One of the main characteristics of Ad hoc networks is node mobility, which results in constantly changing in network topologies. Consequently, the ability to forecast the future status of mobility nodes plays a key ro...One of the main characteristics of Ad hoc networks is node mobility, which results in constantly changing in network topologies. Consequently, the ability to forecast the future status of mobility nodes plays a key role in QOS routing. We propose a random mobility model based on discretetime Markov chain, called ODM. ODM provides a mathematical framework for calculating some parameters to show the future status of mobility nodes, for instance, the state transition probability matrix of nodes, the probability that an edge is valid, the average number of valid-edges and the probability of a request packet found a valid route. Furthermore, ODM can account for obstacle environment. The state transition probability matrix of nodes can quantify the impact of obstacles. Several theorems are given and proved by using the ODM. Simulation results show that the calculated value can forecast the future status of mobility nodes.展开更多
This paper considers the convergence rate of an asymmetric Deffuant-Weisbuch model.The model is composed by finite n interacting agents.In this model,agent i’s opinion is updated at each time,by first selecting one r...This paper considers the convergence rate of an asymmetric Deffuant-Weisbuch model.The model is composed by finite n interacting agents.In this model,agent i’s opinion is updated at each time,by first selecting one randomly from n agents,and then combining the selected agent j’s opinion if the distance between j’s opinion and i’s opinion is not larger than the confidence radiusε0.This yields the endogenously changing inter-agent topologies.Based on the previous result that all agents opinions will converge almost surely for any initial states,the authors prove that the expected potential function of the convergence rate is upper bounded by a negative exponential function of time t when opinions reach consensus finally and is upper bounded by a negative power function of time t when opinions converge to several different limits.展开更多
In this paper,robustness properties of the leader-follower consensus are considered.Forsimplicity of presentation,the attention is focused on a group of continuous-time first-order dynamicagents with a time-invariant ...In this paper,robustness properties of the leader-follower consensus are considered.Forsimplicity of presentation,the attention is focused on a group of continuous-time first-order dynamicagents with a time-invariant communication topology in the presence of communication errors.In orderto evaluate the robustness of leader-follower consensus,two robustness measures are proposed:the L_2gain of the error vector to the state of the network and the worst case L_2 gain at a node.Althoughthe L_2 gain of the error vector to the state of the network is widely used in robust control design andanalysis,the worst case L_2 gain at a node is less conservative with respect to the number of nodes inthe network.It is thus suggested that the worst case L_2 gain at a node is used when the robustnessof consensus is considered.Theoretical analysis and simulation results show that these two measuresare sensitive to the communication topology.In general,the 'optimal' communication topology thatcan achieve most robust performance with respect to either of the proposed robustness measures isdifficult to characterize and/or obtain.When the in-degree of each follower is one,it is shown thatboth measures reach a minimum when the leader can communicate to each node in the network.展开更多
基金Acknowledgements This work is supported by the Postdoctoral Science Foundation of China under Grant No.20080431142.
文摘One of the main characteristics of Ad hoc networks is node mobility, which results in constantly changing in network topologies. Consequently, the ability to forecast the future status of mobility nodes plays a key role in QOS routing. We propose a random mobility model based on discretetime Markov chain, called ODM. ODM provides a mathematical framework for calculating some parameters to show the future status of mobility nodes, for instance, the state transition probability matrix of nodes, the probability that an edge is valid, the average number of valid-edges and the probability of a request packet found a valid route. Furthermore, ODM can account for obstacle environment. The state transition probability matrix of nodes can quantify the impact of obstacles. Several theorems are given and proved by using the ODM. Simulation results show that the calculated value can forecast the future status of mobility nodes.
基金supported by the Young Scholars Development Fund of Southwest Petroleum University(SWPU)under Grant No.201499010050the Scientific Research Starting Project of SWPU under Grant No.2014QHZ032+1 种基金the National Natural Science Foundation of China under Grant No.61203141the National Key Basic Research Program of China(973 Program)under Grant No.2014CB845301/2/3
文摘This paper considers the convergence rate of an asymmetric Deffuant-Weisbuch model.The model is composed by finite n interacting agents.In this model,agent i’s opinion is updated at each time,by first selecting one randomly from n agents,and then combining the selected agent j’s opinion if the distance between j’s opinion and i’s opinion is not larger than the confidence radiusε0.This yields the endogenously changing inter-agent topologies.Based on the previous result that all agents opinions will converge almost surely for any initial states,the authors prove that the expected potential function of the convergence rate is upper bounded by a negative exponential function of time t when opinions reach consensus finally and is upper bounded by a negative power function of time t when opinions converge to several different limits.
基金supported by the National Natural Science Foundation of China under Grant No. 60774005
文摘In this paper,robustness properties of the leader-follower consensus are considered.Forsimplicity of presentation,the attention is focused on a group of continuous-time first-order dynamicagents with a time-invariant communication topology in the presence of communication errors.In orderto evaluate the robustness of leader-follower consensus,two robustness measures are proposed:the L_2gain of the error vector to the state of the network and the worst case L_2 gain at a node.Althoughthe L_2 gain of the error vector to the state of the network is widely used in robust control design andanalysis,the worst case L_2 gain at a node is less conservative with respect to the number of nodes inthe network.It is thus suggested that the worst case L_2 gain at a node is used when the robustnessof consensus is considered.Theoretical analysis and simulation results show that these two measuresare sensitive to the communication topology.In general,the 'optimal' communication topology thatcan achieve most robust performance with respect to either of the proposed robustness measures isdifficult to characterize and/or obtain.When the in-degree of each follower is one,it is shown thatboth measures reach a minimum when the leader can communicate to each node in the network.
