移动传感网中基于密度和距离的概率广播算法

广播是移动传感器网络(mobile wireless sensor networks)中最基本的信息传播方式,但现有的广播算法在广播时需要大量中间转发节点,造成大量消息冗余转发,从而导致能量浪费.因此提出一种基于节点密度和距离的概率(broadcasting algorithm named node density and distance-based probability,NDDP)广播算法.该算法平均转发率为5S/(Nπr~2),这里S为网络区域面积,N为网络节点总数,r为通信半径.理论分析得出该算法的平均广播接收率超过95%.ns-2模拟结果表明平均广播接收率达到92%以上,并且网络节点密度越大算法的转发率越低,越节能.模拟实验结果表明NDDP算法无论在稳定性方面还是在节能性方面均优于Smite和Sidewinder中的广播算法.     

无线多跳通信网络中基于贝叶斯概率模型的消息转发机制研究

无线多跳通信网络依赖多节点中继实现信息传输,因不需要依赖预先架设的基础设施而成为军用及民用领域等特殊应用场景下的重要通信方式。为了能在复杂及恶劣环境下组网,信源节点往往采用全网广播路由请求分组RREQ的泛洪方法,以提高多跳转发路径构建成功率。然而,全网泛洪广播产生消息的冗余转发和重叠效应引起节点能耗的上升和信道利用率的下降,导致分组碰撞与网络拥塞概率的上升,严重时可能造成网络瘫痪而失去效用。本文基于贝叶斯概率论设计了无线多跳通信网络的消息转发模型,通过计算节点密度和后验概率在保证网络连通性的条件下减少不必要的消息转发。基于NS2的仿真结果表明,本文所提出的基于贝叶斯概率模型的消息转发机制能够有效减小广播分组的重播次数。相比于同类算法,在基本保证网络吞吐量的前提下,可以有效降低能量消耗、路由开销,并提高分组成功交付率,从而为未来广域大规模动态多跳网络部署提供技术支撑。     

VANET中一种基于概率转发的AODV路由协议

泛洪被作为实现广播通信的最简单的技术,广泛应用于车联网VANET(vehicular Ad Hoc network)路由.然而,由于VANET中节点的快速移动以及网络拓扑动态变化,简单的泛洪容易导致大量的冗余数据包,并引发广播风暴.为此,以典型的按需式距离矢量路由协议AODV (Ad Hoc on-demand distance vector)为基础,提出基于概率转发的AODV路由协议,记为AODV_P.AODV_P协议利用概率转发机制替代AODV中的泛洪.节点利用距离、密度信息计算转发概率,并依据转发概率设置计时器.计时器时间越短,成为下一跳转发节点的可能性越大.仿真结果表明,提出的AODV_P能够有效降低冗余数据包,缓解广播风暴问题.与AODV协议相比,AODV_P在传输时延、数据包传输率方面得到了有效提高.     

一种高效的动态概率广播算法及其概率模型检测分析

在Ad Hoc网络中,广播有着相当广泛的应用,其算法的效率极大地影响着网络的性能.本文基于DP算法提出了BN-DP算法,考虑了节点分布、计数器值以及收发节点间距离对广播算法的影响,赋予处于接收边缘的节点更高的转发概率.然后使用概率模型检测工具PRISM,分析了计数器值和节点分布对BN-DP算法性能的影响.结果表明:在相同可达率的情况下,所提出的BN-DP算法与FP、DP算法相比,减少了转发分组的数量,提高了广播效率.     

车联网中多跳广播转发节点选择研究

在车载自组织网络中(VANET),大部分应用采用多跳广播来交换道路交通信息,其中最典型的为泛洪广播,但是随着车辆和节点的增多泛洪广播会引起广播风暴,导致信道阻塞。结合模糊逻辑,提出一种基于接收节点的多跳广播方案,依靠接收节点的覆盖范围、信道忙闲比和移动因素,由模糊逻辑系统决定当前节点是否具备转发资格。通过于其它方案的仿真对比验证,所提出的方案在投递率与时延方面具有更好的性能,可有效提高信道利用率,降低广播风暴风险。     

