The task assignment problem of multiple heterogeneous unmanned aerial vehicles （UAVs）, concerned with cooperative decision making and control, is studied in this paper. The heterogeneous vehicles have different oper...The task assignment problem of multiple heterogeneous unmanned aerial vehicles （UAVs）, concerned with cooperative decision making and control, is studied in this paper. The heterogeneous vehicles have different operational capabilities and kinematic constraints, and carry limited resources （e.g., weapons） onboard. They are designated to perform multiple consecutive tasks cooperatively on multiple ground targets. The problem becomes much more complicated because of these terms of heterogeneity. In order to tackle the challenge, we modify the former genetic algorithm with multi-type genes to stochastically search a best solution. Genes of chromo- somes are different, and they are assorted into several types according to the tasks that must be performed on targets. Different types of genes are processed specifically in the improved genetic operators including initialization, crossover, and mutation. We also present a mirror representation of vehicles to deal with the limited resource constraint. Feasible chromosomes that vehicles could perform tasks using their limited resources under the assignment are created and evolved by genetic operators. The effect of the proposed algorithm is demonstrated in numerical simulations. The results show that it effectively provides good feasible solutions and finds an optimal one.展开更多
To study multi-radio multi-channel （MR-MC） Ad Hoc networks based on 802.11, an efficient cross-layer routing protocol with the function of joint channel assignment, called joint channel assignment and cross-layer ro...To study multi-radio multi-channel （MR-MC） Ad Hoc networks based on 802.11, an efficient cross-layer routing protocol with the function of joint channel assignment, called joint channel assignment and cross-layer routing （JCACR）, is presented. Firstly, this paper introduces a new concept called channel utilization percentage （CUP）, which is for measuring the contention level of different channels in a node’s neighborhood, and deduces its optimal value for determining whether a channel is overloaded or not. Then, a metric parameter named channel selection metric （CSM） is designed, which actually reffects not only the channel status but also corresponding node’s capacity to seize it. JCACR evaluates channel assignment by CSM, performs a local optimization by assigning each node a channel with the smaller CSM value, and changes the working channel dynamically when the channel is overloaded. Therefore, the network load balancing can be achieved. In addition, simulation shows that, when compared with the protocol of weighted cumulative expected transfer time （WCETT）, the new protocol can improve the network throughput and reduce the end-to-end average delay with fewer overheads.展开更多
This paper presents a scenario of forest fire suppression using UAVs （Unmanned Aerial Vehicles） and addresses task assignment algorithm to coordinate UAVs. Forest fires are a major problem in many nations and fast e...This paper presents a scenario of forest fire suppression using UAVs （Unmanned Aerial Vehicles） and addresses task assignment algorithm to coordinate UAVs. Forest fires are a major problem in many nations and fast extinguishing forest fires brings a lot of ecological advantages so proper use of firefighting resources is very critical. In this sense, multi UAVs forest fire suppression system can be effective way to prevent fire outbreaks. In multi agent system, an appropriate task assignment according to the SA （Situational Awareness） is the most essential to conduct mission. We should consider real time re-planning or re-scheduling of multi UAVs team because environmental situations such as wind are changeable and that changes affect the forest fire spreading. Furthermore, we have to think about convergence to a consistent SA because it may take too much time. CBBA （Consensus-Based Bundle Algorithm） is robust decentralized task assignment tool so it can be implemented in real time re-planning application. A simulation model which is the main topic in this paper shows that multi UAVs can be properly operated to suppress forest fires even if there are unpredictable random factors and partial disconnection. The simulation model includes concrete operating scenarios and recursive task re-assign algorithm until fires in the whole area are suppressed.展开更多
