基于最大流的无线mesh网络负载均衡信道分配算法

针对无线mesh网络中各信道间的干扰情况及流量负载均衡问题,定义了负载均衡的目标优化函数,设计一种基于最大流的负载均衡信道分配算法。该算法优先考虑为负载量比较大的链路分配更多的带宽,使得一些关键链路能够承受较大的流量负载,实现各信道的负载均衡,减少网络拥塞,降低分组丢失率和延迟。实验结果表明,该算法较好地平衡了网络负载,在网络业务较重的情况下还能获得较好的网络性能。     

基于时序差分的动态信道分配算法

合理的信道分配可以提高移动蜂窝网络的服务质量，用户高速移动以及流量突增等应用场景给移动蜂窝网络信道分配技术带来了挑战，动态信道分配算法成为当前研究的热点。基于此，首先引入用户呼叫的移动模型及其相关定义；其次建立了移动蜂窝网络信道分配环境的马尔可夫模型，使用时序差分对问题模型求解；最后通过搭建移动蜂窝网络信道分配仿真平台，在小区均匀流量和不均匀流量分布场景下对不同信道分配算法进行仿真实验。结果表明，所提算法大大降低了切换呼叫阻塞率，满足高移动高流量通信场景下的用户需求。     

一种基于博弈论的无线mesh网络信道分配算法

无线mesh网络中的信道分配会极大地影响网络的性能。为了解决无线mesh网络中的信道分配问题,提出了一种基于博弈论的信道分配(GBCA)算法。该算法将网络中每一个节点模型化为一个博弈者,每个博弈者的策略为信道的分配方案,并将整个网络的吞吐量作为效用函数的目标,效用函数的物理意义则是在给定流量需求矩阵下传输的成功率。博弈者通过相互博弈来优化收益函数,以最大化网络吞吐量。并针对GBCA算法的不足,提出了一种改进算法———GBCA-TP算法。通过NS2.34仿真分析得出,GBCA算法和GBCA-TP算法在收敛性、分组丢失率和吞吐量上都要优于当前的算法。     

一种基于不完美信息博弈的多冲突域信道分配算法

无线网络中信道分配的好坏将极大地影响网络整体性能,为了解决和优化此问题,提出了一种基于不完美信息博弈的信道分配算法。假设网络场景为多跳Ad Hoc网络,因此对其采用多冲突域建模更符合实际。算法通过不断循环改变各用户无线电的信道试图接近纳什均衡点,仿真结果表明算法能够使信道分配策略接近纳什均衡信道分配,同时相比单冲突域情况在多冲突域中更能最大化信道使用率。     

增强型的无线Mesh网络信道分配方法

为更可靠地实行无线mesh网络的资源分配,将干扰模型引入mesh网络的节点流量模型中,提出改进型的基于流量感知的固定C-HYA信道分配方法,采用一种更贪婪的算法规避波纹效应,降低网络干扰。之后对算法进行实现仿真,建立相应网络拓扑结构,对在mesh网络中采用传统算法及改进算法对抗波纹效应及信道干扰的情况进行了对比分析。     

基于贪心算法的无线mesh时空域多信道分配研究

无线mesh网络多接口多信道分配算法中,信道分配与接口数目之间存在相互制约、相互依赖、“涟漪效应”,导致链路无效以及承载网络拓扑的主要业务节点存在时序关系,本文在基于多信道空间和时间联合信道分配算法的基础之上,考虑前一个子时序已分配信道对下一个子时序信道分配的影响,提出了基于贪心算法的无线mesh时空域多信道分配算法.根据贪心算法原理,尽量不改变已分配信道,减少信道切换时间,将剩余的未分配信道分配给要分配的接口,使信道能并行工作以提高整个网络的吞吐量.通过实验仿真,对比了能够抑制“涟漪效应”和链路无效的静态多接口多信道分配算法、空间与时间相结合的多接口多信道分配算法.结果表明,整个mesh网络的吞吐量有明显提高,且随着网络中业务节点变化的减小而增大,随着可利用信道数目的增加而增加.     

基于最大化网络吞吐量的WMN信道分配算法

为了解决无线Mesh网络中的信道分配问题,提出了一种基于博弈论的信道分配算法.该算法将网络中每一个节点模型化为一个博弈者,每个博弈者的策略为信道的分配方案,并将整个网络的吞吐量作为效用函数的目标,效用函数的物理意义则是在给定流量需求矩阵下传输的成功率.博弈者通过相互博弈来优化收益函数以最大化网络吞吐量.通过NS2.34仿真分析得出,GBCA算法在收敛性、丢包率和吞吐量上都要优于当前的算法.     

