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.     

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.     

Reasonable routing in delay/disruption tolerant networks

Delay/disruption tolerant networking (DTN) is an approach to networking where intermittent connectivity exists: it is often afforded by a store and forward technique. Depending on the capability of intermediary nodes to carry and forward messages, messages can be eventually delivered to their destination by mobile nodes with an appropriate routing protocol. To have achieved a successful delivery, most DTN routing protocols use message duplication methods. Although messages are rapidly transferred to the destination, the redundancy in the number of message copies increases rapidly. This paper presents a new routing scheme based on a stochastic process for epidemic routing. Message redundancy is efficiently reduced and the number of message copies is controlled reasonably. During the contact process of nodes in the network, the number of message copies changes, and according to the variability in the number of copies, we construct a special Markov chain, birth and death process, on the number of message copies then calculate and obtain a stationary distribution of the birth and death process. Comparing the theoretical model with the simulation we have performed we see similar results. Our method improves on time-to-live (TTL) and antipacket methods, in both redundancy and delivery success efficiency.     

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.     

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。     

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.     

一种面向机会网络路由的最优停止决策方法

投递延迟是机会网络的一个重要指标,给定节点缓存和消息副本数目限制,如何选择合适的节点复制消息成为一个关键问题.提出一种基于最优停止理论的路由决策方法（OSDR）.OSDR 将每个时隙上所遇节点和目标节点的平均相遇时间看做一个随机变量,根据该随机变量的统计特性得到一个停止观察、复制消息的规则,该规则呈现简单的阈值结构,即当某个时隙上所遇节点和目标节点的平均相遇时间小于给定阈值时即复制消息. OSDR 可以在较小的相遇间隔和等待成本之间进行折衷,实现数学期望意义上的最小消息投递延迟.介绍了OSDR 的网络模型、最优停止规则的存在性证明过程以及计算方法.模拟实验结果表明,OSDR 相对其他方法,在投递成功率、投递延迟等方面具有明显优势.     

An encounter-based multicast scheme for disruption tolerant networks

Some ad hoc network scenarios are characterized by frequent partitions and intermittent connectivity. Hence, existing ad hoc routing schemes that assume that an end-to-end path exists from a source to a destination do not work in such challenging environment. A store-and-forward network architecture known as the disruption tolerant network (DTN) has been designed for such challenging network environments. Several unicast and multicast routing schemes have been designed for DTNs. However, the existing multicast routing schemes assume a route discovery process that is similar to the existing ad hoc network routing approach. Thus, in this paper, we design an encounter-based multicast routing (EBMR) scheme for DTNs which uses fewer hops for message delivery. We first describe how the EBMR scheme works and then present an analytical framework to estimate the delivery performance of the EBMR scheme. Next, we present some comparisons of the analytical and simulation results to show that our analytical framework provides delivery performance estimates that match closely the observed simulation results. Last but not least, we present simulation results to study the delivery performance of EBMR in different scenarios, e.g. different mobility models, different multicast group size, different number of multicast groups and different node speed. We also compare the performance of the EBMR scheme with other DTN multicast strategies. Our simulation results indicate that the EBMR scheme can achieve higher delivery ratio while maintaining high data transmission efficiency compared to other multicast strategies.     

在分裂的机会网络中多个消息摆渡的路由设计

针对机会网络中节点分布不规则造成分割的网络区域相隔较远的情况, 提出了一种基于全局消息摆渡和节点中继的多摆渡路由算法（GMF-NRA）。该算法使用一个全局消息摆渡节点和各个区域内的中继节点为运行于区域内部的局部消息摆渡节点中继消息, 共同完成区域间的信息传输。摆渡节点在中继节点处交互区域间的信息, 以至于不再需要摆渡节点之间实现在线协作转发消息。最后, 仿真结果表明GMF-NRA较现有的节点中继算法在网络的平均传输时延和数据交付率方面能获得更好的网络性能。     

基于消息摆渡的DTN路由协议性能评估

通过分析消息摆渡方法对提升稀疏DTN(delay/disruption-tolerant networks)性能的可行性,提出了基于消息摆渡的DTNs的两种路由方案。使用网络模拟方法对多个路由协议在基于消息摆渡的DTNs中的性能作分析比较,实验表明,通过加入消息摆渡节点可以有效提高DTN路由协议在节点分布稀疏情况下的性能。     

GAER: genetic algorithm-based energy-efficient routing protocol for infrastructure-less opportunistic networks

In infrastructure-less opportunistic networks (Oppnets), the routing of messages is a challenging task since nodes are not aware of the network topology and they look for an opportunity to send the message by finding or predicting a best temporary path at each hop towards the destination. As nodes perform various computations for next hop selection, a lot of battery power gets consumed, which in turn reduces the network lifetime. Thus, there is a clear demand for routing protocols for such networks which are energy-efficient and consume lesser power of nodes in forwarding a message. In this paper, a novel routing protocol named genetic algorithm-based energy-efficient routing (GAER) protocol for infrastructure-less Oppnets is proposed. This protocol uses a node’s personal information, and then applies the genetic algorithm (GA) to select a better next hop among a group of neighbour nodes for the message to be routed to the destination. With the application of GA, optimal results are obtained that help in the selection of the best possible node as the next hop, which in turn, leads to prolonged battery life. Simulation results show that GAER outperforms the Epidemic, PROPHET, and Spray and Wait protocols in terms of messages delivered, overhead ratio, average residual energy, and number of dead nodes. The results obtained for average latency and average buffer time using GAER are comparable to those obtained for the aforementioned protocols.     

