具有上下文认知的高能效多径路由算法研究

针对移动Ad Hoc网络终端能量资源受限对全网路由的影响,提出了一种基于上下文认知的高能效多径Ad Hoc网络路由算法.该算法面向Ad Hoc网络环境综合考虑节点的能耗、传输路径的能耗和多径路由选择等要素.经过NS2仿真实验并且与其他相关路由算法进行比较,结果表明在相同的实验环境下,该路由算法能够有效地节约能量,降低了端到端的时延,提高网络的吞吐量.     

一种基于Clos交换结构的路由算法

随着互联网业务数据的爆炸性增长,网络中的关键节点——交换机的“电子瓶颈”问题成为限制网络吞吐能力的重要原因.设计了一种适用于Clos交换结构的平面间路由算法,按照业务传输路径的特性和业务之间的位置关系,为业务快速选择最合适的传输路径.仿真表明,该算法在减少业务阻塞率、降低时延方面表现出色,有效改善了交换设备的路由性能.     

基于仿人体血管路径WSN故障容错路由算法研究

为提高无线传感器网络(WSN)故障容错性和传输稳定性,实现网络负载均衡,提出了一种仿人体血管路径的WSN故障容错路由算法.通过研究人体血管路径特性,将其引入到WSN故障容错路由设计中,在对网络节点分区域进行等级标定的基础上实行能耗均衡的静态分簇;运用改进的蚁群算法生成节点路径并计算各路径信息素值,以确定传输路径选择概率并建立仿血管拓扑结构路由.理论与仿真结果表明,此算法具有良好的性能.     

基于最小费用最大流的无线多媒体传感网多路径路由算法

为了解决多媒体数据的实时传输和网络生存时间优化问题,提出基于最小费用最大流的无线多媒体传感网多路径路由算法(MRAMCMF).MRAMCMF分析了数据传输能耗、节点剩余能量和最小数据传输时延,提出了新的权值函数,并利用最小费用最大流算法构建多路径的数据路由方案.所有多媒体传感节点沿着多个传输路径将数据传输到sink节点.仿真结果表明,该算法能延长网络生存时间,降低和平衡节点能耗,降低数据传输时延,在一定的条件下,比Ratio_w算法和TPGF算法更优.     

一种改进的基于时间竞争成簇的路由算法

为平衡无线传感器网络中的簇头负载并进一步降低多跳传输能耗,文中提出了一种改进的基于时间竞争成簇的路由算法。该算法通过限制近基站节点成簇入簇,以防止近基站节点成簇入簇的节能收益无法补偿成簇入簇能耗;利用基站广播公共信息和基于时间机制成簇,以减少节点基本信息交换能耗;通过候选簇头中继来平衡簇头负载。候选簇头的评价函数综合考虑了剩余能量和最优跳数的理想路径,以期在保持中继负载平衡的基础上尽量降低多跳能耗。仿真结果显示,该算法较LEACH和DEBUC算法延长了以30%节点死亡为网络失效的网络生存周期,表明该算法在降低节点能耗和平衡负载方面是有效的。     

IP over WDM网络中业务持续时间感知的绿色路由算法

研究了IP over WDM网络的低碳路由问题,综合 考虑业务持续时间和利用可再生能源和传统能源供能两个 因素,基于分层图模型,提出一种带有业务持续时间感知的绿色路由(HTAGR)算法。HTAGR 依据节点处太阳能 供能情况以及节点和链路的能耗情况动态调整链路权值,并鼓励选择业务持续时间内需要额 外消耗传统能源最少的 路径建立连接。仿真结果表明,与传统节能路由算法相比,HTAGR 有利于消耗更少的传统能 源和使用更多的可再 生能源,在保持较低阻塞率的同时,进一步降低了业务平均传统能耗和CO₂排放量。     