无线网状网射频链路的信道分配算法

研究了无线网状网络节点的接口异构对网络容量的影响.提出了一种新颖的以射频链路为信道分配对象的接口和信道联合分配的分布式贪婪最大算法.该算法以队列长度为权的射频链路吞吐量之和最大为目标,寻找自适应于网络拓扑和流量变化的分布式接口与信道联合分配方案.算法分析指出本算法与非接口异构的Dist. Greedy算法的时间复杂度相当,NS2仿真结果表明网络容量有明显提升.     

基于能效优化的WSNs多径流量分配路由算法

该文针对传感器节点能量受限的特点建立能效优化模型,该模型兼顾网络传输能耗和能耗均衡特性,以最大化网络节点总剩余能量和最小化剩余能量的方差为目标,通过合理分配多条路径的流量来优化网络能效。利用权衡评价函数实现了模型的求解,进而提出一种多径流量分配路由(MFAR)算法。仿真实验表明,该算法能够合理配置各路径流量,显著提高网络能量效率,达到在降低网络能耗的同时保证能耗分布均衡的目标。     

无线自组织网络中一种拥塞意识的多径路由算法

提出了无线自组织网络中一种拥塞意识的多径路由算法。该算法在路由发现过程中,综合节点的队列长度和路径跳数来动态确定路由请求消息的转发概率,可以在保证路由请求消息有一定送达率的条件下,降低路由开销;在路径选择和流量分配过程中,综合考虑节点的队列长度和路径质量作为路由度量,发现流量高吞吐量低拥塞路径,并基于该度量值进行流量分配。仿真结果显示,所提出的多径路由算法能有效提高网络性能。     

用于VSN的低延时多径路由

视频传感器网络VSN（Video Sensor Network）相对于传统的传感器网络需要更高的带宽和更低的延时。文中提出了一种适合于VSN的多径路由算法MPTT（Multi-path Predicted Transmission Time）。这种路由算法是从MAC层建模,根据链路邻居节点的流量信息来估算出路径的整体延时,再根据每条路径延时的大小分配数据流量使其总体的延时达到最小。经过仿真可以得出,在数据流量不大时,该算法与延时最小的路径延时相当。随着所分配流量的加大,MPTT比DSR延时要小,而且可以提供更高的数据流带宽。     

Le millefeuille: Algorithme de routage pour réseau en mode paquet et réseau en mode connecté

We present in this paper an innovating routing method on constrained capacity based on the actual link load ratio. This method is used during the data network or switching network design step. Its goal is to use all the free capacity of the network, by splitting the flow along several paths, and lowering the maximal link load on the network. We present a routing method and a non additive metric on the network components for the computation of the paths. We compare this multi-routings method to disjoint multi-routing methods and show the interest of this method. It provides the network higher resistance to flow increase, and higher resistance to single link failure.     

Design of logical topology with K‐connected constraints and channel assignment for multi‐radio wireless mesh networks

In multi‐radio multi‐channel wireless mesh networks, the design of logical topology is different from that in single channel wireless mesh networks. The same channel assignment algorithm used for various logical topologies will lead to diverse network performance. In this paper, we study the relationship between k ‐connected logical topology and the maximum number of assigned channels. Meanwhile, we analyze the issues affecting channel assignment performance, and present the lower and upper bounds of the maximum allowable number of assigned channels for k ‐connected logical topology. We then develop a k ‐connected logical topology design algorithm based on shortest disjoint paths and minimum interference disjoint paths for each node‐pair. In addition, we propose a static channel assignment algorithm according to minimum spanning tree search. Extensive simulations show that our proposed algorithm achieves higher throughput and lower end‐to‐end delay than fault tolerant topology control algorithms, which validates the involved trade‐off between path length and nodal interference. Moreover, numerical results demonstrate that our proposed channel assignment further improves network performance under the context of limited radio interfaces. Copyright © 2014 John Wiley & Sons, Ltd.     

Maximizing Capacity Usage and Selection of Optimal Antennas to Improve Spectrum Efficiency in Massive MIMO Technology

The performance of Massive MIMO can be enhanced by utilizing a large number of antennas than used and signifying its enormous capabilities in upgrading spectral efficiency. Antenna Selection is a low-priced complexity that decreases the number of radiofrequency chains with the contemplation of augmenting channel capacity. In this paper, an Augment Antenna Selection algorithm based on maximum flow minimum cut theorem is proposed which captures the optimal antennas based on the aggregate capacity of the possible antenna combinations. The first step in this algorithm proposes a subset of antennas to compute the augment paths and the second step selection considers the remaining capacity present in antennas to compute the maximum flow in a network. Thus, this algorithm that selects optimal antennas with better channel conditions aims at improving spectrum and energy efficiency. Simulation results show the outage capacity and the performance of BER with 64*64 and 128*128 Massive MIMO versus SNR has been analyzed.

