移动性受限物联网应用中基于图论的高效数据采集策略

针对物联网数据采集应用，研究移动性受到限制的汇聚节点对数据采集性能和能量有效性造成的影响，提出能量有效的数据采集策略.基于图论基本原理对系统进行分析，建立借助方格的网络分层描述方法.提出数据采集中的能量分层优化HOEE问题，采用基于启发式算法的匹配算法来匹配节点方格，制定能耗均衡的数据包上报策略.NS-3仿真实验结果表明，HOEE数据采集策略具有优越性，与最短路径树、最大数据量最小路径以及随机采集策略相比，网络寿命能够有效提高约30%，维持较高的数据采集性能.在具有移动性受限的汇聚节点的物联网应用中使用HOEE数据采集策略，能够提高网络寿命，保证数据采集性能.

Efficient data gathering scheme in mobility-constrained internet of things with graph theory

The impact of the mobility-constrained mobile sink deployed in internet of things (IoT) on the data gathering performance and the energy efficiency was investigated, and an energy efficient data gathering scheme was proposed for the data collection and application of IoT. The IoT system was analyzed by the graph theory and the network was described based on hierarchical equal-sized grids. The comprehensive data gathering scheme, hierarchical optimization of energy efficiency (HOEE), was proposed; and a matching algorithm based on heuristic algorithm was employed to match nodes; and a dynamic and adaptive data packet delivery protocol was proposed to balance the energy consumption among pipe nodes. Network Simulator-3 (NS-3) platform's simulation results show that the HOEE scheme has superiority in important metrics and increases the network lifetime by 30% when compared to the shortest path tree (SPT), maximum amount shortest path (MASP), and RANDOM scheme. The HOEE data gathering scheme can be applied in the IoT applications with a mobility-constrained mobile sink to increase the network lifetime and improve the data gathering performance.