A Markov chain model for drop ratio on one-packet buffers DTNs

Most of the efforts to characterize DTN routing are focused on the trade-off between delivery ratio and delay. Buffer occupancy is usually not considered a problem and most of the related work assumes infinite buffers. In the present work, we focus on the drop ratio for message forwarding considering finite buffers. We model message drops with a continuous time Markov chain (CTMC). To the best of our knowledge, there is no previous work with such approach. We focus on the worst case with 1-packet buffers for message forwarding in homogeneous inter-contact times (ICT) and 2-class heterogeneous ICT. Our main contribution is to link the encounter rate(s) with the drop ratio. We show that the modeled drop ratio fits simulation results obtained with synthetic traces for both cases

Spraying the replication probability with geographic assistance for Delay Tolerant Networks

Receiving great interest from the research community, Delay Tolerant Networks (DTNs) are a type of Next Generation Networks (NGNs) proposed to bridge communication in challenged environments. In this paper, the message replication probability is proportionally sprayed for efficient routing mainly under sparse scenario. This methodology is different from the spray based algorithms using message copy tickets to control replication. Our heuristic algorithm aims to overcome the scalability of the spray based algorithms, since to determine the initial value of the copy tickets requires the assumption that either the number of nodes is known in advance, or the underlying mobility model follows the Random WayPoint (RWP) characteristic. Specifically, in combining with the assistance of geographic information to estimate the movement range of destination, the routing decision is based on the encounter angle between pairwise nodes, and is dynamically switched between the designed two routing phases, named as geographic replication and replication probability spray. Furthermore, messages are under prioritized transmission with the consideration of redundancy pruning. Simulation results show our heuristic algorithm outperforms other well known algorithms in terms of delivery ratio, transmission overhead, average latency as well as buffer occupancy time. © 2012 IEEE

A trajectory-driven opportunistic routing protocol for VCPS

By exploring sensing, computing and communication capabilities on vehicles, Vehicular Cyber-Physical Systems (VCPS) are promising solutions to provide road safety and traffic efficiency in Intelligent Transportation Systems (ITS). Due to high mobility and sparse network density, VCPS could be severely affected by intermittent connectivity. In this paper, we propose a Trajectory-Driven Opportunistic Routing (TDOR) protocol, which is primarily applied for sparse networks, e.g., Delay/Disruption Tolerant Networks (DTNs). With geographic routing protocol designed in DTNs, existing works primarily consider the proximity to destination as a criterion for nexthop selections. Differently, by utilizing GPS information of onboard vehicle navigation system to help with data transmission, TDOR selects the relay node based on the proximity to trajectory. This aims to provide reliable and efficient message delivery, i.e., high delivery ratio and low transmission overhead. TDOR is more immune to disruptions, due to unfavorable mobility of intermediate nodes. Performance evaluation results show TDOR outperforms well known opportunistic geographic routing protocols, and achieves much lower routing overhead for comparable delivery ratio

A Reliable and Efficient Encounter-Based Routing Framework for Delay/Disruption Tolerant Networks

This article addresses Delay/Disruption Tolerant Networking (DTN) routing under a highly dynamic scenario, envisioned for communication in Vehicular Sensor Networks (VSNs) suffering from intermittent connection. Here, we focus on the design of a high level routing framework, rather than the dedicated encounter prediction. Based on an analyzed utility metric to predict nodal encounter, our proposed routing framework considers the following three cases: 1) Messages are efficiently replicated to a better qualified candidate node, based on the analysed utility metric related to destination. 2) Messages are conditionally replicated if the node with a better utility metric has not been met. 3) Messages are probabilistically replicated if the information in relation to destination is unavailable in the worst case. With this framework in mind, we propose two routing schemes covering two major technique branches in literature, namely Encounter-Based Replication Routing (EBRR) and Encounter-Based Spraying Routing (EBSR). Results under the scenario applicable to VSNs show that, in addition to achieving high delivery ratio for reliability, our schemes are more efficient in terms of a lower overhead ratio. Our core investigation indicates that apart from what information to use for encounter prediction, how to deliver messages based on the given utility metric is also important

