Abstract:In order to overcome the problem that the existing urban road lighting street lamp control systems are not able to balance energy saving and driving safety，an adaptive energy saving control algorithm for urban road lighting is proposed and studied. The algorithm uses real-time average brightness feedback on the road surface，compares the brightness of the road surface based on the standard design during sunrise and sunset hours，adaptively adjusts the actual switch light time. According to the average traffic flow of the road hours，the corresponding road lighting brightness is calculated by the hour during the night lighting period，realizing the time-division dimming control strategy that matches the statistical results of the traffic flow，which can guarantee driving safety and realize obvious energy saving. It describes the working principle of the algorithm and the flow chart of the program in detail，and introduces the structure and function of the urban road lighting monitoring system based on the LoRa wireless internet of things. The actual operation effect of the system in the same weather conditions and time on a main road in Hunan Province in summer shows that the system can reliably realize the monitoring functions of the remote wireless switch and dimming control of the regional road street lights，verifying the effectiveness of the energy-saving adaptive control algorithm，with an energy saving rate of 39.3% compared with the traditional control methods.

Abstract:To solve the problem of fewer beacon nodes and unknown transmission time in Time of Arrival (ToA) based localization, a new linear programming algorithm was proposed to approximate nonlinear localization estimation problems. We consider the least mean absolute errors of the residual and formulate the nonconvex localization problem as a simple linear programming by using linear approximation. Simulation results demonstrate that the proposed algorithm can maintain good positioning accuracy under fewer beacon nodes and achieve better performance by using less node resources than the existing algorithms.

Abstract:An approximate algorithm of Top-k query based on sampling and weight in wireless sensor network was presented. The algorithm divides the network into several disjoint clusters in the sink node and the nodes in cluster to take sampling process. In the process of sampling, greater weight for reliable and important sensor node is given. The sensor node sensing data has a time correlation, and sampling threshold filtering in the cluster. Each cluster head node receives a Top-k candidate subset of the cluster, and then sends the subset to the sink node. Finally, the sink node can receive a Top-k sample candidate that represents the whole network. Simulation experiments show that the algorithm only needs to send small data and smaller samples, and can satisfy arbitrary precision requirements.

Abstract:An improved algorithm in WSN hierarchical routing protocols was put forward, which considered the residual energy of cluster head selection and multi-hop data transmission from cluster heads to the sink node, to solve the problems of some cluster heads premature depletion, which affect the whole life of the network, caused by part of the cluster heads over long distances with single hop data transmission to the sink node. Analyses and the simulations were conducted on the first nodes death round number and the energy image.The results show that the improved algorithm can balance the network load better and extend the whole network life, compared with the traditional algorithms.

Abstract:The increasing application of WSN (Wireless Sensor Network) brings forward higher and higher requirements on the security of the network.The Sybil is one of the multitudinous security attacks that WSN has to face now and is one of the most ruinous.Based on the analysis of its attacking principle, a type of dispersing guarding algorithm linked with network localization was proposed.The algorithm was used for the measurement of the consistency and the calculation of two methods for the detection of attack nodes, which is different from the traditional centralized guarding mode.The emulation of the algorithm and the experiment results indicate that the algorithm has very good pertinence and robustness against Sybil attack.

Abstract:Because there are a large number of unreliable communication links in wireless sensor network applications, it is difficult to achieve energy efficiency and QoS guarantee.So an energy balanced and QoS guaranteed geographic opportunistic routing protocol (EQGOR) was proposed to solve this problem. Based on opportunistic transmit mechanism, we established the models of forwarding efficiency, forwarding delay, energy efficiency and residual energy, and then proposed an adaptive forwarding set optimization algorithm based on multi-objective particle swarm optimization algorithm, which takes into account both energy and QoS requirement to meet QoS requirement and extend network lifetime. The simulation results have shown that this routing performs better than the opportunistic routing GOR and the traditional multi-path QoS routing QuESt in QoS and energy efficiency.

Abstract:This paper presented a WSN node’s theoretical mode, which includes traffic factor, aggregation factor and bridging factor, and then constructed an articulationnode’s determination and discovery algorithm. Experiment results have shown that the invalidation of nodes identified by the model will have a serious impact on the connectivity of the network. By using this method, we can quickly identify the hot spots in WSN.

Abstract:提出了一种基于蚁群 - 遗传的无线传感器网络路由算法.通过有限寿命的蚂蚁在源节点与目的节点之间的运动获取多个备选路径,然后把每一个备选路径视为一个基因序列,通过选择、交叉和变异操作获得路径的优化,并适时进行路由维护.仿真结果表明,本算法减少了能耗,延长了网络生存时间,提高了网络的可靠性和自适应性.