具有传输成功率保证的概率路由算法的TTL预测模型

概率路由算法是机会网络中一种常用的路由算法,其TTL的设置将直接影响路由的性能.本文首先利用马尔可夫链对概率路由的转发过程进行建模,并从消息的传输成功率和传输延时方面进行性能评估,不仅可以计算出一个消息从源节点到目的节点所需的传输延时,还可以预测出在给定传输成功率下所需要的最短消息生存周期TTL,这对于TTL的设置具有理论上的指导作用.其次,本文建立的预测模型还可以使一些无法到达目的节点的消息及时被删除,从而减少不必要的转发,达到节约网络资源的目的.最后,在两个真实数据集中的实验结果表明,本文提出的模型能够为概率路由中TTL值的准确设置提供有效参考.     

基于信誉值维护的机会网络自私节点检测机制

机会网络中自私节点的存在严重影响路由转发的性能。为在路由时避开此类节点、消除其对网络性能的影响,提出了一种基于信誉值维护的自私节点检测机制,通过两跳ACK消息来监测节点行为,利用监测信息计算节点的信誉值,并将其作为判断节点是否自私的依据。在多种路由算法上加载该检测机制进行仿真实验,结果表明该检测机制可准确识别机会网络中的自私节点,提高消息投递的成功率,并能有效控制消息副本数和网络开销。     

基于社会特征周期演化的机会移动网络路由转发策略

针对分布式k团社区检测引起的超大社区问题,提出了具有节点退出机制的?-window社区检测方法,相应提出了?-window中心性估计。通过实验发现?-window社区和?-window中心性具有周期演化特性,利用该特性,提出TTL(time to live)社区检测和TTL中心性估计,以更准确预测消息生存期上节点的相遇。随后,利用TTL社区和TTL中心性作为转发测度,设计了新的机会移动网络路由算法PerEvo。实验结果表明,与现有的基于社会特征的路由算法比较,PerEvo在保持基本不变的传输开销的同时,有效提高了机会移动网络消息投递的成功率。 关键词：机会移动网络;社区;中心性;周期演化;消息转发     

基于信誉的延迟容忍网络激励方案

由于长延迟、频繁中断等特性,延迟容忍网络采用“存储-携带-转发”的路由方式实现报文的传递.这种传输方式建立在网络节点互相信任,诚实合作的假设之上.然而,由于受到自身资源的限制,网络中存在自私节点拒绝参与网络合作的行为,导致网络传输性能下降,甚至无法正常运行.针对此类问题,本文提出一种基于信誉的延迟容忍网络激励方案,鼓励节点共享资源,并约束自私行为.设计了一种观测协议,以解决延迟容忍网络环境下对网络节点行为的观测问题;提出了一种信誉模型,通过信任值评价节点的可信程度,从而优化路由决策,惩罚自私节点.仿真结果表明了本文提出的激励方案的有效性和可行性.     

基于相遇紧密程度估测的延迟容忍网络路由

针对延迟容忍网络中节点运动状态变化频繁、通信路径不完整,使得转发消息仅能通过节点相遇而获得连接机会来完成,以及在不知节点间相关性的延迟容忍网络中盲目转发消息易导致其转发成功率较低等问题,提出了基于相遇紧密程度动态估测的延迟容忍网络路由策略。通过设计节点间的条件相遇时间间隔和连接持续时间的计算模型,来确定节点间关系的紧密程度;定义延迟容忍网络模型,构造最短路径择取机制,动态地选出条件最短路径,对消息进行转发。仿真数据对比显示,所提策略可有效改善网络性能,提高消息成功投递率,降低传输时延和负载率。     

基于预期延迟值的扩散转发路由算法

针对现有延迟容忍网络路由算法在消息传递过程中分发不灵活的问题,提出基于节点通话历史记录计算预期通断时长以及消息传递延迟值,并根据结果选择节点、分配副本数进行消息转发的路由算法（MDESF）。在算法不同阶段,根据节点的活跃度选择中继节点,再分配传递消息的副本数目,加快分发,降低延迟。同时为保证消息及时传递,在单副本阶段选择最优节点转发。本算法同时提出内存管理策略,提高消息转发成功率。仿真实验表明,该算法相对其他同类算法在投递率、交付时延和网络拥塞比率方面综合表现更优。     

机会网络中基于活跃度的主动拒绝路由算法

针对机会网络Epidemic路由算法投递率较低的问题,提出了基于活跃度的主动拒绝路由算法。该算法根据节点转发能力和投递能力估算节点活跃度,缓存不足时,节点基于活跃度拒绝或接收新消息。在ONE仿真平台上实现了该算法,仿真结果表明,此算法能有效地减少消息抛出现象,在传输延迟没有明显增加的情况下,改进后的算法能够提高投递率,降低投递开销。     