Employing multiple channels in wireless multihop networks is regarded as an effective approach to increas-ing network capacity. This paper presents a centralized quasi-static channel assignment for multi-radio multi-c...Employing multiple channels in wireless multihop networks is regarded as an effective approach to increas-ing network capacity. This paper presents a centralized quasi-static channel assignment for multi-radio multi-channel Wireless Mesh Networks (WMNs). The proposed channel assignment can efficiently utilize multiple channels with only 2 radios equipped on each mesh router. In the scheme, the network end-to-end traffics are first modeled by probing data at wireless access points, and then the traffic load between each pair of neighboring routers is further estimated using an interference-aware estimation algorithm. Having knowledge of the expected link load, the scheme assigns channels to each radio with the objective of mini-mizing network interference, which as a result greatly improves network capacity. The performance evalua-tion shows that the proposed scheme is highly responsive to varying traffic conditions, and the network per-formance under the channel assignment significantly outperforms the single-radio IEEE 802.11 network as well as the 2-radio WMN with static 2 channels.展开更多
The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem（TSP）,which has been widely applied in the conventional automated storage and retri...The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem（TSP）,which has been widely applied in the conventional automated storage and retrieval system（AS/RS）.However,the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems（MSWS） because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP.In this study,a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period（SWP） and lift idle period（LIP） during transaction cycle time.A mean arrival time difference matrix for pairwise stock keeping units（SKUs） is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation.The decomposition method is applied to analyze the interactions among outbound task time,SWP,and LIP.The ant colony clustering algorithm is designed to determine storage partitions using clustering items.In addition,goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane.This combination is derived based on the analysis results of the queuing network model and on three basic principles.The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry.The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.展开更多
Recent demand for wireless communication continues to grow rapidly as a result of the increasing number of users, the emergence of new user requirements, and the trend to new access technologies. At the same time, the...Recent demand for wireless communication continues to grow rapidly as a result of the increasing number of users, the emergence of new user requirements, and the trend to new access technologies. At the same time, the electromagnetic spectrum or frequencies allocated for this purpose are still limited. This makes solving the frequency assignment problem more and more critical. In this paper, a new approach is proposed using self-organizing multi-agent systems to solve distributed dynamic channel-assignment;it concerns distribution among agents which task is to assign personal station to frequencies with respect to well known constraints. Agents only know their variables and the constraints affecting them, and have to negotiate to find a collective solution. The approach is based on a macro-level management taking the form of a hierarchical group of distributed agents in the network and handling all RANs (Regional Radio Access Network) in a localized region regardless of the operating band. The approach defines cooperative self-organization as the process leading the collective to the solution: agents can change the organization by their own decision to improve the state of the system. Our approach has been tested on PHEADEPHIA benchmarks of frequency assignment Problem. The results obtained are equivalent to those of current existing methods with the benefits that our approach shows more efficiency in terms of flexibility and autonomy.展开更多
Energy saving and emission reduction for railway systems should not only be studied from a technical perspective but should also be focused on management and economics. On the basis of relevant trainscheduling models ...Energy saving and emission reduction for railway systems should not only be studied from a technical perspective but should also be focused on management and economics. On the basis of relevant trainscheduling models for train operation management, in this paper we introduce an extended multi-objective trainscheduling optimization model considering locomotive assignment and segment emission constraints for energy saving. The objective of setting up this model is to reduce the energy and emission cost as well as total passenger- time. The decision variables include continuous variables such as train arrival and departure time, and binary vari- ables such as locomotive assignment and segment occu- pancy. The constraints are concerned with train movement, trip time, headway, and segment emission, etc. To obtain a non-dominated satisfactory solution on these objectives, a fuzzy multi-objective optimization algorithm is employed to solve the model. Finally, a numerical example is performed and used to compare the proposed model with the existing model. The results show that the proposed model can reduce the energy consumption, meet exhausts emission demands effectively by optimal locomotive assignment, and its solution methodology is effective.展开更多
