基于梯度化邻居节点信息的传感器网络性能优化*

由于路由控制粒度粗，传统最小跳数路由无线传感器网络模型MHR存在数据汇聚可靠性差和能量有效性低等问题，需进一步完善。为改善传统MHR网络的性能，提出一种高效可靠的最小跳数路由无线传感器网络模型MHR-ER，在MHR网络的基础上，通过提取网络梯度化邻居节点信息作为路由精细化控制的依据，通过限制最小跳数梯度场梯度层次宽度以保证数据汇聚的高可靠性，通过限制数据分组的各跳转发节点数以提高数据汇聚的能量有效性。理论分析和仿真结果表明，与MHR网络相比，MHR-ER网络具有极高的数据汇聚可靠性和较好的能量有效性，有利于推动最小跳数路由无线传感器网络的实际应用。

Performance optimization for wireless sensor networks based on gradient neighbor information

As a result of the rough control on routing, the original minimum hop routing (MHR) wireless sensor networks has such shortcomings as inconsistently reliability and poor energy-efficiency in the process of data sinking, it is necessary to further improve the MHR networks. In order to improve the performance of MHR networks, a reliable and efficient minimum hop routing (MHR-ER) wireless sensor networks on basis of MHR networks is presented. With the help of gradient neighbor information discovered from the network behaviors, the routing is controlled finely. By controlling the level width of the minimum hop gradient field, the consistently reliability of data sinking is ensured. By limiting the number of forwarding node in every hop, the energy-efficiency is improved. The theoretic analysis and simulation result validated that the reliability and efficiency of MHR-ER networks is high, these is good for promoting the practical application of minimum hop routing networks.