无线传感器网络簇间节能路由算法

针对基于分簇网络的无线传感器网络簇间路由协议,让簇首和Sink节点直接通信或通过簇首节点转发数据造成能耗不均,节点过早死亡的缺陷。文中提出一种基于网关节点模型的无线传感器网络簇间路由算法,通过簇头与网关节点、网关节点自身建立虚电路,制定存储转发路由,将数据转发给Sink节点。并引入延时等待机制,增强了簇间信息的融合度,此算法适用于大规模无线传感器网络,有良好的可扩展性。仿真表明在能量节省等性能上与传统簇间路由算法相较有较大提高。     

基于DV-HOP的改进算法及仿真

节点定位技术是无线传感器网络中的关键技术之一。为了提高节点定位精度,在DV-HOP算法的基础上提出两种改进措施:锚节点规划部署和加权算法,改进后的算法统称为加权DV-HOP。在新算法的基础上建立Matlab仿真模型。仿真结果表明加权DV-HOP算法,在相同的锚节点数量和锚节点无线覆盖范围下,节点定位精度约提高10%。     

A myopic mobile sink migration strategy for maximizing lifetime of wireless sensor networks

Network lifetime maximization is challenging particularly for large-scale wireless sensor networks. The sensor nodes near the sink node tend to suffer high energy consumption due to heavy traffic relay operations, becoming vulnerable to energy depletion. The rationale of the sink mobility approach is that as the sink node moves around, such risk of energy depletion at some nodes can be alleviated. In this paper, we first obtain the optimal mobile sink sojourning pattern by solving a linear programming model and then we mathematically analyze why the optimal solution exhibits such sojourning pattern. We use the insights from this analysis to design a simple practical heuristic algorithm for sink mobility, which utilizes only local information. Our heuristic is very different from the existing algorithms which often use the traffic volume as the main decision factor, in that we consider the variance of residual energy of neighboring sensor nodes. The simulation results show that our scheme achieves near-optimal network lifetime even with the relatively low moving speed of the mobile sink.     

具有路径能耗优化特性的WSN无标度容错拓扑控制算法

针对数据传输型的大规模无线传感网络中路径能量损耗问题,建立在多跳模式下的网络路径能耗优化模型,得出可以使网络通信能耗最小的节点度取值规律。依据节点度的最优取值,通过控制网络平均节点度的适应度模型来构建网络拓扑,提出一种具有路径能耗优化特性的无标度容错拓扑控制算法EETA(energy efficiency topology algorithm)。动态性能分析表明,由该算法生成的网络拓扑,其节点的度分布服从幂律,具有无标度拓扑的强容错能力。仿真实验结果显示,该算法同时也降低了网络路径能量消耗,具有路径节能性。     

一种基于网格划分的水下传感器网络多维优化部署策略

针对水下无线传感器网络节点的部署问题,提出一种基于网格划分的多维优化部署策略。首先,将所需探测水下环境划分成相同规格的网格;然后,综合考虑网络节点数量、网络覆盖率、网络冗余度、网络生存率等指标,构建多目标优化数学模型;最后,采用遗传算法对多维优化部署策略加以实现并进行仿真分析。结果显示：所提策略能够有效地减少部署节点数量,提高网络覆盖率和生存效率,降低网络能耗。     

Design and analysis of asynchronous wakeup for wireless sensor networks

In wireless sensor networks, scheduling the sleep duration of each node is one of the key elements for controlling critical performance metrics such as energy consumption and latency. Since the wakeup interval is a primary parameter for determining the sleeping schedule, how to tune the wakeup interval is crucial for the overall network performance. In this paper, we present an effective framework for tuning asynchronous wakeup intervals of IEEE 802.15.4 sensor networks from the energy consumption viewpoint. First, we derive an energy consumption model of each node as an explicit function of the wakeup interval, and empirically validate the derived model. Second, based on the proposed model, we formulate the problem of tuning the wakeup interval with the following two objectives: to minimize total energy consumption and to maximize network lifetime. We show that these two problems can be optimally solved by an iterative algorithm with global information by virtue of the convexity of the problem structure. Finally, as practical solutions, we further propose heuristic optimization algorithms that only exploit local information. In order to develop heuristic algorithms, we propose two broadcasting schemes, which are entitled as maximum wakeup interval broadcasting and efficient local maximum broadcasting. These broadcasting algorithms enable nodes in the network to have heterogeneous wakeup intervals.     