Multiple channels are available for use in IEEE 802.11.Multiple channels can increase the available network's capacity,and how to efficiently assign these available channels to optimize the network performance is ...Multiple channels are available for use in IEEE 802.11.Multiple channels can increase the available network's capacity,and how to efficiently assign these available channels to optimize the network performance is a challenge.We survey current techniques to solve the problem,and category the techniques single-radio,multi-radio,cross-layer multi-channel assignment.This paper also discusses some interesting issues at last.展开更多
In wavelength division multiplexing (WDM) networks without wavelengthconversion functionality, we convert the dynamic routing and wavelength assignment problem formulti-lightpath demands to the edge-disjoint paths pro...In wavelength division multiplexing (WDM) networks without wavelengthconversion functionality, we convert the dynamic routing and wavelength assignment problem formulti-lightpath demands to the edge-disjoint paths problem, and propose a new algorithm. Thecomputer simulations show that the proposed algorithm has better blocking probability performancethan a sequential algorithm, which first separates a multi-lightpath demand into mutilplesingle-lightpath demands, then uses the fixed-alternate routing-first fit wavelength assignment(AR-FF) algorithm for each single-lightpath demand.展开更多
To improve the efficiency of gate reassignment and optimize the plan of gate reassignment,the concept of disruption management is introduced,and a multi-objective programming model for airport gate reassignment is pro...To improve the efficiency of gate reassignment and optimize the plan of gate reassignment,the concept of disruption management is introduced,and a multi-objective programming model for airport gate reassignment is proposed.Considering the interests of passengers and the airport,the model minimizes the total flight delay,the total passengers′walking distance and the number of flights reassigned to other gates different from the planned ones.According to the characteristics of the gate reassignment,the model is simplified.As the multi-objective programming model is hard to reach the optimal solutions simultaneously,a threshold of satisfactory solutions of the model is set.Then a simulated annealing algorithm is designed for the model.Case studies show that the model decreases the total flight delay to the satisfactory solutions,and minimizes the total passengers′walking distance.The least change of planned assignment is also reached.The results achieve the goals of disruption management.Therefore,the model is verified to be effective.展开更多
System reliability optimization problem of multi-source multi-sink flow network is defined by searching the optimal components that maximize the reliability and minimize the total assignment cost. Therefore, a genetic...System reliability optimization problem of multi-source multi-sink flow network is defined by searching the optimal components that maximize the reliability and minimize the total assignment cost. Therefore, a genetic-based approach is proposed to solve the components assignment problem under budget constraint. The mathematical model of the optimization problem is presented and solved by the proposed genetic-based approach. The proposed approach is based on determining the optimal set of lower boundary points that maximize the system reliability such that the total assignment cost does not exceed the specified budget. Finally, to evaluate our approach, we applied it to various network examples with different numbers of available components;two-source two-sink network and three-source two-sink network.展开更多