延迟容忍移动传感器网络中基于最优距离的可靠节能传输策略

在延迟容忍移动传感器网络（Delay Tolerant Mobile Senor Networks，DTMSN）的数据传输过程中容易出现数据丢失及节点因能量耗尽而导致网络生存时间减少的问题.针对上述问题本文提出了基于最优距离的可靠节能传输策略，该传输策略利用距离与能量的关系解决了DTMSN中的三个重要问题：可靠性、能源效率、网络生存时间.首先，在链路质量保证下，引入了"可靠节能距离"和"可靠能量平衡距离"两个概念.此外，通过分析节点间距离、节点运动方向及节点当前剩余能量来确定节点的综合效用值，最后根据综合效用值的大小来路由消息.实验结果表明，该策略显著提高了消息的投递率及可靠性保证下传感器节点的能量利用率，延长了网络的生存时间.     

机会网络中一种增加控制信息的传染病算法

机会网络中,泛洪算法具有较高的消息成功投递率,但是其网络负载也较高。针对现有的泛洪算法Epidemic,引入控制信息,利用控制信息删除已经到达目的节点的消息,从而避免携带无用信息,降低网络负载率。仿真结果表明,改进后的路由算法在保证消息成功投递率和网络平均时延的同时,有效降低了网络负载率。     

社区机会网络路由性能提升策略

在社区机会网络中由于网络资源的限制,节点的缓存、能量、带宽等属性会严重影响网络的性能。现有的社区机会网络路由算法往往只根据节点的中心性级别来进行副本的分配,而并没有充分考虑上述属性的影响。针对这一问题,本文提出一种结合节点属性与中心性的路由算法WRACS。该路由算法既考虑了影响节点传输能力的各种属性,又结合了节点的活跃程度。最后通过ONE仿真分析可知,该算法在信息投递率,平均延时和平均缓存时间等性能指标上都体现出良好的性能。     

Integrated Social and QoS Trust-Based Routing in Delay Tolerant Networks

We propose and analyze a class of integrated social and quality of service (QoS) trust-based routing protocols in mobile ad-hoc delay tolerant networks. The underlying idea is to incorporate trust evaluation in the routing protocol, considering not only QoS trust properties but also social trust properties to evaluate other nodes encountered. We prove that our protocol is resilient against bad-mouthing, good-mouthing and whitewashing attacks performed by malicious nodes. By utilizing a stochastic Petri net model describing a delay tolerant network consisting of heterogeneous mobile nodes with vastly different social and networking behaviors, we analyze the performance characteristics of trust-based routing protocols in terms of message delivery ratio, message delay, and message overhead against connectivity-based, epidemic and PROPHET routing protocols. The results indicate that our trust-based routing protocols outperform PROPHET and can approach the ideal performance obtainable by epidemic routing in delivery ratio and message delay, without incurring high message overhead. Further, integrated social and QoS trust-based protocols can effectively trade off message delay for a significant gain in message delivery ratio and message overhead over traditional connectivity-based routing protocols.     

An optimized trusted‐cluster–based routing in disruption‐tolerant network using experiential learning model

Disruption‐tolerant network (DTN) implementation is subject to many routing constraints like limited knowledge of the network and intermittent connections with no end‐to‐end path existence. In this paper, the researchers propose trusted‐cluster–based routing protocol (TCR) for routing in DTN. TCR uses the experiential learning model that integrates neural network‐based bipolar sigmoid activation function to form trusted‐cluster DTN. TCR works in two phases: firstly to form a trusted‐cluster and secondly to identify cluster heads to direct network traffic through them. After the formation of the trusted‐cluster, a cluster head is chosen for a set period, thus instigating stability in the network. These trust values are attached to the node's route cache to make competitive routing decisions by relaying a message to the other trusted intermediate nodes only. With negative trust value, any node is deprived of participation in the network. This way, TCR eliminates malicious or selfish nodes to participate in the DTN network and minimizes the number of messages forwarded in a densely populated DTN. Also, this implementation conserves sufficient buffer memory to reach the destined node. The TCR's performance with other DTN routing schemes, namely, epidemic and trust‐based routing, is compared using multiple simulations runs. The proposed work is verified using mobility traces from Community Resource for Archiving Wireless Data At Dartmouth, and the experimental result shows the elimination of selfish nodes participating in the DTN. The simulation result shows an increase of 19% in message delivery by forwarding only to a trusted intermediate node possible.     

