Energy-saving Mechanism With Continuous Time Single Sleep Mode In CRN And Its Performance Study

The explosive surge of mobile communication data and bandwidth-intensive applications,lead to a sharp increase in energy consumption of the network base station.This not only intensifies the greenhouse effect and other ecological problems,but also violates the pursuit of low energy consumption to service providers."Energy saving" issue of the network has aroused widespread attention.For CRN(cognitive radio network),in view of overlay dynamic spectrum allocation strategy,we study the energy saving mechanism based on single sleep mode,and carry out performance evaluation and system optimization.First,we introduce single sleep mode and then propose a SM-ESM(Energy Saving Mechanism with Sleep Mode)for CRN.Considering the different priorities of the cognitive user and the licensed user,we establish a single vacation preemptive priority queuing model,and give the transfer rate matrix.Using the matrix geometric solution method to analyze the steady state,we derive the system performance measures — energy saving rate and the average latency of cognitive user packets.Secondly,in order to improve the response performance of cognitive user packets,considering that when the number of cognitive user packets reaches to N,the sleep period will be terminated in advance,we put forward a NSM-ESM(Energy Saving Mechanism with N-policy Sleep Mode).In the continuous time domain,we establish a N policy single vacation preemptive priority queuing model.Combining the number of cognitive user packets with the status of the Base Station,we construct a two-dimensional Markov chain to analyze the model.Based on the case that the Base Station needs shallow sleep,we evaluate the energy saving effect and response performance of the system quantitatively.Then,on the basis of NSM-ESM,when the arrival of user packets is sparse,the Base Station needs deep sleep,we consider the activation process of the Base Station,and then establish a queuing model with the start-up procedure.Combining the number of cognitive user packets and licensed users packets with the Base Station status,we construct a three-dimensional Markov chain to analyze the model.Taking into account the case that Base Station needs deep sleep,we evaluate the system performance of the NSM-ESM.Finally,we verify the effectiveness of SM-ESM and NSM-ESM by numerical experiments and simulation experiments.For SM-ESM,we analyze the Nash equilibrium and the social optimum from the perspective of cognitive user packets,and then give a pricing scheme to realize the social optimization.Considering the case that Base Station needs shallow sleep or deep sleep,respectively,we trade off the system performance measures of NSM-ESM,construct the cost function,and then give the artificial bee colony(ABC)algorithm to achieve system optimization.