With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Thing...With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Things (IoT), social networks, video on demand, and mobile multimedia platforms, the backbone network is bound to bear more traffic. The transmission capacity of Single Core Fiber (SCFs) may be limited in the future and Spatial Division Multiplexing (SDM) leveraging multi-core fibers promises to be one of the solutions for the future. Currently, Elastic optical networks (EONs) with multi-core fibers (MCFs) are a kind of SDM-enabled EONs (SDM-EON) used to enhance the capacity of transmission. The resource assignment in MCFs, however, will be subject to Inter-Core Crosstalk (IC-XT), hence, reducing the effectiveness of transmission. This research highlights the routing, modulation level, and spectrum assignment (RMLSA) problems with anycast traffic mode in SDM-EON. A multipath routing scheme is used to reduce the blocking rate of anycast traffic in SDM-EON with the limit of inter-core crosstalk. Hence, an integer linear programming (ILP) problem is formulated and a heuristic algorithm is proposed. Two core-assignment strategies: First-Fit (FF) and Random-Fit (RF) are used and their performance is evaluated through simulations. The simulation results show that the multipath routing method is better than the single-path routing method in terms of blocking ratio and spectrum utilization ratio. Moreover, the FF is better than the RF in low traffic load in terms of blocking ratio (BR), and the opposite in high traffic load. The FF is better than the RF in terms of a spectrum utilization ratio. In an anycast protection problem, the proposed algorithm has a lower BR than previous works.展开更多
Conducting reasonable weapon-target assignment( WTA) with near real time can bring the maximum awards with minimum costs which are especially significant in the modern war. A framework of dynamic WTA( DWTA) model base...Conducting reasonable weapon-target assignment( WTA) with near real time can bring the maximum awards with minimum costs which are especially significant in the modern war. A framework of dynamic WTA( DWTA) model based on a series of staged static WTA( SWTA) models is established where dynamic factors including time window of target and time window of weapon are considered in the staged SWTA model. Then,a hybrid algorithm for the staged SWTA named Decomposition-Based Dynamic Weapon-target Assignment( DDWTA) is proposed which is based on the framework of multi-objective evolutionary algorithm based on decomposition( MOEA / D) with two major improvements: one is the coding based on constraint of resource to generate the feasible solutions, and the other is the tabu search strategy to speed up the convergence.Comparative experiments prove that the proposed algorithm is capable of obtaining a well-converged and well diversified set of solutions on a problem instance and meets the time demand in the battlefield environment.展开更多
A novel data association algorithm is developed based on fuzzy geneticalgorithms (FGAs). The static part of data association uses one FGA to determine both the lists ofcomposite measurements and the solutions of m-bes...A novel data association algorithm is developed based on fuzzy geneticalgorithms (FGAs). The static part of data association uses one FGA to determine both the lists ofcomposite measurements and the solutions of m-best S-D assignment. In the dynamic part of dataassociation, the results of the m-best S-D assignment are then used in turn, with a Kalman filterstate estimator, in a multi-population FGA-based dynamic 2D assignment algorithm to estimate thestates of the moving targets over time. Such an assignment-based data association algorithm isdemonstrated on a simulated passive sensor track formation and maintenance problem. The simulationresults show its feasibility in multi-sensor multi-target tracking. Moreover, algorithm developmentand real-time problems are briefly discussed.展开更多
In this paper, we propose an algorithm for solving multi-objective assignment problem (MOAP) through Hungarian Algorithm, and this approach emphasizes on optimal solution of each objective function by minimizing the r...In this paper, we propose an algorithm for solving multi-objective assignment problem (MOAP) through Hungarian Algorithm, and this approach emphasizes on optimal solution of each objective function by minimizing the resource. To illustrate the algorithm a numerical example (Sec. 4;Table 1) is presented.展开更多
Improving capacity and reducing delay are the most challenging topics in wireless ad hoc networks. Nodes that equip multiple radios working on different channels simultaneously permit ef-fective utility of frequency s...Improving capacity and reducing delay are the most challenging topics in wireless ad hoc networks. Nodes that equip multiple radios working on different channels simultaneously permit ef-fective utility of frequency spectrum and can also reduce interference. In this paper, after analyzing several current protocols in Multi-Radio Multi-Channel (MR-MC) ad hoc networks, a new multi-channel routing metric called Integrative Route Metric (IRM) is designed. It takes channel load, inter-flow, and intra-flow interference into consideration. In addition, an MR-MC routing protocol based on Interference-Aware and Channel-Load (MR-IACL) is also presented. The MR-IACL can assign channels and routings for nodes according to channel load and interference degree of links, and optimize channel distribution dynamically to satisfy the features of topology changing and traffic frequent fluctuation during network running. The simulation results show that the new protocol outperforms others in terms of network throughput, end-to-end delay, routing overhead, and network lifetime.展开更多
