基于社会组的高投递率机会网络路由协议

针对现有的基于社会组的机会网络路由协议（SGBR）存在中继节点的选择和消息副本数量的分配不合理的问题,提出了基于社会组的高投递率机会网络路由协议（SGBRHDR）。SGBRHDR协议是一种采用分布式划分社会组的多副本路由协议。在社会组内,节点依据平均关系强度值决定相遇节点是否成为转发节点;在社会组间,节点依据相遇节点所在的社会组活跃性大小分配消息副本数量。采用ONE工具对SGBRHDR协议进行了仿真,仿真结果表明：与SGBR协议相比,SGBRHDR协议减小了消息平均端到端时延的同时,消息投递成功率提高了18%。     

社会感知多副本车载自组织网络机会路由协议

为提高车载自组织网络(vehicular Ad hoc networks, VANETs)中消息投递的效率, 提出了一种社会感知多副本车载自组织网络机会路由协议(SAMOR)。协议结合了车载自组织网络中节点的社会性特点和多副本路由方案的优势, 采用携带—存储—转发的机会路由方式进行消息投递。利用节点间的相遇历史区分社区节点和全局节点, 并使用所提出的节点社区中心性和网络中心性的度量方法, 得到了节点的效用。在路由过程的扩散阶段, 节点间按效用分配副本, 在转发阶段, 副本继续向效用高的节点转发。仿真结果表明, SAMOR实现了较高的消息投递成功率和较低的延迟。     

路口设施中继辅助车载自组织网络感染路由算法

随着智能交通系统和智慧城市的发展,路旁设施的部署将越来越普遍,城市环境下的车载自组织网络路由算法可以利用路旁设施中继辅助以提高算法的性能。为了解决感染路由算法在高负载场景下由于产生过多的消息副本而引起的路由性能剧烈下降问题,设计了路口设施辅助车载自组织网络感染路由算法IRAER。算法根据道路特点,将车辆的邻居节点划分为不同的区域,且在每个区域中仅选择一个候感节点进行感染,以降低消息副本数量,提高路由性能。另外,建立了随机模型与感染路由算法产生的副本数量进行了对比分析。理论分析和仿真实验结果均表明,所提出路由算法大大降低了在高节点密度场景下的副本数量和投递时延,提高了投递成功率。     

基于卡尔曼滤波理论的容迟与容断网络自适应感知路由算法

针对容迟与容断网络中的单播通信问题,提出了一种自适应感知路由协议(adaptive context aware routing protocol,ACRP);并引入卡尔曼滤波理论,给出最优的消息轮渡节点选取策略.仿真实验表明,与常见的单副本拷贝或多副本拷贝协议相比,提出的面向情境感知的自适应路由协议拥有更好的传输性能和稳定性.     

机会社会网络中基于社区的消息传输算法

针对机会网络中的主流转发协议未考虑到节点移动社会性的问题,提出一种基于副本限制和人类社会特性的路由算法。该算法根据节点间的社会关系强度,动态自适应地将节点划分为不同的社区,通过限制消息副本数来减少网络中消息的冗余,并利用活跃性高的节点带动消息的转发和传递。仿真结果表明,该协议能够保证较高的消息传输成功率和相对较低的传输时延,降低网络的资源消耗。     

无源感知网络中能耗和延迟平衡的机会路由协议

部署于野外的感知网络在应用时广泛存在节点能量不足的问题,而新型的使用能量收集技术的节点可以通过周期性地从环境中获取能量来延长网络的生存周期.因此,针对使用能量收集型节点的无源感知网络,能耗不再像有源节点网络那样成为制约网络性能最关键的因素.综合考虑能耗和延迟,可以在使节点获得较长生存周期的同时提高数据到达基站的速度.针对现有应用于无源感知网络的路由协议大多不能兼顾能耗和延迟性能的问题,提出了能耗和延迟平衡的机会路由协议（balance of energy and delay opportunistic routing protocol,简称EDOR）.该协议通过分析节点通信过程来估算节点的预期能耗值,使得节点选择令自己能耗较低的邻居节点作为转发候选.在最终确定转发节点时,该协议通过结合候选节点下一跳邻居节点的占空比信息来进行决策,使得发送节点选择能够更快将数据转发出去的候选节点来降低延迟,从而实现能耗和延迟性能的平衡.最后,该协议还通过设计退避策略来实现转发节点的单一性,减少机会路由过程中产生的不必要的数据包副本数量.     