一种基于多跳光旁路的IP over WDM节能网络设计方法

针对IP over WDM网络,基于多跳光旁路和流量疏导,以减少能耗为目标对网络链路配置进行设计;考虑多跳光旁路会增大业务传输距离的问题,分析了光路建立顺序对业务传输距离的影响;通过优先路由短距离业务和限制最大传输跳数来减少业务的平均传输跳数。仿真结果表明,优先建立短距离光路的启发式算法与Dijkstra算法相比可以减少25%～55%的能耗,业务平均物理跳数与Dijkstra算法相差在1跳之内。     

基于异构无线网络的多路径传输

针对异构无线网络环境中,大容量业务传输质量不可靠、网络资源利用率低的问题,提出了一种基于异构无线自组织网络的多路径传输路由算法。该算法有效避免了单路通信方式下的传输链路拥塞、吞吐量低等问题,并结合大容量业务的特点,通过一定的法则合理表征网络环境信息,依据表征结果提出发端到终端的多路径策略,使得重要性不同的业务可选择相应链路质量的路径进行并行传输,避免了网络中的每个自组网节点独立寻找路由导致的源节点难以获得中间节点路由信息的现象。仿真结果表明,该算法可实现整个网络负载均衡,缓解网络链路拥塞,有效降低传输中的丢包率,降低传输时延。     

高能效互联网传输技术研究

从实现网络传输过程中的能耗比例计算理念以及降低网络中数据的重复传输2个角度综述了降低网络能耗的方法.实现能耗比例计算理念的技术包括边缘网络的网络存在性代理技术、以太网节能技术和核心网络的节能路由技术.人类对数据访问的异步性需求以及对数据访问呈现重尾分布的规律从宏观上为减少数据的重复传输提供了前提.比较了互联网上现有的和处于实验阶段的多种内容分发方式,包括CDN、P2P、CCN和双结构互联网,探讨了它们对提高网络传输能效的作用.     

传感器网络中一种基于估计代价的数据聚合树生成算法

无线传感器网络是一种全新的技术,能够广泛应用于恶劣环境和军事领域.传感器网络在数据收集中,为减少冗余数据的传输耗能,降低延迟,需要采用数据聚合技术.本文采用定向传输方式,在消息路由机制基础上提出了一种基于估计代价的数据聚合树生成算法.该算法主要思想在于将节点能耗、传输距离与聚合收益三方面作为估计代价,优化聚合路径,实现数据聚合在能量与时延上的折中.     

Optimum energy efficient multi-hop protocol for homogenous and heterogeneous 3D underwater acoustic sensor networks

Information transmission is extremely challenging in underwater acoustic sensor networks (UASNs) because, in the acoustic channel, the packet loss is high compared to other channels due to low bandwidth and a long propagation delay. So, designing an efficient energy algorithm is a big challenge in the acoustic channel. In this paper, first, a cluster head (CH) election fitness function based on a hybrid particle swarm optimization and gravitational search algorithm (PSO-GSA) is proposed for a three-dimensional (3D) underwater sensor network (UASN). The proposed algorithm includes CH election, CH load, and neighbor CH distance for multi-hop transmission (MH-PSOGSA). Then, based on the proposed algorithm, a relay-based traffic-aware energy-efficient routing protocol (R-TAEERP) with a weight function is proposed to offload the heavy consumption of the CHs. MATLAB simulations were accomplished to compare the performance of MH-PSOGSA and R-TAEERP with the existing representative protocols. The heterogeneity in energy and traffic has been considered. The simulation results show better performance of the proposed algorithm than other existing representative protocols in terms of energy consumption, the performance of the stable region, and the lifetime of the network.     