多智能体信息融合(multi-agent information fusion,MAIF)系统主要面向多个智能体之间的信息融合、调节、交流和矛盾处理。研究针对数据高度冲突条件下的D-S证据理论失效问题,提出一种将重构的基本概率分配和信念熵相结合的多智能体系...多智能体信息融合(multi-agent information fusion,MAIF)系统主要面向多个智能体之间的信息融合、调节、交流和矛盾处理。研究针对数据高度冲突条件下的D-S证据理论失效问题,提出一种将重构的基本概率分配和信念熵相结合的多智能体系统冲突数据融合方法。该方法使用重构的基本概率分配和信念熵修正证据的可靠性,获得更合理的证据,使用Dempster组合规则将证据进行融合得到结果,在2个实验中均得到了超过90%的置信度。实验表明了该方法的有效性,提高了MAIF系统辨识过程的精度。展开更多
文摘The task assignment problem of multiple heterogeneous unmanned aerial vehicles （UAVs）, concerned with cooperative decision making and control, is studied in this paper. The heterogeneous vehicles have different operational capabilities and kinematic constraints, and carry limited resources （e.g., weapons） onboard. They are designated to perform multiple consecutive tasks cooperatively on multiple ground targets. The problem becomes much more complicated because of these terms of heterogeneity. In order to tackle the challenge, we modify the former genetic algorithm with multi-type genes to stochastically search a best solution. Genes of chromo- somes are different, and they are assorted into several types according to the tasks that must be performed on targets. Different types of genes are processed specifically in the improved genetic operators including initialization, crossover, and mutation. We also present a mirror representation of vehicles to deal with the limited resource constraint. Feasible chromosomes that vehicles could perform tasks using their limited resources under the assignment are created and evolved by genetic operators. The effect of the proposed algorithm is demonstrated in numerical simulations. The results show that it effectively provides good feasible solutions and finds an optimal one.
基金supported by the National Natural Science Foundationof China (60873195 61070220)+3 种基金the Natural Science Foundation of Anhui Province (070412049)the Outstanding Young Teacher Foundation of Anhui Higher Education Institutions of China (2009SQRZ167)the Natural Science Foundation of Anhui Higher Education Institutions of China (KJ2009B114)the Open Project Program of Engineering Research Center of Safety Critical Industry Measure and Control Technology (SCIMCT0802)
文摘To study multi-radio multi-channel （MR-MC） Ad Hoc networks based on 802.11, an efficient cross-layer routing protocol with the function of joint channel assignment, called joint channel assignment and cross-layer routing （JCACR）, is presented. Firstly, this paper introduces a new concept called channel utilization percentage （CUP）, which is for measuring the contention level of different channels in a node’s neighborhood, and deduces its optimal value for determining whether a channel is overloaded or not. Then, a metric parameter named channel selection metric （CSM） is designed, which actually reffects not only the channel status but also corresponding node’s capacity to seize it. JCACR evaluates channel assignment by CSM, performs a local optimization by assigning each node a channel with the smaller CSM value, and changes the working channel dynamically when the channel is overloaded. Therefore, the network load balancing can be achieved. In addition, simulation shows that, when compared with the protocol of weighted cumulative expected transfer time （WCETT）, the new protocol can improve the network throughput and reduce the end-to-end average delay with fewer overheads.
文摘This paper presents a scenario of forest fire suppression using UAVs （Unmanned Aerial Vehicles） and addresses task assignment algorithm to coordinate UAVs. Forest fires are a major problem in many nations and fast extinguishing forest fires brings a lot of ecological advantages so proper use of firefighting resources is very critical. In this sense, multi UAVs forest fire suppression system can be effective way to prevent fire outbreaks. In multi agent system, an appropriate task assignment according to the SA （Situational Awareness） is the most essential to conduct mission. We should consider real time re-planning or re-scheduling of multi UAVs team because environmental situations such as wind are changeable and that changes affect the forest fire spreading. Furthermore, we have to think about convergence to a consistent SA because it may take too much time. CBBA （Consensus-Based Bundle Algorithm） is robust decentralized task assignment tool so it can be implemented in real time re-planning application. A simulation model which is the main topic in this paper shows that multi UAVs can be properly operated to suppress forest fires even if there are unpredictable random factors and partial disconnection. The simulation model includes concrete operating scenarios and recursive task re-assign algorithm until fires in the whole area are suppressed.