移动传感网中基于虚拟货币的路由策略

移动无线传感器网络中,针对节点基于随机运动模型的路由问题,提出一种基于虚拟货币的低能耗路由策略——DTVC。根据节点的属性和数据消息的属性进行买方和卖方的定价并据此选择转发节点。为了提升网络性能,通过控制数据消息的副本数以及对节点的缓存队列中的数据消息排序,把网络中的节点分为源节点和中继节点,只有数据消息的源节点可以复制该数据消息,并依据数据消息的延迟容忍度对消息进行排序,延迟容忍度越小则优先级越高。为了减少网络中的能量消耗,根据sink节点广播的消息删除缓存队列中已经传输成功的数据消息。在Matlab上的仿真实验结果表明,与基于消息容错的自适应数据传输算法（FAD）、基于距离和能量感知模糊逻辑的路由算法（FLDAER）和基于能耗自选演进机制的路由算法相比,DTVC的数据消息投递率至少提高2.5%,平均副本数至少减少25%。     

稀疏机会网络中基于固定中继节点与消息相关性的缓存管理策略

针对稀疏机会网络中固定中继节点和移动节点间的相遇频率以及缓存资源的差异性问题,在多副本路由协议中,提出一种结合固定中继节点重要性和消息相关性的缓存管理策略。该策略通过交互固定节点和移动节点的接触信息和消息队列信息,减少固定中继节点缓存中冗余消息的数量,从而合理地利用固定中继节点的缓存资源。仿真结果表明,所提的缓存管理策略能够在保证消息传输成功率的基础上提高固定中继节点缓存空间的利用率。     

一种基于历史相遇信息的容迟网络地理路由算法

为使消息在容迟网络中更有效地传输,将节点的地理位置、移动方向等地理信息与节点间的历史相遇频繁程度相结合,提出一种新的容迟网络地理路由算法。该算法将移动节点间的历史相遇信息作为分配消息副本的依据,从而减少复制策略路由算法中的副本数量。利用邻居节点移动方向所构成的夹角对中继节点的选择进一步优化,得到较高的投递率以及较低的端到端平均时延。仿真结果表明,当节点移动相对缓慢并且消息生存周期较短时,该算法的消息投递率优于Spray&Wait,Epidemic,Prophet等路由算法,在消息生存周期较短的情况下,当节点的缓存资源为限制路由算法性能的瓶颈因素时,与Epidemic算法相比,网络负载率降低40%,与Prophet算法相比负载降低了25%,有效减少了平均跳数和平均时延。     

基于PROPHET路由算法的缓冲区管理

DTN网络一般采用基于消息复制的随机路由策略,由于网络中存在大量的消息副本,因此会导致中间节点缓冲区占用大,出现拥塞。为此,从冗余控制角度出发,基于PROPHET路由算法,设计用于缓冲区管理的3种机制,包括消息副本数量的控制、数据包生存期的动态设置以及已成功传输数据包的主动删除。通过限制消息副本数和删除多余消息,降低网络中消息副本总量,从而减轻节点负载。实验结果表明,在网络资源有限的情况下,上述3种机制能提高消息的成功传输率,降低网络开销。     

TB-SnW: Trust-based Spray-and-Wait routing for delay-tolerant networks

Unlike the conventional routing techniques in Internet where routing privileges are given to trustworthy and fully authenticated nodes, delay-tolerant networks (DTNs) allow any node to participate in routing due to the lack of consistent infrastructure and central administration. This creates new security issues since even authorized nodes in DTNs could inject several malicious threats into the network. This paper investigates the problem of mitigating blackhole attacks in DTNs based on the Spray-and-Wait routing protocol. A new knowledge-based routing scheme, called Trust-Based Spray-and-Wait protocol (TB-SnW), is designed based on distributed trust management. Each node maintains the trust levels for encountered nodes based on the message exchange history, and uses the trust levels to smartly distribute message copies to bypass blackhole attackers. Simulation results demonstrate that, compared with Spray-and-Wait, TB-SnW can achieve higher message delivery rate with very low communication overhead in DTNs that suffer from blackhole attacks.     