Assessing the influence of selfishness on the system performance of gossip based vehicular networks

In delay tolerant vehicular networks, gossip is an efficient forwarding scheme, which significantly reduces the message transmission overhead while maintaining a relatively high transmission rate in the high mobility vehicular environment. This mechanism requires vehicles as the network nodes to forward messages according to the system-defined gossip probability in a cooperative and selfless way among all the vehicles in the system. However, in the real word vehicular networks, most of the vehicular nodes exhibit selfish and non-collaboration behaviors to reduce the gossip probability in order to save their own energy and other limited resources in the vehicular nodes. In this paper, we study how node selfishness influences the performance of energy-constrained gossip forwarding based vehicular networks. We consider two typical forms of selfishness in the realistic vehicular networks: individual selfishness and social selfishness, and study the networking performance by focusing on the average message transmission delay and mean transmission cost. First, we model the message transmission process with selfish behaviors in the gossip forwarding based delay tolerant vehicular networks using a continuous time Markov chain. Based on this useful model, we derive closed-form formulae for average message transmission delay and mean transmission cost. Then, we give extensive numerical results to analyze the impact of selfishness on system performance of the vehicular networks. The results show that gossip forwarding in delay tolerant vehicular networks is robust to selfish behaviors since even when they increase the message transmission delay, there is a gain on the message transmission cost.     

Optimal mobility control with energy constraint in delay tolerant networks

Owing to the uncertainty of transmission opportunities between mobile nodes, the routing in delay tolerant networks (DTNs) exploits the mechanism of store‐carry‐and‐forward. In this routing mechanism, mobility plays an important role, and we need to control the mobility of nodes around the network to help with carrying messages from the source to the destination. This is a difficult problem because the nodes in the network may move arbitrarily and it is difficult for us to determine when the nodes should move faster to help the data transmission while considering the complicated energy consumption in such a network. At the same time, for most DTNs, the system energy is limited, and energy efficient algorithms are crucial to maximizing the message delivery probability while reducing the delivery cost. In this paper, we investigate the problem of energy efficient mobility speed control in epidemic routing of DTN. We model the message dissemination process under variable mobility speed by a continuous‐time Markov model. With this model, we then formulate the optimization problem of the optimal mobility control for epidemic routing and obtain the optimal policy from the solution of this optimization problem. Furthermore, extensive numerical results demonstrate that the proposed optimal policy significantly outperforms the static policy with constant speed, in terms of energy saving. Copyright © 2012 John Wiley & Sons, Ltd.     

An Improved Routing Algorithm Based on Social Link Awareness in Delay Tolerant Networks

The routing efficiency in delay tolerant networks is degraded due to intermittent connection and high latency. Additionally, socially selfish nodes in social networks refuse to provide message forwarding service since there are limited resources. To solve these problems, an improved routing algorithm based on the social link awareness is proposed. In this algorithm, multiple social features of the nodes’ behaviors are utilized to quantify the nodes pairs’ social links. The social links of the nodes pairs are computed based on their encounter history. These social links can be used to construct the friendship communities of the nodes. The intra-community and inter-community forwarding mechanisms are implemented to raise the successful delivery ratio with low overhead and decrease the transmission delay. Simulation results show that the proposed algorithm shortens the routing delay and increases the successful delivery ratio, thereby improving the routing efficiency.     

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。     

Extension of Delay Tolerant Network’s Routing Protocols for Preventing Excessive Utilization of Resources

The routing algorithms of DTN have the inbuilt storage management scheme such as Hop based TTL (Spray and Wait) or passive cure (Potential-based Entropy Adaptive Routing PEAR). There has been a significant amount of work in the past regarding buffer management policies. In this paper, we have proposed a new message deletion policy for multi-copy routing schemes. In this scheme, message delivery information is communicated to the other nodes in the network for removing useless bundles from the network, which prevents the nodes from the buffer overflow problem and avoid transfer of useless message replicas thus relaxing the resources of the nodes. We evaluate our proposed method by simulating network, on four major DTNs routing algorithms: Epidemic, Spray and Wait, ProPHET and MaxProp. The simulation results clearly show significant improvement in the value of delivery probability and the overhead ratio for an Epidemic, Spray and Wait, and Prophet routing protocols.     

An energy-aware deadline-constrained message delivery in delay-tolerant networks

In order to understand the message dissemination performance in delay-tolerant networks, much analysis work has been proposed in literature. However, existing work shares a common simplification that the pairwise inter-meeting time between any two mobile nodes is exponentially distributed. Not mention the fact that such assumption is only an approximation, it cannot be applied by network planners to directly control the mobile nodes for any network optimization, e.g., energy efficiency. It is quite significant to study the relationship between the network performance with the parameters that can be adjusted directly to tackle the limitations of current exponential distribution assumption based analysis. Therefore, in this paper, we are motivated to jointly consider the transmission range and messages residence time to stochastically analyze deadline-constrained message delivery ratio utilizing a controlled epidemic routing. The message propagation is considered as an age-structure process and described by a susceptible–infectious–recovered model, which is then analyzed using delay differential equations. Since both the transmission range and the message residence time are related to the mobile nodes’ energy consumption, we further apply our analysis framework to investigate the tradeoff between the energy consumption and the achievable message delivery ratio. The correctness and accuracy of our analysis are validated by extensive simulations.