文摘Employing multiple channels in wireless multihop networks is regarded as an effective approach to increas-ing network capacity. This paper presents a centralized quasi-static channel assignment for multi-radio multi-channel Wireless Mesh Networks (WMNs). The proposed channel assignment can efficiently utilize multiple channels with only 2 radios equipped on each mesh router. In the scheme, the network end-to-end traffics are first modeled by probing data at wireless access points, and then the traffic load between each pair of neighboring routers is further estimated using an interference-aware estimation algorithm. Having knowledge of the expected link load, the scheme assigns channels to each radio with the objective of mini-mizing network interference, which as a result greatly improves network capacity. The performance evalua-tion shows that the proposed scheme is highly responsive to varying traffic conditions, and the network per-formance under the channel assignment significantly outperforms the single-radio IEEE 802.11 network as well as the 2-radio WMN with static 2 channels.
基金Supported by National Natural Science Foundation of China(Grant No.661403234)Shandong Provincial Science and Techhnology Development Plan of China(Grant No.2014GGX106009)
文摘The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem（TSP）,which has been widely applied in the conventional automated storage and retrieval system（AS/RS）.However,the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems（MSWS） because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP.In this study,a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period（SWP） and lift idle period（LIP） during transaction cycle time.A mean arrival time difference matrix for pairwise stock keeping units（SKUs） is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation.The decomposition method is applied to analyze the interactions among outbound task time,SWP,and LIP.The ant colony clustering algorithm is designed to determine storage partitions using clustering items.In addition,goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane.This combination is derived based on the analysis results of the queuing network model and on three basic principles.The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry.The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.
文摘Recent demand for wireless communication continues to grow rapidly as a result of the increasing number of users, the emergence of new user requirements, and the trend to new access technologies. At the same time, the electromagnetic spectrum or frequencies allocated for this purpose are still limited. This makes solving the frequency assignment problem more and more critical. In this paper, a new approach is proposed using self-organizing multi-agent systems to solve distributed dynamic channel-assignment;it concerns distribution among agents which task is to assign personal station to frequencies with respect to well known constraints. Agents only know their variables and the constraints affecting them, and have to negotiate to find a collective solution. The approach is based on a macro-level management taking the form of a hierarchical group of distributed agents in the network and handling all RANs (Regional Radio Access Network) in a localized region regardless of the operating band. The approach defines cooperative self-organization as the process leading the collective to the solution: agents can change the organization by their own decision to improve the state of the system. Our approach has been tested on PHEADEPHIA benchmarks of frequency assignment Problem. The results obtained are equivalent to those of current existing methods with the benefits that our approach shows more efficiency in terms of flexibility and autonomy.
基金supported by the National Natural Science Foundation of China (No. 71101007)the National High Technology Research and Development Program of China (No. 2011AA110502)State Key Laboratory of Rail Traffic Control and Safety of Beijing Jiaotong University Program (RCS2010ZZ001)
文摘Energy saving and emission reduction for railway systems should not only be studied from a technical perspective but should also be focused on management and economics. On the basis of relevant trainscheduling models for train operation management, in this paper we introduce an extended multi-objective trainscheduling optimization model considering locomotive assignment and segment emission constraints for energy saving. The objective of setting up this model is to reduce the energy and emission cost as well as total passenger- time. The decision variables include continuous variables such as train arrival and departure time, and binary vari- ables such as locomotive assignment and segment occu- pancy. The constraints are concerned with train movement, trip time, headway, and segment emission, etc. To obtain a non-dominated satisfactory solution on these objectives, a fuzzy multi-objective optimization algorithm is employed to solve the model. Finally, a numerical example is performed and used to compare the proposed model with the existing model. The results show that the proposed model can reduce the energy consumption, meet exhausts emission demands effectively by optimal locomotive assignment, and its solution methodology is effective.