Spray and forward:Efficient routing based on the Markov location prediction model for DTNs

Typical delay tolerant networks(DTNs)often suffer from long and variable delays,frequent connectivity disruptions,and high bit error rates.In DTNs,the design of an efficient routing algorithm is one of the key issues.The existing methods improve the accessibility probability of the data transmission by transmitting many copies of the packet to the network,but they may cause a high network overhead.To address the tradeoff between a successful delivery ratio and the network overhead,we propose a DTN routing algorithm based on the Markov location prediction model,called the spray and forward routing algorithm(SFR).Based on historical information of the nodes,the algorithm uses the second-order Markov forecasting mechanism to predict the location of the destination node,and then forwards the data by greedy routing,which reduces the copies of packets by spraying the packets in a particular direction.In contrast to a fixed mode where a successful-delivery ratio and routing overhead are contradictory,a hybrid strategy with multi-copy forwarding is able to reduce the copies of the packets efficiently and at the same time maintain an acceptable successful-delivery ratio.The simulation results show that the proposed SFR is efficient enough to provide better network performance than the spray and wait routing algorithm,in scenarios with sparse node density and fast mobility of the nodes.     

Leapfrog: Optimal Opportunistic Routing in Probabilistically Contacted Delay Tolerant Networks

Delay tolerant networks (DTNs) experience frequent and long lasting network disconnection due to various reasons such as mobility, power management, and scheduling. One primary concern in DTNs is to route messages to keep the end-to-end delivery delay as low as possible. In this paper, we study the single-copy message routing problem and propose an optimal opportunistic routing strategy – Leapfrog Routing – for probabilistically contacted DTNs where nodes encounter or contact in some fixed probabilities. We deduce the iterative computation formulate of minimum expected opportunistic delivery delay from each node to the destination, and discover that under the optimal opportunistic routing strategy, messages would be delivered from high-delay node to low-delay node in the leapfrog manner. Rigorous theoretical analysis shows that such a routing strategy is exactly the optimal among all possible ones. Moreover, we apply the idea of Reverse Dijkstra algorithm to design an algorithm. When a destination is given, this algorithm can determine for each node the routing selection function under the Leapfrog Routing strategy. The computation overhead of this algorithm is only O(n ²) where n is the number of nodes in the network. In addition, through extensive simulations based on real DTN traces, we demonstrate that our algorithm can significantly outperform the previous ones.     

ML-SOR: Message routing using multi-layer social networks in opportunistic communications

Opportunistic networks are a generalization of DTNs in which disconnections are frequent and encounter patterns between mobile devices are unpredictable. In such scenarios, message routing is a fundamental issue. Social-based routing protocols usually exploit the social information extracted from the history of encounters between mobile devices to find an appropriate message relay. Protocols based on encounter history, however, take time to build up a knowledge database from which to take routing decisions. While contact information changes constantly and it takes time to identify strong social ties, other types of ties remain rather stable and could be exploited to augment available partial contact information. In this paper, we start defining a multi-layer social network model combining the social network detected through encounters with other social networks and investigate the relationship between these social network layers in terms of node centrality, community structure, tie strength and link prediction. The purpose of this analysis is to better understand user behavior in a multi-layered complex network combining online and offline social relationships. Then, we propose a novel opportunistic routing approach ML-SOR (Multi-layer Social Network based Routing) which extracts social network information from such a model to perform routing decisions. To select an effective forwarding node, ML-SOR measures the forwarding capability of a node when compared to an encountered node in terms of node centrality, tie strength and link prediction. Trace driven simulations show that a routing metric combining social information extracted from multiple social network layers allows users to achieve good routing performance with low overhead cost.     