基于车联网的广播MAC协议性能分析

针对车载自组织网络IEEE 802.11协议中媒体访问控制(medium access control, MAC)层一维广播性能分析模型不适用于小竞争窗口的问题,提出一种考虑了连续冻结过程(consecutive freeze process, CFP)现象的二维马尔科夫模型。将CFP映射为连续发送分组过程和连续退避冻结过程,分析得出饱和状态下节点各状态转移的概率,并推导出节点广播分组的性能表达式。仿真结果表明,与一维分析模型相比,即使是在争用信道的竞争窗口较小情况下,该二维分析模型也能很好地预测饱和状态下节点广播分组的平均时延、吞吐量和成功接收率。     

车联网中基于距离的多转发者广播协议

为实现安全信息在车载自组织网络中快速、有效的传播,提出一种基于距离的多转发者广播协议.将上一跳转发节点信号边缘处的节点作为最优转发节点,以增加单次转发覆盖新节点的数量.选择信号覆盖范围中点处节点和次接近信号覆盖范围边缘处节点作为备选转发节点,以降低因隐蔽站或车辆脱离信号覆盖范围导致转发失败的概率,并通过反向车辆存储转发广播分组恢复路由.仿真结果表明,该协议能够适应多种车辆密度的车载自组织网络,满足不同交通流密度情况下紧急信息的分发要求,降低车辆间通信的平均端到端延时和转发率,提高转发效率,并且负载上升缓慢,能有效抑制广播风暴.     

低开销的无线传感器网络时间同步方法

时间同步在无线传感器网络中是一个重要的基础性因素。该文采用发送方-接收方模式传播时间同步消息包，应用线性回归方法和MAC层打时间戳的方法来改善时间同步的精度。提出降低同步开销的方法：利用下级节点度选取某些特定节点，发送消息包，其他节点只是被动接收消息。相比泛洪广播，大大降低了网络开销。     

基于P2P的CDN网络中紧急消息广播技术

向基于P2P方式连接的CDN网络中的所有节点广播紧急消息,泛洪技术可以满足快速和可达这两个指标,但同时会在网络中产生大量冗余的消息广播,效率低下,使网络负荷产生一个短时的波峰.提出泛洪技术的两种改进方案,即WFES和WFESN技术,在不降低泛洪技术快速和可达的前提下提高了广播效率,改善了网络负荷的性能.     

基于路径收集的Ad-hoc网络路由协议的研究

针对Ad-hoc网络中由于节点移动导致的链路断裂和RREQ(Route Request)分组泛洪的问题,提出了基于路径收集的路由协议.采用路径收集机制和链路不相交的多路径算法,提高节点获取路由的能力,增加节点的平均有效路由数量,提高RREQ分组被应答的可能性,从而限制RREQ的广播范围和转发次数;依据路径维持时间的概率密度呈指数分布的特点,设计优先使用最新路径、兼顾路径长度的路由选择策略,以在概率上延长通信路径的维持时间.NS2的仿真结果表明,与AODV、AOMDV以及AODV_PA协议相比,提出的协议提高了分组投递率,并显著地减少了路由开销和通信时延.     

Performance evaluation of dynamic probabilistic broadcasting for flooding in mobile ad hoc networks

In mobile ad hoc networks (MANETs), flooding is a required message dissemination technique for network-wide broadcast. The conventional blind flooding algorithm causes broadcast storm problem, a high number of unnecessary packet rebroadcasts thus resulting in high contention and packet collisions. This paper proposes a new probabilistic approach that dynamically fine-tunes the rebroadcasting probability of a node for routing request packets (RREQs) according to the number of neighbour nodes. We evaluate the performance of the proposed approach for the ad hoc on demand distance vector (AODV) routing protocol and compared against the blind flooding, fixed probabilistic and adjusted probabilistic flooding [L.M.M.M. Bani-Yassein, M. Ould-Khaoua et al., Performance analysis of adjusted probabilistic broadcasting in mobile ad hoc networks, International Journal of Wireless Information Networks 13(2) (2006) 127–140; M.B. Yassein, M.O. Khaoua et al., Improving route discovery in on-demand routing protocols using local topology information in MANETs, Proceedings of the ACM international workshop on Performance Monitoring, Measurement, and Evaluation of Heterogeneous Wireless and Wired Networks, Terromolinos, Spain, ACM Press, 2006, pp. 95–99.] approaches. The simulation results show that our proposed approach demonstrates better performance than blind flooding, fixed probabilistic and adjusted flooding approaches.     

