Delay and Disruption Tolerant Networks (DTNs) may lack continuous network connectivity. Routing in DTNs is thus a challenge since it must handle network partitioning, long delays, and dynamic topology. Meanwhile, routing protocols of the traditional Mobile Ad hoc NETworks (MANETs) cannot work well due to the failure of its assumption that most network connections are available. In this article, a geographic routing protocol is proposed for MANETs in delay tolerant situations, by using no more than one-hop information. A utility function is designed for implementing the under-controlled replication strategy. To reduce the overheads caused by message flooding, we employ a criterion so as to evaluate the degree of message redundancy. Consequently a message redundancy coping mechanism is added to our routing protocol. Extensive simulations have been conducted and the results show that when node moving speed is relatively low, our routing protocol outperforms the other schemes such as Epidemic, Spray and Wait, FirstContact in delivery ratio and average hop count, while introducing an acceptable overhead ratio into the network.
Until currently, a set of congestion control mechanisms have been proposed in Deterministic DTNs, which is mainly implemented in the network with limited mobility or the static network with scheduled disruption interval. @cite_16 propose an active congestion control based routing algorithm that pushes the selected message before the congestion happens. @cite_14 propose a novel node-based replication management algorithm which addresses buffer congestion by dynamically limiting the replication a node performs during each encounter. @cite_13 use information about queue backlogs, random walk and data packet scheduling nodes to make packet routing and forwarding decisions without the notion of end-to-end routes. Furthermore, @cite_2 proposes a two-level Back-Pressure with Source-Routing algorithm (BP+SR), which reduced the number of queues required at each node and reduced the size of the queues, thereby reducing the end-to-end delay.
@cite_14 @cite_16 @cite_13 @cite_2
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The widespread availability of mobile wireless devices offers growing opportunities for the formation of temporary networks with only intermittent connectivity. These intermittently-connected networks (ICNs) typically lack stable end-to-end paths. In order to improve the delivery rates of the networks, new store-carry-and-forward protocols have been proposed which often use message replication as a forwarding mechanism. Message replication is effective at improving delivery, but given the limited resources of ICN nodes, such as buffer space, bandwidth and energy, as well as the highly dynamic nature of these networks, replication can easily overwhelm node resources. In this work we propose a novel node-based replication management algorithm which addresses buffer congestion by dynamically limiting the replication a node performs during each encounter. The insight for our algorithm comes from a stochastic model of message delivery in ICNs with constrained buffer space. We show through simulation that our algorithm is effective, nearly tripling delivery rates in some scenarios, and imposes little overhead. Opportunistic Networks (ONs) utilize the communication opportunity with a hop-by-hop behavior, and implement communication between encountered nodes based on the Store-and-Forward routing pattern. This approach, which is totally different from the traditional communication model, has received extensive interests from academic community. We consider the ONs are a type of Delay Tolerant Networks (DTNs) since their routing behavior are quite same regardless of the bundle layer protocol. Until currently, a set of congestion control mechanisms have been proposed in Deterministic DTNs, which is mainly implemented in the network with limited mobility or the static network with scheduled disruption interval. However, regarding the networks with large topology variation, known as Opportunistic DTNs, to design a congestion control mechanism is difficult. In this paper, we propose an active congestion control based routing algorithm that pushes the selected message before the congestion happens. In order to predict the future congestion situation, a corresponding estimation function is designed and our proposed algorithm works based on two asynchronous routing functions, which are scheduled according to the decision of estimation function. Simulation results show our proposed algorithm efficiently utilizes the distributed storage to achieve a quite low overhead ratio and also performs well in the realistic scenario. In this paper we consider an alternative, highly agile In this paper we consider an alternative, highly agile approach called backpressure routing for Delay Tolerant Networks (DTN), in which routing and forwarding decisions are made on a per-packet basis. Using information about queue backlogs, random walk and data packet scheduling nodes can make packet routing and forwarding decisions without the notion of end-to-end routes. To the best of our knowledge, this is the first ever implementation of dynamic backpressure routing in DTNs. Simulation results show that the proposed approach has advantages in terms of DTN networks. We study a mobile wireless network where groups or clusters of nodes are intermittently connected via mobile carriers'' (the carriers provide connectivity over time among different clusters of nodes). Over such networks (an instantiation of a delay tolerant network), it is well-known that traditional routing algorithms perform very poorly. In this paper, we propose a two-level Back- Pressure with Source-Routing algorithm (BP+SR) for such networks. The proposed BP+SR algorithm separates routing and scheduling within clusters (fast time-scale) from the communications that occur across clusters (slow time-scale), without loss in network throughput (i.e., BP+SR is throughput-optimal). More importantly, for a source and destination node that lie in different clusters, the traditional back-pressure algorithm results in large queue lengths at each node along its path. This is because the queue dynamics are driven by the slowest time-scale (i.e., that of the carrier nodes) along the path between the source and destination, which results in very large end-to-end delays. On the other-hand, we show that the two-level BP+SR algorithm maintains large queues only at a very few nodes, and thus results in order-wise smaller end-to-end delays. We provide analytical as well as simulation results to confirm our claims.