水声网络中的跨层设计研究

跨层设计是水声网络中急需解决的关键技术之一。对于能量和可用频带严重受限的水声网络系统,跨层设计能有效地利用海洋声信道环境下稀少的可用资源,克服分层网络设计中非最优和不灵活的缺点,使系统运行在最佳模式下。在介绍国内外水声网络跨层设计研究的基础上,提出了一种基于控制通道和数据通道的双通道水声网络跨层设计模型,分析了该跨层网络模型的优势,并给出一种自适应节点调制和编码的双通道水声网络跨层模型应用方案,在水池和厦门海域中进行了多节点自组织组网实验,验证了该方案的可行性,表明双通道跨层模型在水声网络设计中具有良好的应用前景。     

一种基于能量感知的节点独立多径路由协议

在综合最小电池代价路由和最小最大电池代价路由优点的基础上,提出一种新的能量感知路由策略,从理论上推导最佳路径条数,并在DSDV路由协议的基础上设计基于该策略的独立多径路由协议EA-MDSDV。仿真结果表明,相比DSDV协议,EA-MDSDV可以较大地提高数据包的递交率,提高网络可靠性;相比非能量保护下的多径路由协议,EA-MDSDV可以保护低能节点的电池能量,延长网络寿命。     

On the Interdependence of Routing and Data Compression in Multi-Hop Sensor Networks

We consider a problem of broadcast communication in sensor networks, in which samples of a random field are collected at each node, and the goal is for all nodes to obtain an estimate of the entire field within a prescribed distortion value. The main idea we explore in this paper is that of jointly compressing the data generated by different nodes as this information travels over multiple hops, to eliminate correlations in the representation of the sampled field. Our main contributions are: (a) we obtain, using simple network flow concepts, conditions on the rate/distortion function of the random field, so as to guarantee that any node can obtain the measurements collected at every other node in the network, quantized to within any prescribed distortion value; and (b) we construct a large class of physically-motivated stochastic models for sensor data, for which we are able to prove that the joint rate/distortion function of all the data generated by the whole network grows slower than the bounds found in (a). A truly novel aspect of our work is the tight coupling between routing and source coding, explicitly formulated in a simple and analytically tractable model – to the best of our knowledge, this connection had not been studied before.     

基于改进粒子群算法的分布式天线系统跨层功率分配方案

结合数据链路层的队列状态信息和物理层的信道状态信息定义了系统的吞吐量系数和公平性系数,建立了分布式天线系统跨层功率分配的离散速率集优化模型。对粒子群优化算法的初始群体产生、粒子更新等步骤进行了改进,形成了改进粒子群算法(IMPSO)。利用IMPSO进行了动态功率分配和跨层优化。数值仿真结果表明,IMPSO能够取得很好的队列时延性能,选取不同的权重可对系统吞吐量性能和公平性性能产生重要影响,IMPSO获得的系统吞吐量性能和公平性性能较之功率固定分配算法(AP)均有较大幅度的提高。     

一种基于跨层设计的无线传感器网络自适应概率广播策略

针对盲目泛洪带来的广播风暴问题,提出了一种基于跨层设计的无线传感器网络自适应概率广播策略(APBCL).APBCL通过MAC层接收信号的强度估算发送节点和接收节点的距离,根据距离计算出转发分组的概率.APBCL减少了分组在网络中的重复传输,降低节点间的竞争和碰撞.仿真实验表明:相比泛洪和概率泛洪,APBCL在不牺牲网络吞吐率的前提下,提高了转播节省率,降低了平均端对端延迟和节点平均丢包率.     

无线传感器网络中的地址分配协议

地址用来标识节点,使能网络通信协议,在无线传感器网络中扮演重要角色.由于无线传感器网络中节点众多,再考虑其网络动态性,手动地为每个节点分配地址是一件繁琐甚至无法完成的工作,于是,地址分配协议成为必需.由于无线传感器网络自身所具有的特点,传统的DHCP协议和ad hoc网络的地址分配协议对其不再适用.分析了无线传感器网络地址分配协议的必要性,总结了地址分配协议需要解决的问题和所面临的挑战,并对已有地址分配协议进行了分类.介绍和比较了当前有代表性的地址分配协议,并指出了它们的问题,分析了地址分配协议下一步研究的重点.     

Sandpiper optimization algorithm with cosine similarity based cross-layer routing protocol for smart agriculture in wireless sensor network assisted internet of things systems

The Internet of Things (IoT) has recently attained a prominent role in enabling smooth and effective communication among various networks. Wireless sensor network (WSN) is utilized in IoT to collect peculiar data without interacting with humans in specific applications. Energy is a major problem in WSN-assisted IoT applications, even though better data communication is achieved through cross-layer models. This paper proposes a new cross-layer-based clustering and routing model to provide a scalable and energy-efficient long data communication in WSN-assisted IoT systems for smart agriculture. Initially, the fuzzy k-medoids clustering approach is used to split the network into various clusters since the formation of clusters plays an important role in energy consumption. Then, a new swarm optimization known as enhanced sparrow search algorithm (ESSA), which is the combination of SSA and chameleon swarm algorithm (CSA), has been introduced for optimal cluster head (CH) selection to solve the energy-hole problems in WSN. A cross-layer strategy has been preferred to provide efficient data transmission. Each sensor node parameter of the physical layer, network layer and medium access control (MAC) is considered for processing routing. Finally, a new bio-inspired algorithm is known as the sandpiper optimization algorithm (SOA), and cosine similarity (CS) has been employed to determine the optimal route for efficient data transmission and retransmission. The simulation of the proposed protocol is implemented by network simulator (NS2), and the simulation results are taken in terms of end-to-end delay, PDR, communication overhead, communication cost, average consumed energy, and network lifetime.     

无线传感器网络中的逐跳跨层拥塞控制

给出一种逐跳跨层拥塞控制机制,依据检测缓冲区占用率和拥塞度所获得的拥塞信息,在传输层开环逐跳速率控制的基础上,自适应地调整节点MAC层信道接入优先级,使整个传感器网络中的节点根据局部的拥塞状态调整信息发送速率。NS2仿真结果表明,该算法可有效地提高网络性能和拥塞控制效率。     

基于WSN的随机网络编码跨层研究

基于无线传感器网络,提出一种跨层实现随机网络编码的方案,并在NS2平台上进行仿真。将网络编码方案与传统的几种传感器路由机制进行对比,分析编码与解码功能,将该方案应用于无线传感器网络中,对影响解码率的几个主要因素,如缓存队列长度、Sink节点的位置等进行了评估。     

无线Ad Hoc网络中QoS感知的跨层资源分配算法

在分析无线Ad Hoc网络资源分配模型的基础上,提出一种QoS感知的跨层资源分配算法CL-QARA (cross layer QoS aware resource allocation).其主要思想是,引入价格作为资源分配的度量指标,以QoS带宽需求为参数,将网络层的动态资源分配信息与MAC层CSMA/CA接入机制相结合,以改进MAC层的冲突退避算法.设计了改进的退避算法和呼叫接入控制算法,以实现MAC层与网络层的跨层技术.通过QoS感知的资源分配算法和跨层技术协同工作,为QoS服务提供了业务保障.仿真结果表明,CL-QARA算法具有良好的收敛性和稳定性.与其他算法相比,CL-QARA能够有效地提供QoS保证,提高了网络的效用和性能.