We propose a self-organized optimization mechanism to improve the transport capacity of complex gradient networks. We find that, regardless of network topology, the congestion pressure can be strongly reduced by the s...We propose a self-organized optimization mechanism to improve the transport capacity of complex gradient networks. We find that, regardless of network topology, the congestion pressure can be strongly reduced by the self-organized optimization mechanism. Furthermore, the random scale-free topology is more efficient to reduce congestion compared with the random Poisson topology under the optimization mechanism. The reason is that the optimization mechanism introduces the correlations between the gradient field and the local topology of the substrate network. Due to the correlations, the cutoff degree of the gradient network is strongly reduced and the number of the nodes exerting their maximal transport capacity consumedly increases. Our work presents evidence supporting the idea that scale-free networks can efficiently improve their transport capacity by self- organized mechanism under gradient-driven transport mode.展开更多
ADELIN(ADaptive rELIable traNsport protocol)协议利用冗余传输节点来增强了水声传感器网络数据传输的可靠性.下游节点实际上已经接到冗余节点转发的绝大多数数据包.本文提出了基于IPool(Improved Pool)节点的IPool-ADELIN协议.通过...ADELIN(ADaptive rELIable traNsport protocol)协议利用冗余传输节点来增强了水声传感器网络数据传输的可靠性.下游节点实际上已经接到冗余节点转发的绝大多数数据包.本文提出了基于IPool(Improved Pool)节点的IPool-ADELIN协议.通过监听节点的数据传输,IPool节点不但能够在链路状态较差时进行链路维护,而且能够只转发没有被数据包暗示响应的数据包.数学分析和仿真结果表明,和ADELIN协议相比,IPool-ADELIN协议具有更高的数据到达率和更低的数据传输能耗.展开更多
基金Supported by the Education Foundation of Hubei Province under Grant No D20120104
文摘We propose a self-organized optimization mechanism to improve the transport capacity of complex gradient networks. We find that, regardless of network topology, the congestion pressure can be strongly reduced by the self-organized optimization mechanism. Furthermore, the random scale-free topology is more efficient to reduce congestion compared with the random Poisson topology under the optimization mechanism. The reason is that the optimization mechanism introduces the correlations between the gradient field and the local topology of the substrate network. Due to the correlations, the cutoff degree of the gradient network is strongly reduced and the number of the nodes exerting their maximal transport capacity consumedly increases. Our work presents evidence supporting the idea that scale-free networks can efficiently improve their transport capacity by self- organized mechanism under gradient-driven transport mode.
文摘ADELIN(ADaptive rELIable traNsport protocol)协议利用冗余传输节点来增强了水声传感器网络数据传输的可靠性.下游节点实际上已经接到冗余节点转发的绝大多数数据包.本文提出了基于IPool(Improved Pool)节点的IPool-ADELIN协议.通过监听节点的数据传输,IPool节点不但能够在链路状态较差时进行链路维护,而且能够只转发没有被数据包暗示响应的数据包.数学分析和仿真结果表明,和ADELIN协议相比,IPool-ADELIN协议具有更高的数据到达率和更低的数据传输能耗.