基金spported by the National Natural Science Foundation of China ( No. 60973139, 60773041 )Postdoctoral Foundation (No. 0801019C,20090451240, 20090451241)+2 种基金Science&Technology Innovation Fund for Higher Education Institutions of Jiangsu Province( No.CX09B_153Z,CX08B-086Z )Six Projects Sponsoring Talent Summits of Jiangsu Province(No. 2008118)the project of NJUPT(No.NY207135)
文摘Multiple channels are available for use in IEEE 802.11.Multiple channels can increase the available network's capacity,and how to efficiently assign these available channels to optimize the network performance is a challenge.We survey current techniques to solve the problem,and category the techniques single-radio,multi-radio,cross-layer multi-channel assignment.This paper also discusses some interesting issues at last.
基金Supported by the National High Technology Development 863 Program of China(2001AA122023)
文摘In wavelength division multiplexing (WDM) networks without wavelengthconversion functionality, we convert the dynamic routing and wavelength assignment problem formulti-lightpath demands to the edge-disjoint paths problem, and propose a new algorithm. Thecomputer simulations show that the proposed algorithm has better blocking probability performancethan a sequential algorithm, which first separates a multi-lightpath demand into mutilplesingle-lightpath demands, then uses the fixed-alternate routing-first fit wavelength assignment(AR-FF) algorithm for each single-lightpath demand.
基金Supported by the National Natural Science Foundation of China(71103034)the Natural Science Foundation of Jiangsu Province(bk2011084)
文摘To improve the efficiency of gate reassignment and optimize the plan of gate reassignment,the concept of disruption management is introduced,and a multi-objective programming model for airport gate reassignment is proposed.Considering the interests of passengers and the airport,the model minimizes the total flight delay,the total passengers′walking distance and the number of flights reassigned to other gates different from the planned ones.According to the characteristics of the gate reassignment,the model is simplified.As the multi-objective programming model is hard to reach the optimal solutions simultaneously,a threshold of satisfactory solutions of the model is set.Then a simulated annealing algorithm is designed for the model.Case studies show that the model decreases the total flight delay to the satisfactory solutions,and minimizes the total passengers′walking distance.The least change of planned assignment is also reached.The results achieve the goals of disruption management.Therefore,the model is verified to be effective.
文摘System reliability optimization problem of multi-source multi-sink flow network is defined by searching the optimal components that maximize the reliability and minimize the total assignment cost. Therefore, a genetic-based approach is proposed to solve the components assignment problem under budget constraint. The mathematical model of the optimization problem is presented and solved by the proposed genetic-based approach. The proposed approach is based on determining the optimal set of lower boundary points that maximize the system reliability such that the total assignment cost does not exceed the specified budget. Finally, to evaluate our approach, we applied it to various network examples with different numbers of available components;two-source two-sink network and three-source two-sink network.
文摘With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Things (IoT), social networks, video on demand, and mobile multimedia platforms, the backbone network is bound to bear more traffic. The transmission capacity of Single Core Fiber (SCFs) may be limited in the future and Spatial Division Multiplexing (SDM) leveraging multi-core fibers promises to be one of the solutions for the future. Currently, Elastic optical networks (EONs) with multi-core fibers (MCFs) are a kind of SDM-enabled EONs (SDM-EON) used to enhance the capacity of transmission. The resource assignment in MCFs, however, will be subject to Inter-Core Crosstalk (IC-XT), hence, reducing the effectiveness of transmission. This research highlights the routing, modulation level, and spectrum assignment (RMLSA) problems with anycast traffic mode in SDM-EON. A multipath routing scheme is used to reduce the blocking rate of anycast traffic in SDM-EON with the limit of inter-core crosstalk. Hence, an integer linear programming (ILP) problem is formulated and a heuristic algorithm is proposed. Two core-assignment strategies: First-Fit (FF) and Random-Fit (RF) are used and their performance is evaluated through simulations. The simulation results show that the multipath routing method is better than the single-path routing method in terms of blocking ratio and spectrum utilization ratio. Moreover, the FF is better than the RF in low traffic load in terms of blocking ratio (BR), and the opposite in high traffic load. The FF is better than the RF in terms of a spectrum utilization ratio. In an anycast protection problem, the proposed algorithm has a lower BR than previous works.
