In this paper, the stabilization problem is considered for the class of wireless networked control systems （WNCS）. An indicator is introduced in the WNCS model. The packet drop sequences in the indicator are represe...In this paper, the stabilization problem is considered for the class of wireless networked control systems （WNCS）. An indicator is introduced in the WNCS model. The packet drop sequences in the indicator are represented as states of a Markov chain. A new discrete Markov switching system model integrating 802.11 protocol and new scheduling approach for wireless networks with control systems are constructed. The variable controller can be obtained easily by solving the linear matrix inequality （LMI） with the use of the Matlab toolbox. Both the known and unknown dropout probabilities are considered. Finally, a simulation is given to show the feasibility of the proposed method.展开更多
Due to the effectiveness, simple deployment and low cost, radio frequency identification （RFID） systems are used in a variety of applications to uniquely identify physical objects. The operation of RFID systems ofte...Due to the effectiveness, simple deployment and low cost, radio frequency identification （RFID） systems are used in a variety of applications to uniquely identify physical objects. The operation of RFID systems often involves a situation in which multiple readers physically located near one another may interfere with one another＇s operation. Such reader collision must be minimized to avoid the faulty or miss reads. Specifically, scheduling the colliding RFID readers to reduce the total system transaction time or response time is the challenging problem for large-scale RFID network deployment. Therefore, the aim of this work is to use a successful multi-swarm cooperative optimizer called pseo to minimize both the reader-to-reader interference and total system transaction time in RFID reader networks. The main idea of pS20 is to extend the single population PSO to the interacting multi-swarm model by constructing hierarchical interaction topology and enhanced dynamical update equations. As the RFID network scheduling model formulated in this work is a discrete problem, a binary version of PS20 algorithm is proposed. With seven discrete benchmark functions, PS20 is proved to have significantly better performance than the original PSO and a binary genetic algorithm, pS20 is then used for solving the real-world RFID network scheduling problem. Numerical results for four test cases with different scales, ranging from 30 to 200 readers, demonstrate the performance of the proposed methodology.展开更多
In traditional wireless broadcast networks,a corrupted packet must be retransmitted even if it has been lost by only one receiver.Obviously,this is not bandwidth-efficient for the receivers that already hold the retra...In traditional wireless broadcast networks,a corrupted packet must be retransmitted even if it has been lost by only one receiver.Obviously,this is not bandwidth-efficient for the receivers that already hold the retransmitted packet.Therefore,it is important to develop a method to realise efficient broadcast transmission.Network coding is a promising technique in this scenario.However,none of the proposed schemes achieves both high transmission efficiency and low computational complexity simultaneously so far.To address this problem,a novel Efficient Opportunistic Network Coding Retransmission(EONCR)scheme is proposed in this paper.This scheme employs a new packet scheduling algorithm which uses a Packet Distribution Matrix(PDM)directly to select the coded packets.The analysis and simulation results indicate that transmission efficiency of EONCR is over 0.1,more than the schemes proposed previously in some simulation conditions,and the computational overhead is reduced substantially.Hence,it has great application prospects in wireless broadcast networks,especially energyand bandwidth-limited systems such as satellite broadcast systems and Planetary Networks(PNs).展开更多
In spectrum aggregation(SA), two or more component carriers(CCs) of different bandwidths in different bands can be aggregated to support wider transmission bandwidth. The current resource scheduling schemes for spectr...In spectrum aggregation(SA), two or more component carriers(CCs) of different bandwidths in different bands can be aggregated to support wider transmission bandwidth. The current resource scheduling schemes for spectrum aggregation are not optimal or suitable for CR based heterogeneous networks(Het Nets). Consequently, the authors propose a novel resource scheduling scheme for spectrum aggregation in CR based Het Nets, termed as cognitive radio based resource scheduling(CR-RS) scheme. CR-RS has a three-level structure. Under a dynamic traffic model, an equivalent throughput of the CCs based on the knowledge of primary users(PUs) is given. On this basis, the CR users data transmission time of each CC is equal in CR-RS. The simulation results show that CR-RS has the better performance than the current resource scheduling schemes in the CR based Het Nets. Meanwhile, CR-RS is also effective in other spectrum aggregation systems which are not CR based HetNets.展开更多
Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems (NCSs). The limitation of communication bandwidth results in transport delay, affects the ...Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems (NCSs). The limitation of communication bandwidth results in transport delay, affects the property of real-time system, and degrades the performance of NCSs. An integrated control and scheduling optimization method using genetic algorithm is proposed in this paper. This method can synchronously optimize network scheduling and improve the performance of NCSs. To illustrate its effectiveness, an example is provided.展开更多
