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Filters: Author is Ji, Y.  [Clear All Filters]
2019-09-11
Wang, D., Ma, Y., Du, J., Ji, Y., Song, Y..  2018.  Security-Enhanced Signaling Scheme in Software Defined Optical Network. 2018 10th International Conference on Communication Software and Networks (ICCSN). :286–289.

The communication security issue is of great importance and should not be ignored in backbone optical networks which is undergoing the evolution toward software defined networks (SDN). With the aim to solve this problem, this paper conducts deep analysis into the security challenge of software defined optical networks (SDON) and proposes a so-called security-enhanced signaling scheme of SDON. The proposed scheme makes full advantage of current OpenFIow protocol with some necessary extensions and security improvement, by combining digital signatures and message feedback with efficient PKI (Public Key Infrastructure) in signaling procedure of OpenFIow interaction. Thus, this security-enhanced signaling procedure is also designed in details to make sure the end-to-end trusted service connection. Simulation results show that this proposed approach can greatly improve the security level of large-scale optical network for Energy Internet services with better performance in term of connection success rate performance.

2017-03-08
Ji, Y., Wang, J., Yan, S., Gao, W., Li, H..  2015.  Optimal microgrid energy management integrating intermittent renewable energy and stochastic load. 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). :334–338.

In this paper, we focus on energy management of distributed generators (DGs) and energy storage system (ESS) in microgrids (MG) considering uncertainties in renewable energy and load demand. The MG energy management problem is formulated as a two-stage stochastic programming model based on optimization principle. Then, the optimization model is decomposed into a mixed integer quadratic programming problem by using discrete stochastic scenarios to approximate the continuous random variables. A Scenarios generation approach based on time-homogeneous Markov chain model is proposed to generate simulated time-series of renewable energy generation and load demand. Finally, the proposed stochastic programming model is tested in a typical LV network and solved by Matlab optimization toolbox. The simulation results show that the proposed stochastic programming model has a better performance to obtain robust scheduling solutions and lower the operating cost compared to the deterministic optimization modeling methods.