文摘Conducting reasonable weapon-target assignment( WTA) with near real time can bring the maximum awards with minimum costs which are especially significant in the modern war. A framework of dynamic WTA( DWTA) model based on a series of staged static WTA( SWTA) models is established where dynamic factors including time window of target and time window of weapon are considered in the staged SWTA model. Then,a hybrid algorithm for the staged SWTA named Decomposition-Based Dynamic Weapon-target Assignment( DDWTA) is proposed which is based on the framework of multi-objective evolutionary algorithm based on decomposition( MOEA / D) with two major improvements: one is the coding based on constraint of resource to generate the feasible solutions, and the other is the tabu search strategy to speed up the convergence.Comparative experiments prove that the proposed algorithm is capable of obtaining a well-converged and well diversified set of solutions on a problem instance and meets the time demand in the battlefield environment.
文摘A novel data association algorithm is developed based on fuzzy geneticalgorithms (FGAs). The static part of data association uses one FGA to determine both the lists ofcomposite measurements and the solutions of m-best S-D assignment. In the dynamic part of dataassociation, the results of the m-best S-D assignment are then used in turn, with a Kalman filterstate estimator, in a multi-population FGA-based dynamic 2D assignment algorithm to estimate thestates of the moving targets over time. Such an assignment-based data association algorithm isdemonstrated on a simulated passive sensor track formation and maintenance problem. The simulationresults show its feasibility in multi-sensor multi-target tracking. Moreover, algorithm developmentand real-time problems are briefly discussed.
文摘In this paper, we propose an algorithm for solving multi-objective assignment problem (MOAP) through Hungarian Algorithm, and this approach emphasizes on optimal solution of each objective function by minimizing the resource. To illustrate the algorithm a numerical example (Sec. 4;Table 1) is presented.
基金Supported by the National Natural Science Foundation of China (No. 60873195, No. 61070220)the Research Fund for the Doctoral Program of Higher Education of China (No. 20090111110002)
文摘Improving capacity and reducing delay are the most challenging topics in wireless ad hoc networks. Nodes that equip multiple radios working on different channels simultaneously permit ef-fective utility of frequency spectrum and can also reduce interference. In this paper, after analyzing several current protocols in Multi-Radio Multi-Channel (MR-MC) ad hoc networks, a new multi-channel routing metric called Integrative Route Metric (IRM) is designed. It takes channel load, inter-flow, and intra-flow interference into consideration. In addition, an MR-MC routing protocol based on Interference-Aware and Channel-Load (MR-IACL) is also presented. The MR-IACL can assign channels and routings for nodes according to channel load and interference degree of links, and optimize channel distribution dynamically to satisfy the features of topology changing and traffic frequent fluctuation during network running. The simulation results show that the new protocol outperforms others in terms of network throughput, end-to-end delay, routing overhead, and network lifetime.
文摘多智能体信息融合(multi-agent information fusion,MAIF)系统主要面向多个智能体之间的信息融合、调节、交流和矛盾处理。研究针对数据高度冲突条件下的D-S证据理论失效问题,提出一种将重构的基本概率分配和信念熵相结合的多智能体系统冲突数据融合方法。该方法使用重构的基本概率分配和信念熵修正证据的可靠性,获得更合理的证据,使用Dempster组合规则将证据进行融合得到结果,在2个实验中均得到了超过90%的置信度。实验表明了该方法的有效性,提高了MAIF系统辨识过程的精度。