Aiming at scheduling problems of networked control system （NCS） used to fulfill motion synthesis and cooperation control of the distributed multi-mechatronic systems, the differences of network scheduling and task s...Aiming at scheduling problems of networked control system （NCS） used to fulfill motion synthesis and cooperation control of the distributed multi-mechatronic systems, the differences of network scheduling and task scheduling are compared, and the mathematic description of task scheduling is presented. A performance index function of task scheduling of NCS according to task balance and traffic load matching principles is defined. According to this index, a static scheduling method is designed and implemented to controlling task set simulation of the DCY100 transportation vehicle. The simulation results are applied successfully to practical engineering in this case so as to validate the effectiveness of the proposed performance index and scheduling algorithm.展开更多
In the cloud data centers,how to map virtual machines(VMs) on physical machines(PMs) to reduce the energy consumption is becoming one of the major issues,and the existing VM scheduling schemes are mostly to reduce ene...In the cloud data centers,how to map virtual machines(VMs) on physical machines(PMs) to reduce the energy consumption is becoming one of the major issues,and the existing VM scheduling schemes are mostly to reduce energy consumption by optimizing the utilization of physical servers or network elements.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,this paper proposes a two-stage VM scheduling scheme:(1) We propose a static VM placement scheme to minimize the number of activating PMs and network elements to reduce the energy consumption;(2) In the premise of minimizing the migration costs,we propose a dynamic VM migration scheme to minimize the maximum link utilization to improve the network performance.This scheme makes a tradeoff between energy efficiency and network performance.We design a new twostage heuristic algorithm for a solution,and the simulations show that our solution achieves good results.展开更多
To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before app...To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before applying the forecasting techniques, a support vector classifier was first used to classify the data, and then the filtering was used to create separate trend and volatility sequences. After forecasting, the Markov chain transition probability matrix was introduced to adjust the residual. Simulation results using surplus gas data from an iron and steel enterprise demonstrate that the constructed SVC-HP-ENN-LSSVM-MC prediction model prediction is accurate, and that the classification accuracy is high under different conditions. Based on this, the scheduling model was constructed for surplus gas operating, and it has been used to investigate the comprehensive measures for managing the operational probabilistic risk and optimize the economic benefit at various working conditions and implementations. It has extended the concepts of traditional surplus gas dispatching systems, and provides a method for enterprises to determine optimal schedules.展开更多
In this paper we consider a queueing network consisting of two parallel servers and threearrival streams generated by independent Poisson sources. Each server has its own queue and receivescustomers from its own arriv...In this paper we consider a queueing network consisting of two parallel servers and threearrival streams generated by independent Poisson sources. Each server has its own queue and receivescustomers from its own arrival stream. A third arrival stream consists of customers which place resourcedemands on both servers, which are handled separately by each server once the request is made. Eachservice time is independent and exponentially distributed. Each customer in the system pays a holdingcost per unit time. The objective is to dynamically determine the optimal scheduling policy to the thirdstream of conupled customers. based on the state of the system, so as to minimize the average cost. Thismodel is new, and has Policy implications for computer or communication networks. A fuzzy approachis presented to solve this problem. Simulation shows that the approach is efficient and promising.展开更多
基金supported by Science Fund for Distinguished Young Scholars of Hebei Province (No. F2011203110)Program for New Century Excellent Talents in the University of China (No. NCET-08-0658)+2 种基金National Natural Science Foundation of China (No. 60974018, No. 60934003)National Basic Research Program of China (973 Program) (No. 2010CB731800)Key Project for Natural Science Research of Hebei Education Department (No. ZD200908)
文摘In this paper, the stabilization problem is considered for the class of wireless networked control systems （WNCS）. An indicator is introduced in the WNCS model. The packet drop sequences in the indicator are represented as states of a Markov chain. A new discrete Markov switching system model integrating 802.11 protocol and new scheduling approach for wireless networks with control systems are constructed. The variable controller can be obtained easily by solving the linear matrix inequality （LMI） with the use of the Matlab toolbox. Both the known and unknown dropout probabilities are considered. Finally, a simulation is given to show the feasibility of the proposed method.
