Terahertz Waveguides for Next Generation Communication Network

Author(s):  
Kathirvel Nallappan ◽  
Hichem Guerboukha ◽  
Yang Cao ◽  
Guofu Xu ◽  
Chahé Nerguizian ◽  
...  
2017 ◽  
Vol 11 (10) ◽  
pp. 25-34
Author(s):  
Marwa Yousif Hassan ◽  
Abdi O. Shuriye ◽  
Momoh Jimoh Eyiomika Salam ◽  
Aisha Hassan Abdalla ◽  
Othman O. Khalifa

2013 ◽  
Vol 765-767 ◽  
pp. 1844-1848
Author(s):  
Wei Zhe Ma ◽  
Yue Hua Li ◽  
Man Rui Song ◽  
Fan Bo Meng

This paper studies the overload control problem of the Parlay gateway in next-generation electric power communication network. First, this paper analyses the effectiveness and fairness of the overload control of the Parlay gateway. And then taking the energy efficiency of the electric power communication network as target, we establish the optimization model of energy efficiency overload control. Thirdly, we put forward an energy efficiency overload control algorithm based on the ant colony algorithm. Simulation results show that our algorithm is feasible and effective.


2013 ◽  
Vol 422 ◽  
pp. 266-272
Author(s):  
Yong Xia ◽  
Wei Zhe Ma ◽  
Man Rui Song ◽  
Fan Bo Meng

With the rapid development of the information and communication technology (ICT) and the considerable increasing of the network business, the energy consumption of the network equipments improves continually. Thus building the technology of the next generation electric power communication network based on energy efficiency has become the research focus of the current electric power communication field. This paper researches the problem of the QoS graded optimization in the next generation electric power communication network. First of all, we discuss the network model of the networks QoS graded optimization, and analyze the delay and the packet loss ratio in time-variant networks. Secondly, we introduce the mathematical description of the throughput capacity and the energy consumption in time-variant networks and build the optimizing model of the energy efficiency which describes the networks QoS classification through considering the QoS constraints such as the networks delay and packet loss ratio etc. Thirdly, we propose using Genetic Algorithm to solve the model and find the QoS classes which make the networks reach the maximum energy efficiency through iterative optimization. Finally, the simulation results indicate the method proposed in this paper is available.


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