Probabilistic flooding for efficient information dissemination in random graph topologies

Probabilistic flooding has been frequently considered as a suitable dissemination information approach for limiting the large message overhead associated with traditional (full) flooding approaches that are used to disseminate globally information in unstructured peer-to-peer and other networks. A key challenge in using probabilistic flooding is the determination of the forwarding probability so that global network outreach is achieved while keeping the message overhead as low as possible. In this paper, by showing that a probabilistic flooding network, generated by applying probabilistic flooding to a connected random graph network, can be (asymptotically) “bounded” by properly parameterized random graph networks and by invoking random graph theory results, asymptotic values of the forwarding probability are derived guaranteeing (probabilistically) successful coverage, while significantly reducing the message overhead with respect to traditional flooding. Asymptotic expressions with respect to the average number of messages and the average time required to complete network coverage are also derived, illustrating the benefits of the properly parameterized probabilistic flooding scheme. Simulation results support the claims and expectations of the analytical results and reveal certain aspects of probabilistic flooding not covered by the analysis.     

A new probabilistic broadcasting scheme for mobile ad hoc on-demand distance vector (AODV) routed networks

Broadcast is a fundamental operation used in Mobile Ad hoc NETworks (MANETs) for many services, such as route discovery and sending information messages. The direct method to perform broadcast is a simple flooding, which can decrease the performance of MANET. Recently, a probabilistic approach to flooding has been proposed as one of most important suggested solutions to solve the broadcast storm problem, which leads to the collision, contention and duplicated messages. This paper presents the Smart Probabilistic Broadcasting (SPB) as a new probabilistic method to improve the performance of existing on-demand routing protocols by reducing the RREQ overhead during the rout discovery operation. The simulation results show that the combination of AODV and a suitable probabilistic rout discovery can reduce the average end-to-end delay as well as overhead, while achieving low normalized routing load, compared to AODV that uses fixed probability and blind flooding. Simulation experiments have been conducted to examine our proposed scheme. The results show that SPB outperforms its counterparts and opens up a promising framework towards optimal probabilistic broadcasting.     

Impact of noise and interference on probabilistic broadcast schemes in mobile ad-hoc networks

Broadcasting is a vital part of on-demand routing protocols to discover new routes in mobile ad-hoc networks (MANET). Pure flooding is the earliest and still widely used mechanism of broadcasting for route discovery in on-demand routing protocol. In pure flooding, a source node broadcasts a route request to its neighbors. These neighbors then rebroadcast the received route request to their neighbors until the route request arrives at the destination node. Pure flooding may generate excessive redundant traffic leading to increased contention and collisions deteriorating the performance. To limit the redundant traffic, a number of probabilistic broadcast schemes have been proposed in the literature. However, the performance of those probabilistic broadcasting schemes is questionable under real life MANETs which are noisy in nature. Environmental factors like thermal noise and co-channel interference may have adverse effects on the system performance. This paper investigates the effects of thermal noise and co-channel interference on the performance of probabilistic schemes employed in the route discovery mechanism in MANETs. Based on extensive ns-2 simulations, this paper discovers that, contrary to the findings of previous studies, these schemes do not outperform pure flooding scheme when thermal noise and co-channel interference are taken into account.     

基于连通支配集的无线传感器网络洪泛协议

无线传感器网络WSNs在医疗、工业等诸多领域有着重要的应用。WSNs通常由大量的传感器节点组成,这些节点在许多应用中依赖于有限的电源,因此提高无线传感器网络的能效成为研究领域一项重要课题。网络洪泛作为无线传感器网络中的一项基本服务,具有信息可以在整个网络中快速、可靠地分布的优点。然而,由于网络中存在大量冗余传输,网络洪泛的能量效率较低。利用连接支配集CDS,通过减少传输量来提高网络洪泛的能源效率,提出了基于连通支配集的洪泛协议锥(CONE),在洪泛过程中,CONE禁止未在CDS中的节点重播数据包。通过模拟仿真实验评估了CONE的性能,并与基线协议进行了比较。实验结果表明,洪泛协议锥(CONE)提高了网络洪泛端到端的可靠性,降低了网络洪泛的占空比,能有效降低平均能耗。     