Geographic-Based Spray-and-Relay (GSaR): An Efficient Routing Scheme for DTNs

In this article, we design and evaluate the proposed Geographic-based Spray-and-Relay (GSaR) routing scheme in Delay/Disruption Tolerant Networks (DTNs). To the best of our knowledge, GSaR is the first spray based geographic routing scheme using the historical geographic information for making routing decision. Here, the term spray means only a limited number of message copies are allowed for replication in the network. By estimating a movement range of destination via the historical geographic information, GSaR expedites message being sprayed towards this range, meanwhile prevents that away from and postpones that out of this range. As such, the combination of them intends to fast and efficiently spray the limited number of message copies towards this range, and effectively spray them within range, in order to reduce the delivery delay and increase the delivery ratio. Furthermore, GSaR exploits Delegation Forwarding (DF) to enhance the reliability of routing decision and handle the local maximum problem, considered as the challenges for applying geographic routing scheme in sparse networks. We evaluate GSaR under three city scenarios abstracted from real world, with other routing schemes for comparison. Results show that GSaR is reliable for delivering messages before expiration deadline and efficient for achieving low routing overhead ratio. Further observation indicates that GSaR is also efficient in terms of a low and fair energy consumption over the nodes in the network

The stability region of the delay in Pareto opportunistic networks

The intermeeting time, i.e., the time between two consecutive contacts between a pair of nodes, plays a fundamental role in the delay of messages in opportunistic networks. A desirable property of message delay is that its expectation is finite, so that the performance of the system can be predicted. Unfortunately, when intermeeting times feature a Pareto distribution, this property does not always hold. In this paper, assuming heterogeneous mobility and Pareto intermeeting times, we provide a detailed analysis of the conditions for the expectation of message delay to be finite (i.e., to converge) when social-oblivious or social-aware forwarding schemes are used. More specifically, we consider different classes of social-oblivious and social-aware schemes, based on the number of hops allowed and the number of copies generated. Our main finding is that, in terms of convergence, allowing more than two hops may provide advantages only in the social-aware case. At the same time, we show that using a multi-copy scheme can in general improve the convergence of the expected delay. We also compare social-oblivious and social-aware strategies from the convergence standpoint and we prove that, depending on the mobility scenario considered, social-aware schemes may achieve convergence while social-oblivious cannot, and vice versa. Finally, we apply the derived convergence conditions to three popular contact data sets available in the literature (Cambridge, Infocom, and RollerNet), assessing the convergence of each class of forwarding protocols in these three cases

Performance modelling of opportunistic forwarding under heterogenous mobility

The Delay Tolerant Networking paradigm aims to enable communications in disconnected environments where traditional protocols would fail. Oppor- tunistic networks are delay tolerant networks whose nodes are typically the users\u27 personal mobile devices. Communications in an opportunistic network rely on the mobility of users: each message is forwarded from node to node, according to a hop-by-hop decision process that selects the node that is better suited for bringing the message closer to its destination. Despite the variety of forwarding protocols that have been proposed in the recent years, there is no reference framework for the performance modelling of opportunistic for- warding. In this paper we start to ll this gap by proposing an analytical model for the rst two moments of the delay and the number of hops expe- rienced by messages when delivered in an opportunistic fashion. This model seamlessly integrates both social-aware and social-oblivious single-copy for- warding protocols, as well as dierent hypotheses for user contact dynamics. More specically, the model can be solved exactly in the case of exponential and Pareto inter-meeting times, two popular cases emerged from the liter- ature on human mobility analysis. In order to exemplify how the proposed framework can be used, we discuss its application to two case studies with dierent mobility settings. Finally, we discuss how the framework can be also solved exactly when inter-meeting times follow a hyper-exponential distribu- tion. This case is particularly relevant as hyper-exponential distributions are able to approximate the large class of high-variance distributions (distribu- tions with coecient of variation greater than one), which are those more challenging, e.g., from the delay standpoint