基金Projects(61105067,61174164)supported by the National Natural Science Foundation of ChinaProjects(012BAF10B11,2012BAF10B06)supported by the National Key Technologies R&D Program of China+1 种基金Project(F11-264-1-08)supported by the Shenyang Science and Technology Project,ChinaProject(2011BY100383)supported by the Cooperation Project of Foshan and Chinese Academy of Sciences
文摘Due to the effectiveness, simple deployment and low cost, radio frequency identification （RFID） systems are used in a variety of applications to uniquely identify physical objects. The operation of RFID systems often involves a situation in which multiple readers physically located near one another may interfere with one another＇s operation. Such reader collision must be minimized to avoid the faulty or miss reads. Specifically, scheduling the colliding RFID readers to reduce the total system transaction time or response time is the challenging problem for large-scale RFID network deployment. Therefore, the aim of this work is to use a successful multi-swarm cooperative optimizer called pseo to minimize both the reader-to-reader interference and total system transaction time in RFID reader networks. The main idea of pS20 is to extend the single population PSO to the interacting multi-swarm model by constructing hierarchical interaction topology and enhanced dynamical update equations. As the RFID network scheduling model formulated in this work is a discrete problem, a binary version of PS20 algorithm is proposed. With seven discrete benchmark functions, PS20 is proved to have significantly better performance than the original PSO and a binary genetic algorithm, pS20 is then used for solving the real-world RFID network scheduling problem. Numerical results for four test cases with different scales, ranging from 30 to 200 readers, demonstrate the performance of the proposed methodology.
基金supported in part by the National Natural Science Foundation of China under Grant No. 61032004the National High Technical Research and Development Program of China (863 Program) under Grants No. 2012AA121605,No. 2012AA01A503,No.2012AA01A510
文摘In traditional wireless broadcast networks,a corrupted packet must be retransmitted even if it has been lost by only one receiver.Obviously,this is not bandwidth-efficient for the receivers that already hold the retransmitted packet.Therefore,it is important to develop a method to realise efficient broadcast transmission.Network coding is a promising technique in this scenario.However,none of the proposed schemes achieves both high transmission efficiency and low computational complexity simultaneously so far.To address this problem,a novel Efficient Opportunistic Network Coding Retransmission(EONCR)scheme is proposed in this paper.This scheme employs a new packet scheduling algorithm which uses a Packet Distribution Matrix(PDM)directly to select the coded packets.The analysis and simulation results indicate that transmission efficiency of EONCR is over 0.1,more than the schemes proposed previously in some simulation conditions,and the computational overhead is reduced substantially.Hence,it has great application prospects in wireless broadcast networks,especially energyand bandwidth-limited systems such as satellite broadcast systems and Planetary Networks(PNs).
基金supported by Major National Science and Technology Project(2014ZX03004003-005)Municipal Exceptional Academic Leaders Foundation (2014RFXXJ002)China Postdoctoral Science Foundation (2014M561347)
文摘In spectrum aggregation(SA), two or more component carriers(CCs) of different bandwidths in different bands can be aggregated to support wider transmission bandwidth. The current resource scheduling schemes for spectrum aggregation are not optimal or suitable for CR based heterogeneous networks(Het Nets). Consequently, the authors propose a novel resource scheduling scheme for spectrum aggregation in CR based Het Nets, termed as cognitive radio based resource scheduling(CR-RS) scheme. CR-RS has a three-level structure. Under a dynamic traffic model, an equivalent throughput of the CCs based on the knowledge of primary users(PUs) is given. On this basis, the CR users data transmission time of each CC is equal in CR-RS. The simulation results show that CR-RS has the better performance than the current resource scheduling schemes in the CR based Het Nets. Meanwhile, CR-RS is also effective in other spectrum aggregation systems which are not CR based HetNets.