An event-driven energy-efficient routing protocol for water quality sensor networks

Due to the limited resources of water quality sensor networks, how to design a routing protocol which can prolong the network life cycle is one of a research hotspots. In this paper, according to the event level and the node energy of the sensor networks, the nodes’ types are defined, which can help to determine the cluster node. Then, an event driven routing protocol (EDRP) is proposed, which considers the event information and the remaining energy of the whole network. Simulation results show that, compared with distributed energy-efficient clustering algorithm, EDRP can reduce the overall energy consumption of the network by 138–172%, based on different kinds of events. Besides, EDRP can effectively prolong the life cycle and greatly increase the amount of data transmission of the network.

     

基于博弈的协作路由算法

协作虚拟多输入多输出（VMIMO）传输是一种有效的无线传输性能优化技术。将物理层协作VMIMO技术和网络层路由选择技术相结合,设计跨层VMIMO路由选择方案可以利用VMIMO的分集增益,显著地降低网络传输能耗。如何设计VMIMO协作路由协议抵抗无线网络的自私节点和欺骗行为,保证高数据转发率和低传输能耗成为路由设计中的重大挑战。为了提高自私网络的VMIMO路由性能,提出了一种基于重复路由博弈的VMIMO协作路由算法。该算法将网络划分成多个Group、Group间使用VMIMO传输数据。将Group间路由选择过程建模为重复路由博弈过程。为了提高数据转发的成功率,提出适用度函数评估节点参与数据分组转发的信誉。以此为基础,提出基于适用度的路由选择子算法和路由转发子算法。理论证明所提重复路由博弈可达到帕累托最优。仿真实验结果表明本算法可以促进自私节点相互合作,可获得较高的数据转发率,较好地减少数据传输时延以及能量消耗。     

Energy-efficient routing for correlated data in wireless sensor networks

In this paper, we investigate the reduction in the total energy consumption of wireless sensor networks using multi-hop data aggregation by constructing energy-efficient data aggregation trees. We propose an adaptive and distributed routing algorithm for correlated data gathering and exploit the data correlation between nodes using a game theoretic framework. Routes are chosen to minimize the total energy expended by the network using best response dynamics to local data. The cost function that is used for the proposed routing algorithm takes into account energy, interference and in-network data aggregation. The iterative algorithm is shown to converge in a finite number of steps. Simulations results show that multi-hop data aggregation can significantly reduce the total energy consumption in the network.     

An ant colony optimization based routing algorithm for extending network lifetime in wireless sensor networks

Reducing the energy consumption of network nodes is one of the most important problems for routing in wireless sensor networks because of the battery limitation in each sensor. This paper presents a new ant colony optimization based routing algorithm that uses special parameters in its competency function for reducing energy consumption of network nodes. In this new proposed algorithm called life time aware routing algorithm for wireless sensor networks (LTAWSN), a new pheromone update operator was designed to integrate energy consumption and hops into routing choice. Finally, with the results of the multiple simulations we were able to show that LTAWSN, in comparison with the previous ant colony based routing algorithm, energy aware ant colony routing algorithms for the routing of wireless sensor networks, ant colony optimization-based location-aware routing algorithm for wireless sensor networks and traditional ant colony algorithm, increase the efficiency of the system, obtains more balanced transmission among the nodes and reduce the energy consumption of the routing and extends the network lifetime.     

Energy-Efficient Routing Algorithm Based on Unequal Clustering and Connected Graph in Wireless Sensor Networks

Clustering and multi-hop routing algorithms substantially prolong the lifetime of wireless sensor networks (WSNs). However, they also result in the energy hole and network partition problems. In order to balance the load between multiple cluster heads, save the energy consumption of the inter-cluster routing, in this paper, we propose an energy-efficient routing algorithm based on Unequal Clustering Theory and Connected Graph Theory for WSN. The new algorithm optimizes and innovates in two aspects: cluster head election and clusters routing. In cluster head election, we take into consideration the vote-based measure and the transmission power of sensor nodes when to sectionalize these nodes into different unequal clusters. Then we introduce the connected graph theory for inter-cluster data communication in clusters routing. Eventually, a connected graph is constituted by the based station and all cluster heads. Simulation results show that, this new algorithm balances the energy consumption among sensor nodes, relieves the influence of energy-hole problem, improve the link quality, achieves a substantial improvement on reliability and efficiency of data transmission, and significantly prolongs the network lifetime.     