A routing defense mechanism using evolutionary game theory for Delay Tolerant Networks

Delay Tolerant Networks (DTNs) often suffer from intermittent disruption due to factors such as mobility and energy. Though lots of routing algorithms in DTNs have been proposed in the last few years, the routing security problems have not attracted enough attention. DTNs are still facing the threats from different kinds of routing attacks. In this paper, a general purpose defense mechanism is proposed against various routing attacks on DTNs. The defense mechanism is based on the routing path information acquired from the forwarded messages and the acknowledgment (ACK), and it is suitable for different routing schemes. Evolutionary game theory is applied with the defense mechanism to analyze and facilitate the strategy changes of the nodes in the networks. Simulation results show that the proposed evolutionary game theory based defense scheme can achieve high average delivery ratio, low network overhead and low average transmission delay in various routing attack scenarios. By introducing the game theory, the networks can avoid being attacked and provide normal transmission service. The networks can reach evolutionary strategy stable (ESS) under special conditions after evolution. The initial parameters will affect the convergence speed and the final ESS, but the initial ratio of the nodes choosing different strategies can only affect the game process.     

Look-Ahead Routing and Message Scheduling in Delay-Tolerant Networks

Routing is one of the most challenging development issues in Delay-Tolerant Networks (DTNs) because of lack of continuous connection. Existing routing schemes for DTNs provide best effort service, but are unable to optimize QoS and support message priority. In this paper, we present a Look-Ahead Routing and Message Scheduling approach (ALARMS) which exploits more accurate knowledge about various parameters regarding routing to achieve better QoS in the DTN. We assume a variation of the well-known ferry model, in which there are ferry nodes moving along pre-defined routes to exchange messages with the gateway node of each region on the route and also pass to the gateway nodes look-ahead routing information about when it will arrive at each gateway node on the route in the next two rounds and how long it will stay. The gateway nodes use this information to estimate the delivery delay of each message when being delivered by different ferries, and schedule the message to be delivered by the ferry which arrives earliest at the destination. Simulation results show that ALARMS outperforms three existing routing protocols: epidemic routing, Spray-and-Wait, and Spray-and-Focus, in terms of delay time, delivery ratio, and overhead. We also discuss five enhancement strategies on ALARMS and how ALARMS can support message prioritization.     

SmallWorld Model-Based Polylogarithmic Routing Using Mobile Nodes

The use of mobile nodes to improve network system performance has drawn considerable attention recently. The movement-assisted model considers mobility as a desirable feature,where routing is based on the store-carry-forward paradigm with random or controlled movement of resource rich mobile nodes.The application of such a model has been used in several emerging networks,including mobile ad hoc networks(MANETs),wireless sensor networks(WSNs),and delay tolerant networks(DTNs).It is well known that mobility increases the capacity of MANETs by reducing the number of relays for routing,prolonging the lifespan of WSNs by using mobile nodes in place of bottleneck static sensors,and ensuring network connectivity in DTNs using mobile nodes to connect different parts of a disconnected network.Trajectory planning and the coordination of mobile nodes are two important design issues aiming to optimize or balance several measures, including delay,average number of relays,and moving distance.In this paper,we propose a new controlled mobility model with an expected polylogarithmic number of relays to achieve a good balance among several contradictory goals,including delay,the number of relays,and moving distance.The model is based on the small-world model where each static node has"short"link connections to its nearest neighbors and"long"link connections to other nodes following a certain probability distribution.Short links are regular wireless connections whereas long links are implemented using mobile nodes.Various issues are considered,including trade-offs between delay and average number of relays,selection of the number of mobile nodes,and selection of the number of long links.The effectiveness of the proposed model is evaluated analytically as well as through simulation.     

DTN中基于节点质量的自适应散发和等待路由

针对节点活动性的差异,给出了节点质量的定义,提出了基于节点质量的自适应散发和等待路由协议。该协议通过引入节点质量的观点来动态地转发报文拷贝数,从而避免了二分散发和等待路由协议在转发报文拷贝数时的盲目性。仿真结果显示,该协议更能够适应自组织状况下动态的网络拓扑,在改善报文递交率和延迟的同时能显著提高报文的递交效用、减小网络开销率。     

延迟容忍网络中路径失效问题的容错研究

延迟容忍网络的路由机制与传统的网络结构有很大不同。针对这类网络中的路径失效问题进行容错研究使得网络在出现路径失效时,能够不影响消息传送,并尽可能地提高消息的成功交付率,从而屏蔽路径失效问题。首先描述了延迟容忍网络中的一种路径失效问题,反映了在路径完全正常、存在部分失效以及完全失效情况下消息交付情况,并针对这一问题研究相应的容错方法。最后给出一个交通延迟容忍网络应用实例,并评价其容错方法的性能。