文摘Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems (NCSs). The limitation of communication bandwidth results in transport delay, affects the property of real-time system, and degrades the performance of NCSs. An integrated control and scheduling optimization method using genetic algorithm is proposed in this paper. This method can synchronously optimize network scheduling and improve the performance of NCSs. To illustrate its effectiveness, an example is provided.
基金This project is supported by National Natural Science Foundation of China (No. 50575013)
文摘Aiming at scheduling problems of networked control system （NCS） used to fulfill motion synthesis and cooperation control of the distributed multi-mechatronic systems, the differences of network scheduling and task scheduling are compared, and the mathematic description of task scheduling is presented. A performance index function of task scheduling of NCS according to task balance and traffic load matching principles is defined. According to this index, a static scheduling method is designed and implemented to controlling task set simulation of the DCY100 transportation vehicle. The simulation results are applied successfully to practical engineering in this case so as to validate the effectiveness of the proposed performance index and scheduling algorithm.
基金supported by the National Natural Science Foundation of China(61002011)the National High Technology Research and Development Program of China(863 Program)(2013AA013303)+1 种基金the Fundamental Research Funds for the Central Universities(2013RC1104)the Open Fund of the State Key Laboratory of Software Development Environment(SKLSDE-2009KF-2-08)
文摘In the cloud data centers,how to map virtual machines(VMs) on physical machines(PMs) to reduce the energy consumption is becoming one of the major issues,and the existing VM scheduling schemes are mostly to reduce energy consumption by optimizing the utilization of physical servers or network elements.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,this paper proposes a two-stage VM scheduling scheme:(1) We propose a static VM placement scheme to minimize the number of activating PMs and network elements to reduce the energy consumption;(2) In the premise of minimizing the migration costs,we propose a dynamic VM migration scheme to minimize the maximum link utilization to improve the network performance.This scheme makes a tradeoff between energy efficiency and network performance.We design a new twostage heuristic algorithm for a solution,and the simulations show that our solution achieves good results.
基金Project(51204082)supported by the National Natural Science Foundation of ChinaProject(KKSY201458118)supported by the Talent Cultivation Project of Kuning University of Science and Technology,China
文摘To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before applying the forecasting techniques, a support vector classifier was first used to classify the data, and then the filtering was used to create separate trend and volatility sequences. After forecasting, the Markov chain transition probability matrix was introduced to adjust the residual. Simulation results using surplus gas data from an iron and steel enterprise demonstrate that the constructed SVC-HP-ENN-LSSVM-MC prediction model prediction is accurate, and that the classification accuracy is high under different conditions. Based on this, the scheduling model was constructed for surplus gas operating, and it has been used to investigate the comprehensive measures for managing the operational probabilistic risk and optimize the economic benefit at various working conditions and implementations. It has extended the concepts of traditional surplus gas dispatching systems, and provides a method for enterprises to determine optimal schedules.
文摘In this paper we consider a queueing network consisting of two parallel servers and threearrival streams generated by independent Poisson sources. Each server has its own queue and receivescustomers from its own arrival stream. A third arrival stream consists of customers which place resourcedemands on both servers, which are handled separately by each server once the request is made. Eachservice time is independent and exponentially distributed. Each customer in the system pays a holdingcost per unit time. The objective is to dynamically determine the optimal scheduling policy to the thirdstream of conupled customers. based on the state of the system, so as to minimize the average cost. Thismodel is new, and has Policy implications for computer or communication networks. A fuzzy approachis presented to solve this problem. Simulation shows that the approach is efficient and promising.