A probabilistic and opportunistic flooding algorithm in wireless sensor networks

In wireless sensor networks, many communication protocols and applications rely on flooding for various networking purposes. Prior efforts focus on how to design efficient flooding algorithms; that is, they seek to achieve full reliability while reducing the number of redundant broadcasting across the network. To achieve efficient flooding, most of the existing protocols try to reduce the number of transmissions, which is decided without considering any online transmission result. In this paper, we propose a probabilistic and opportunistic flooding algorithm that controls rebroadcasts and retransmissions opportunistically. It seeks to achieve a target reliability required by an application. For this purpose, it makes a given node select only the subset of its one-hop neighbors to rebroadcast the same message. It considers node relations such as link error rates among nodes in selecting eligible neighbors to rebroadcast. The sender controls the number of retransmissions opportunistically by tracking the current status of message reception at its neighbors. Simulation is carried out to reveal that our proposed scheme achieves the given target reliability with less overhead than other flooding algorithms in most cases, thus prolonging the network lifetime.     

一种基于ＳＩＭＯ系统的递推盲辨识算法

传统的盲辨识算潮基于通道输入的统计模型和通道输出,然而在对输入的统计特性进行准确估计时需要大量的数据,为了避免这种缺点,本文提出了一种单输入多输（SIMO)线性时不变有限单位冲击响应（ＦＩＲ）系统的盲辨识最小二乘算法,利用递推最小二乘算法求解这类算法中的ＸＬＴＫ方程,大大降低了算法对计算存储量的要求,在盲辨识的基础上,利用多项式互质的一个判别定理,通过解卷积求出ＳＩＭＯ－ＦＩＲ系统输入,最后通过实验验证了算法的有效性。     

基于概率推理的Ad-hoc网络路径选择算法

针对Ad-hoc网络在路径选择上主要选择最短路径所出现的问题，从复杂适应系统理论的角度出发，将基于概率推理的路径选择算法加入到AODV(Ad hoc on-demand distance-vector)路由协议中，通过对节点的适应度进行概率推理来选择路径，有效地解决了Ad-hoc网络的拥塞和负载分配问题，改善了网络性能。采用面向对象的建模技术在OMNET++软件平台上进行仿真，结果证明该方法降低了延迟时间，提高了网络QoS，为Ad-hoc网络路由协议的发展提供了一个新思路。     

The role of congestion in probabilistic broadcasting for ubiquitous wireless multi-hop networks through mediation analysis

Broadcast schemes play an important role in the performance of mobile ad hoc networks, which are a clear example of ubiquitous wireless multi-hop networks where nodes collaborate in a distributed way. They are widely used as a dissemination mechanism and as a part of the discovery phase of routing protocols. The simple flooding algorithm is the usual mechanism employed in mobile ad hoc networks, but its inefficiency has been demonstrated in congested scenarios due to the high number of collisions and contentions. However, these problems can be partially alleviated by using a probabilistic broadcast approach in which every node forwards the incoming packets according to a certain forwarding probability. In this paper, we use a simple probabilistic broadcast protocol to evaluate the effects of congestion on the performance of broadcasting in ad hoc networks through a mediation analysis. We hypothesize that the congestion mediates in the relationship between the forwarding probability (independent variable) and the output metric (dependent variable). We consider several output metrics according to the application of the broadcasting protocol such as reachability, broadcasting delay, packet delivery fraction and end to end delay. The simulation results show the existence of the mediating effects and how such effects may be counterbalanced depending on the target use of the probabilistic broadcast scheme.     

Probabilistic flooding in stochastic networks: Analysis of global information outreach

This article investigates probabilistic information dissemination in stochastic networks. The following problem is studied: A source node intends to deliver a message to all other network nodes using probabilistic flooding, i.e., each node forwards a received message to all its neighbors with a common network-wide forwarding probability ω. Question is: what is the minimum ω-value each node should use, such that the flooded message is obtained by all nodes with high probability? We first present a generic approach to derive the global outreach probability in arbitrary networks and then focus on Erd?s Rényi graphs (ERGs) and random geometric graphs (RGGs). For ERGs we derive an exact expression. For RGGs we derive an asymptotic expression that represents an approximation for networks with high node density. Both reliable and unreliable links are studied.