     

面向带宽碎片最小化和QoS保障的数据中心网络流量调度算法

随着数据中心网络流量的迅速增长,如何提高数据中心网络性能和服务质量成为了研究热点。然而现有的流量调度算法在网络负载加大时,一方面会导致网络带宽碎片化从而使得网络吞吐量降低,另一方面忽视了流量应用需求导致网络服务质量较差。为此,该文提出一种面向带宽碎片最小化和QoS保障的动态流量调度算法,算法综合考虑了带宽敏感的大流、时延与丢包敏感的小流的不同需求,首先根据待调度流的源地址和目的地址建立最短路径集,其次从中筛选出满足待调度流的带宽需求的所有路径,然后根据路径剩余带宽信息和小流应用需求情况为每条路径建立权重函数,最后根据权重函数值利用轮盘赌算法选择转发路径。实验仿真结果显示,与其它算法相比,所提算法降低了小流的丢包率和时延,同时在网络负载较大时提升了网络吞吐量。     

面向电力物联网三维空间几何信道建模的研究

当前研究主要采用椭圆模型描述第6代 (6G)电力物联网(IoT)物理层多节点通信场景,忽视了信号传输路径的俯仰角对系统性能造成的影响。为解决这一问题,该文通过建立3维半椭球体几何传输模型描述6G电力物联网物理层通信场景,提高了电力物联网异构网物理层数据传输分析过程中的准确度。在提出的传输分析算法中,通过推导电力物联网通信无线传输信道中不同传输路径的复冲激响应函数表达式,揭示物理层数据的传输特性。数值分析不同传输路径间的互相关特性,探索电力物联网的时域传输特性,验证上述信道传输特性仿真结果的正确性,对于分析与设计电力物联网无线通信系统具有重要的理论依据和技术支撑。     

基于OFDM认知无线电网络的最优路径算法

针对基于正交频分复用的分布式认知无线电网络,在考虑频谱移动特性的同时,为保证认知用户数据传输的可靠性,提出一种最优路径的基于OFDM认知无线电网络路由算法.该算法首先通过建立认知无线电网络的模型计算信道的期望传输时间和信道干扰,结合类似于按需路由的基本流程得到所有可能的路径.最后,根据最小累积期望传输时间和路径平均吞吐量的指标来选择最优路径.仿真的结果表明,OROCR算法可以明显地减少平均端到端时延,大大地提高平均端到端吞吐量.     

Network coding-aware flow control in wireless ad-hoc networks with multi-path routing

In this paper, we study a flow control problem considering network coding in wireless ad-hoc networks with multi-path routing. As a network coding scheme, we use XOR network coding, in which each node bitwise-XORs some packets received from different sessions, and then broadcasts this coded packet to multiple nodes in a single transmission. This process can reduce the number of required transmissions, and thus can improve network utilization, especially if it is used with appropriate network coding-aware protocols. Considering this XOR network coding, we formulate an optimization problem for flow control that aims at maximizing network utility. By solving the optimization problem in a distributed manner, we implement a distributed flow control algorithm that provides the optimal transmitting rate on each of multiple paths of each session. The simulation results show that our flow control algorithm performs well exploiting the advantages of network coding and provides significant performance improvement.     

Joint data rate and power allocation for lifetime maximization in interference limited ad hoc networks

In this paper, we consider the following problem in the wireless ad hoc network: Given a set of paths between source and destination, how to divide the data flow among the paths and how to control the transmission rates, times, and powers of the individual links in order to maximize the operation time of the worst network node. If all nodes are of equal importance, the operation time of the worst node is also the lifetime of the network. By solving the problem, our aim is to investigate how the network lifetime is affected by link conditions such as the maximum transmission power of a node and the peak data rate of a link. For the purpose, we start from a system model that incorporates the carrier to interference ratio (CIR) into a variable data rate of a link. With this, we can develop an iterative algorithm for the lifetime maximization, which resembles to the distributed power control in cellular systems. Numerical examples on the iterative algorithm are included to illustrate the network lifetime as a function of the maximum transmission power and the peak data rate.