A Novel Spectrum Allocation Strategy with Channel Bonding and Channel Reservation

( Shunfu Jin ),( Xinghua Yao ),( Zhanyou Ma ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.10

In order to meet various requirements for transmission quality of both primary users (PUs) and secondary users (SUs) in cognitive radio networks, we introduce a channel bonding mechanism for PUs and a channel reservation mechanism for SUs, then we propose a novel spectrum allocation strategy. Taking into account the mistake detection and false alarm due to imperfect channel sensing, we establish a three-dimensional Markov chain to model the stochastic process of the proposed strategy. Using the method of matrix geometric solution, we derive the performance measures in terms of interference rate of PU packets, average delay and throughput of SU packets. Moreover, we investigate the influence of the number of the reserved (resp. licensed) channels on the system performance with numerical experiments. Finally, to optimize the proposed strategy socially, we provide a charging policy for SU packets.

Energy-Saving Strategy for Green Cognitive Radio Networks with an LTE-Advanced Structure

Jin, Shunfu,Ma, Xiaotong,Yue, Wuyi The Korea Institute of Information and Commucation 2016 Journal of communications and networks Vol.18 No.4

A green cognitive radio network (CRN), characterized by base stations (BSs) that conserve energy during sleep periods, is a promising candidate for realizing more efficient spectrum allocation. To improve the spectrum efficiency and achieve greener communication in wireless applications, we consider CRNs with an long term evolution advanced (LTE-A) structure and propose a novel energy-saving strategy. By establishing a type of preemptive priority queueing model with a single vacation, we capture the stochastic behavior of the proposed strategy. Using the method of matrix geometric solutions, we derive the performance measures in terms of the average latency of secondary user (SU) packets and the energy-saving degree of BSs. Furthermore, we provide numerical results to demonstrate the influence of the sleeping parameter on the system performance. Finally, we compare the Nash equilibrium behavior and social optimization behavior of the proposed strategy to present a pricing policy for SU packets.

Energy-Saving Strategy for Green Cognitive Radio Networks with an LTE-Advanced Structure

Shunfu Jin,Xiaotong Ma,Wuyi Yue 한국통신학회 2016 Journal of communications and networks Vol.18 No.4

A green cognitive radio network (CRN), characterizedby base stations (BSs) that conserve energy during sleep periods,is a promising candidate for realizing more efficient spectrum allocation. To improve the spectrum efficiency and achieve greenercommunication in wireless applications, we consider CRNs withan long term evolution advanced (LTE-A) structure and proposea novel energy-saving strategy. By establishing a type of preemptivepriority queueing model with a single vacation, we capture thestochastic behavior of the proposed strategy. Using the method ofmatrix geometric solutions, we derive the performance measuresin terms of the average latency of secondary user (SU) packets andthe energy-saving degree of BSs. Furthermore, we provide numericalresults to demonstrate the influence of the sleeping parameteron the system performance. Finally, we compare the Nash equilibriumbehavior and social optimization behavior of the proposedstrategy to present a pricing policy for SU packets.

CK1ε targets Cdc25A for ubiquitin-mediated proteolysis under normal conditions and in response to checkpoint activation

Piao, Shunfu,Lee, Su-Jin,Xu, Yongbin,Gwak, Jungsug,Oh, Sangtaek,Park, Bum-Joon,Ha, Nam-Chul Taylor Francis 2011 Cell cycle Vol.10 No.3

A Novel Spectrum Access Strategy with ${\alpha}$-Retry Policy in Cognitive Radio Networks: A Queueing-Based Analysis

Zhao, Yuan,Jin, Shunfu,Yue, Wuyi The Korea Institute of Information and Commucation 2014 Journal of communications and networks Vol.16 No.2

In cognitive radio networks, the packet transmissions of the secondary users (SUs) can be interrupted randomly by the primary users (PUs). That is to say, the PU packets have preemptive priority over the SU packets. In order to enhance the quality of service (QoS) for the SUs, we propose a spectrum access strategy with an ${\alpha}$-Retry policy. A buffer is deployed for the SU packets. An interrupted SU packet will return to the buffer with probability ${\alpha}$ for later retrial, or leave the system with probability (1-${\alpha}$). For mathematical analysis, we build a preemptive priority queue and model the spectrum access strategy with an ${\alpha}$-Retry policy as a two-dimensional discrete-time Markov chain (DTMC).We give the transition probability matrix of the Markov chain and obtain the steady-state distribution. Accordingly, we derive the formulas for the blocked rate, the forced dropping rate, the throughput and the average delay of the SU packets. With numerical results, we show the influence of the retrial probability for the strategy proposed in this paper on different performance measures. Finally, based on the trade-off between different performance measures, we construct a cost function and optimize the retrial probabilities with respect to different system parameters by employing an iterative algorithm.

A Novel Spectrum Access Strategy with α-Retry Policy in Cognitive Radio Networks: A Queueing-Based Analysis

Yuan Zhao,Shunfu Jin,Wuyi Yue 한국통신학회 2014 Journal of communications and networks Vol.16 No.2

In cognitive radio networks, the packet transmissions ofthe secondary users (SUs) can be interrupted randomly by the primaryusers (PUs). That is to say, the PU packets have preemptivepriority over the SU packets. In order to enhance the quality ofservice (QoS) for the SUs, we propose a spectrum access strategywith an -Retry policy. A buffer is deployed for the SU packets. Aninterrupted SU packet will return to the buffer with probabilityfor later retrial, or leave the system with probability (1 − ). Formathematical analysis, we build a preemptive priority queue andmodel the spectrum access strategy with an -Retry policy as atwo-dimensional discrete-timeMarkov chain (DTMC).We give thetransition probability matrix of the Markov chain and obtain thesteady-state distribution. Accordingly, we derive the formulas forthe blocked rate, the forced dropping rate, the throughput and theaverage delay of the SU packets. With numerical results, we showthe influence of the retrial probability for the strategy proposed inthis paper on different performancemeasures. Finally, based on thetrade-off between different performance measures, we construct acost function and optimize the retrial probabilities with respect todifferent system parameters by employing an iterative algorithm.

A Task Scheduling Strategy in Cloud Computing with Service Differentiation

( Yuanzheng Xue ),( Shunfu Jin ),( Xiushuang Wang ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.11

Task scheduling is one of the key issues in improving system performance and optimizing resource management in cloud computing environment. In order to provide appropriate services for heterogeneous users, we propose a novel task scheduling strategy with service differentiation, in which the delay sensitive tasks are assigned to the rapid cloud with high-speed processing, whereas the fault sensitive tasks are assigned to the reliable cloud with service restoration. Considering that a user can receive service from either local SaaS (Software as a Service) servers or public IaaS (Infrastructure as a Service) cloud, we establish a hybrid queueing network based system model. With the assumption of Poisson arriving process, we analyze the system model in steady state. Moreover, we derive the performance measures in terms of average response time of the delay sensitive tasks and utilization of VMs (Virtual Machines) in reliable cloud. We provide experimental results to validate the proposed strategy and the system model. Furthermore, we investigate the Nash equilibrium behavior and the social optimization behavior of the delay sensitive tasks. Finally, we carry out an improved intelligent searching algorithm to obtain the optimal arrival rate of total tasks and present a pricing policy for the delay sensitive tasks.