移动社会网络中基于社区的消息机会传输策略

移动社会网络是一种由大量具有社会特征的节点组成的机会网络.已有的基于社区的路由算法大多选用社会性最优的节点参与转发,而没有考虑到社区分布对节点移动的影响,将这些算法直接用于移动社会网络中会导致网络资源消耗高、传输成功率低等问题.针对这些问题,提出一种基于社区的消息机会传输算法,在社区间根据节点到目标社区的传输概率选择社区间的最优传输路径,在社区内选择与目标节点相遇概率较高的节点完成社区内传输.仿真实验结果表明,在移动社会网络中,该算法与 Prophet,Spray and Wait 等经典算法相比,提高了消息传输成功率,降低了网络开销.     

时延容忍网络的蔓延路由协议的研究

蔓延路由广泛应用于时延容忍网络(DTNs)。然而,传统的蔓延路由存在资源消耗过多问题,如节点能耗和消息缓存空间。即使消息已传递到目的节点,消息可能仍停留于节点的缓存区,直至消息过期,这会增加能耗。为此,对节点缓存空间的释放时间进行研究,并提出基于释放时间预测的蔓延路由,其目的在于通过减少消息占用缓存的时间,降低资源开销。基于蔓延路由特性,建立基于常微分方程的消息传播模型,并预测消息到达目的节点的时间,再在确保消息被最多节点传染的前提下,推导从缓存区内删除消息的准确时间(释放时间)。实验数据表明,与传统的蔓延路由相比,采用预测释放时间的蔓延路由在维持同等路由性能的同时,降低了能耗和开销。     

节点密度感知的容迟网络路由协议*

为适应容迟网络的动态变化,提高路由性能,结合空间节点分布和节点度中心性,提出一种节点密度感知的容迟网络路由协议DAR。该协议引入移动模型的节点分布,通过感知节点当前所处位置的节点密度,动态选择在网络中传播的消息副本数量,并根据节点的度中心性选择中继和分配消息副本数量。仿真结果表明,DAR能够提高传输率、降低传输延迟,在一定程度上降低了资源消耗。     

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。     

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.     

Dynamic Prediction based Multi Queue (DPMQ) drop policy for probabilistic routing protocols of delay tolerant network

Two most important issues should be considered to achieve data delivery in DTN networking: routing protocols for the network and intelligent buffer management policy for everyone node in the network. The routing scheme decides which messages should be forwarded when nodes meet, and the buffer management policy determines which message is purged when the buffer overflows in a node. This study proposes a buffer management policy named as Dynamic Prediction based Multi Queue (DPMQ) for probabilistic routing protocols. It works by classification of local buffer into three queues of messages, which are DCTL, HPTL and LPTL. The simulation results have proven that the DPMQ performs well as compared to DLA, DOA, MOFO, LIFO, LEPR and LIFO in terms of reducing the message relay, message drop, hop counts average and overhead while rising in the delivery probability.     

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。     

基于城市公共交通移动模型的协作延迟容忍网络路由策略

如何利用有限的传输机会可靠地传送车载服务感知信息是智能交通发展的“瓶颈”问题,利用公共交通中车辆的运动规律,提出基于节点之间机会接触来进行消息的逐跳转发策略,同时结合公共交通系统自身的特点,设计了一种基于公共交通移动模型的协作延迟容忍网络（DTN）路由算法TF。首先,根据公共交通移动模型自身的特点,将公交、长途客车等节点按其运动路径进行分组,提出一种基于固定运动路径分组的DTN路由算法;然后,将出租车、行人类节点定义为自由节点,并设计了一种基于转发因子控制的DTN路由策略作为分组路由机制的补充。仿真结果表明,与Epidemic、Prophet以及SAW路由算法相比,TF路由算法具有较高的消息投递率和较低的平均延迟。     

移动机会网络中面向聚集点的数据转发策略

移动机会网络利用节点接触进行数据转发的特点非常适合实际环境下的自主组网需求,促使了大量应用的产生.考虑到这些节点通常是由人或车来携带,人类行为的参与是这些应用成功的关键因素之一.探讨了人类的移动行为对机会网络中数据转发性能的影响,发现人们总是在一些热点区域之间往返,而很少访问其他区域.基于上述现象,提出了一种基于人类聚集点的机会路由策略——聚集分发策略(GS).GS假设每一个热点区域都配置一个接入点(AP),相对于其他移动节点,接入点有着较高的对信息进行缓存和分发的权限.理论分析证实GS的平均投递延迟低于喷雾-等待机制,仿真结果显示GS同时提高了数据包投递率.