一种基于邻域信息的多信道自适应建网算法

为实现多信道无线自组网的高效建网,针对节点难以感知全网拓扑、其他所有节点的可用频谱以及无法获得同步信息的实际场景,提出了一种基于邻域信息的多信道自适应建网算法。该算法首先设计基于邻域信息的建网策略,使节点能够以自身信息为基础,充分利用可用信道情况、邻居簇首情况等有限的邻域信息进行自适应决策,以建立分簇结构的网络;然后提出基于最大熵原理的信道质量评价算法和基于多头绒泡菌模型的邻居簇首评价算法,分别对节点的可用信道和邻居簇首进行排序,指导节点在建网过程中选择合理的信道和簇首。仿真结果表明,所提建网算法能够使节点在实际场景通信受限的条件下以较小的通信开销完成建网,建立的网络在公共信道数量和簇规模方面也取得了较好的均衡。     

交通路灯监控系统的无线传感网链状路由算法

在交通路灯监控系统中为节省网络节点能耗和降低数据传输时延,提出一种无线传感网链状路由算法（CRASMS）。该算法根据节点和监控区域的信息将监控区域分成若干个簇区域,在每一个簇区域中依次循环选择某个节点为簇头节点,通过簇头节点和传感节点的通信建立簇内星型网络,最终簇头节点接收传感节点数据,采用数据融合算法降低数据冗余,通过簇头节点间的多跳路由将数据传输到Sink节点并将用户端的指令传输到被控节点。仿真结果表明：CRASMS算法保持了PEGASIS算法在节点能耗方面和LEACH算法在传输时延方面的优点,克服了PEGASIS 算法在传输时延方面和LEACH算法在节点能耗方面的不足,将网络平均节点能耗和平均数据传输时延保持在较低水平。在一定的条件下,CRASMS算法比LEACH和PEGASIS算法更优。     

Clustering routing protocol based on improved PSO algorithm in WSN

Aiming at the problem that the location distribution of cluster head nodes filtered by wireless sensor network clustering routing protocol was unbalanced and the data transmission path of forwarding nodes was unreasonable,which would increase the energy consumption of nodes and shorten the network life cycle,a clustering routing protocol based on improved particle swarm optimization algorithm was proposed.In the process of cluster head election,a new fitness function was established by defining the energy factor and position equalization factor of the node,the better candidate cluster head node was evaluated and selected,the position update speed of the candidate cluster head nodes was adjusted by the optimized update learning factor,the local search and speeded up the convergence of the global search was expanded.According to the distance between the forwarding node and the base station,the single-hop or multi-hop transmission mode was adopted,and a multi-hop method was designed based on the minimum spanning tree to select an optimal multi-hop path for the data transmission of the forwarding node.Simulation results show that the clustering routing protocol based on improved particle swarm optimization algorithm can elect cluster head nodes and forwarding nodes with more balanced energy and location,which shortened the communication distance of the network.The energy consumption of nodes is lower and more balanced,effectively extending the network life cycle.     

一个自组网中基于局部状态位置已知的分布式QoS路由算法

在分析自组网的单播QoS路由问题的基础上，提出了一种位置信息已知的利用局部状态信息进行路由选择的的分布式QoS路由算法——LILAGR算法。LILAGR路由算法的基本思想是逐段优化费用和尽快到达目的节点，即在决定节点之间是选择带宽约束费用最小的路径而各个决定节点则是按照贪婪地尽快到达目的节点的原则进行选择。仿真结果表明：LILAGR算法能够以适度的路由消息开销取得较高的路由成功率。此外，LILAGR算法具有可扩展性，可以应用于较大规模的自组网中。