examine the rationality of OQLA for using the first-order part of an upper bound of Lyapunov drift of a function L_1. It is proved that either using the real Lyapunov function (L_2) of networks under QLA or using the entire expression of Lyapunov drift does not improve backlog-utility performance. The linear relationship between the attraction point of backlog and perturbation in the queue is found. Simulations verify the results above.

Content not available PDF Share

FIGURES & TABLES

REFERENCES

L. Georgiadis, M. J. Neely, and L. Tassiulas, Resource allocation and cross-layer control in wireless networks. Now Publishers Inc, 2006.

 

M. J. Neely, Stochastic network optimization with application to communication and queueing systems. Morgan &Claypool Publishers, 2010, vol. 3, no. 1.

 

——, “Energy optimal control for time-varying wireless networks,” IEEE Transactions on Information Theory, vol. 52, no. 7, pp. 2915–2934, 2006.

 

R. Urgaonkar and M. J. Neely, “Optimal routing with mutual information accumulation in wireless networks,” in ConferenceRecord of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR),. IEEE, 2011, pp. 1602–1609.

 

L. Huang and M. J. Neely, “Utility optimal scheduling in energy harvesting networks,” in Proceedings of the Twelfth ACM International Symposium on Mobile Ad Hoc Networking and Computing. ACM, 2011, p. 21.

 

——, “Utility optimal scheduling in processing networks,” Performance Evaluation, vol. 68, no. 11, pp. 1002–1021, 2011.

 

M. J. Neely, “Stock market trading via stochastic network optimization,” in 49th IEEE Conference on Decision and Control (CDC). IEEE, 2010, pp. 2777–2784.

 

L. Huang and M. J. Neely, “Delay reduction via lagrange multipliers in stochastic network optimization,” IEEE Transactions on Automatic Control, vol. 56, no. 4, pp. 842–857, 2011.

 

L. Huang, “Deterministic mathematical optimization in stochastic network control,” Ph.D. dissertation, UNIVERSITY OF SOUTHERN CALIFORNIA, 2011.

 

M. J. Neely and R. Urgaonkar, “Opportunism, backpressure, and stochastic optimization with the wireless broadcast advantage,” in 42nd Asilomar Conference on Signals, Systems and Computers. IEEE, 2008, pp. 2152–2158.

 

LI Hu and etc.. “The detailed version of ‘Equivalence on Quadratic Lyapunov Function Based Algorithms in Stochastic Networks’”, https://figshare.com/s/4d4d27f38d5d07166c05, available since March 2017.

 

EXTRA FILES

COMMENTS