基于注意力机制ConvLSTM的UAV节能预部署策略

无人机(UAV)可以作为空中基站而凭借其移动性灵活地实现热点区域的覆盖.如何预测流量的分布而优化UAV部署是运营商面临的挑战.针对此问题,该文提出一种基于注意力机制卷积长短期记忆网络(A-ConvL-STM)的UAV节能预部署策略:提出一种融合注意力机制的卷积长短期记忆深度时空网络模型A-ConvLSTM,用于预测用户...     

基于改进LEACH的多簇头分簇路由算法

为了降低无线传感器网络(WSN)的能耗,延长网络的生存周期,提出一种多簇头双工作模式的分簇路由算法.算法对低功耗自适应集簇分层(LEACH)协议作了以下改进:采用多簇头双工作模式来分担单簇头的负荷,以解决单簇头因能耗较大而过早消亡的问题;选举簇头时充分考虑节点位置和节点剩余能量,并应用粒子群优化(PSO)算法优化簇头的选举,以均衡网络内各节点的能耗;建立簇与簇之间的数据传输路由,以减少簇间通信的能耗.仿真结果表明,算法有效降低了网络的能耗,延长了网络的生存周期.     

Energy-efficient data sensing and routing in unreliable energy-harvesting wireless sensor network

Energy-harvesting wireless sensor network (WSN) is composed of unreliable wireless channels and resource-constrained nodes which are powered by solar panels and solar cells. Energy-harvesting WSNs can provide perpetual data service by harvesting energy from surrounding environments. Due to the random characteristics of harvested energy and unreliability of wireless channel, energy efficiency is one of the main challenging issues. In this paper, we are concerned with how to decide the energy used for data sensing and transmission adaptively to maximize network utility, and how to route all the collected data to the sink along energy-efficient paths to maximize the residual battery energy of nodes. To solve this problem, we first formulate a heuristic energy-efficient data sensing and routing problem. Then, unlike the most existing work that focuses on energy-efficient data sensing and energy-efficient routing respectively, energy-efficient data sensing and routing scheme (EEDSRS) in unreliable energy-harvesting wireless sensor network is developed. EEDSRS takes account of not only the energy-efficient data sensing but also the energy-efficient routing. EEDSRS is divided into three steps: (1) an adaptive exponentially weighted moving average algorithm to estimate link quality. (2) an distributed energetic-sustainable data sensing rate allocation algorithm to allocate the energy for data sensing and routing. According to the allocated energy, the optimal data sensing rate to maximize the network utility is obtained. (3) a geographic routing with unreliable link protocol to route all the collected data to the sink along energy-efficient paths. Finally, extensive simulations to evaluate the performance of the proposed EEDSRS are performed. The experimental results demonstrate that the proposed EEDSRS is very promising and efficient.     

EOMR: An Energy-Efficient Optimal Multi-path Routing Protocol to Improve QoS in Wireless Sensor Network for IoT Applications

The wireless sensor network based IoT applications mainly suffers from end to end delay, loss of packets during transmission, reduced lifetime of sensor nodes due to loss of energy. To address these challenges, we need to design an efficient routing protocol that not only improves the network performance but also enhances the Quality of Service. In this paper, we design an energy-efficient routing protocol for wireless sensor network based IoT application having unfairness in the network with high traffic load. The proposed protocol considers three-factor to select the optimal path, i.e., lifetime, reliability, and the traffic intensity at the next-hop node. Rigorous simulation has been performed using NS-2. Also, the performance of the proposed protocol is compared with other contemporary protocols. The results show that the proposed protocol performs better concerning energy saving, packet delivery ratio, end-to-end delay, and network lifetime compared to other protocols.