Intermittently connected mobile networks are sparse wireless networks where most of the time there does not exist a complete path from the source to the destination. These networks

Delay-tolerant networks (DTNs) have the potential to connect devices and areas of the world that are under-served by current networks. A critical challenge for DTNs is determining routes through the network without ever having an end-to-end connection, or even knowing which “routers ” will be connected at any given time. Prior approaches have focused either on epidemic message replication or on knowledge of the connectivity schedule. The epidemic approach of replicating messages to all nodes is expensive and does not appear to scale well with increasing load. It can, however, operate without any prior network configuration. The alternatives, by requiring a priori connectivity knowledge, appear infeasible for a self-configuring network. In this paper we present a practical routing protocol that only uses observed information about the network. We designed a metric that estimates how long a message will have to wait before it can be transferred to the next hop. The topology is distributed using a link-state routing protocol, where the link-state packets are “flooded ” using epidemic routing. The routing is recomputed when connections are established. Messages are exchanged if the topology suggests that a connected node is “closer ” than the current node. We demonstrate through simulation that our protocol provides performance similar to that of schemes that have global knowledge of the network topology, yet without requiring that knowledge. Further, it requires a significantly smaller quantity of buffer, suggesting that our approach will scale with the number of messages in the network, where replication approaches may not.

Abstract — Intermittently connected mobile networks are wireless networks where most of the time there does not exist a complete path from source to destination, or such a path is highly unstable and may break soon after it has been discovered. In this context, conventional routing schemes would fail. To deal with such networks we propose the use of an opportunistic hop-by-hop routing model. According to the model, a series of independent, local forwarding decisions are made, based on current connectivity and predictions of future connectivity information diffused through nodes’ mobility. The important issue here is how to choose an appropriate next hop. To this end, we propose and analyze via theory and simulations a number of routing algorithms. The champion algorithm turns out to be one that combines the simplicity of a simple random policy, which is efficient in finding good leads towards the destination, with the sophistication of utility-based policies that efficiently follow good leads. We also state and analyze the performance of an oracle-based optimal algorithm, and compare it to the online approaches. The metrics used in the comparison are the average message delivery delay and the number of transmissions per message delivered. I.

Traditionally, ad hoc networks have been viewed as a connected graph over which end-to-end routing paths had to be established. Mobility was considered a necessary evil thatinvalidatespathsandneedstobeovercomeinanintelligent way to allow for seamless communication between nodes. However, it has recently been recognized that mobility can be turned into a useful ally, by making nodes carry data around the network instead of transmitting them. This model of routing departs from the traditional paradigm and requires new theoretical tools to model its performance. A mobility-assisted protocol forwards data only when appropriate relays encounter each other, and thus the time between such encounters, called hitting or meeting time, is of high importance. In this paper, we derive accurate closed form expressions for the expected encounter time between different nodes, under commonly used mobility models. We also propose a mobility model that can successfully capture some important real-world mobility characteristics, often ignored in popular mobility models, and calculate hitting times for this model as well. Finally, we integrate this results with a general theoretical framework that can be used to analyze the performance of mobility-assisted routing schemes. We demonstrate that derivative results concerning the delay of various routing schemes are very accurate, under all the mobility models examined. Hence, this work helps in better understanding the performance of various approaches in different settings, and can facilitate the design of new, improved protocols.

Intermittently connected mobile networks are wireless networks where most of the time there does not exist a complete path from the source to the destination. There are many real networks that follow this model, for example, wildlife tracking sensor networks, military networks, vehicular ad hoc networks (VANETs), etc. To deal with such networks researchers have suggested to use controlled replication or “spraying ” methods that can reduce the overhead of flooding-based schemes by distributing a small number of copies to only a few relays. These relays then “look” for the destination in parallel as they move into the network. Although such schemes can perform well in scenarios with high mobility (e.g. VANETs), they struggle in situations were mobility is slow and correlated in space and/or time. To route messages efficiently in such networks, we propose a scheme that also distributes a small number of copies to few relays. However, each relay can then forward its copy further using a single-copy utility-based scheme, instead of naively waiting to deliver it to the destination itself. This scheme exploits all the advantages of controlled replication, but is also able to identify appropriate forwarding opportunities that could deliver the message faster. Simulation results for traditional mobility models, as well as for a more realistic “community-based ” model, indicate that our scheme can reduce the delay of existing spraying techniques up to 20 times in some scenarios. 1

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In this paper we analyze multiple wireless LAN (WLAN) traces from university and corporate campuses. In particular, we consider an important event between mobile nodes in wireless networks – encounters. We seek to understand encounter patterns in the mobile network from a holistic view by a graph analysis approach. Such an analysis sheds light on the diverse, non-homogeneous nature of users in the given environments in terms of their encounter events with other nodes. Furthermore, we evaluate the feasibility of forming an infrastructure-less network to reach most of the nodes utilizing time-varying inter-node connectivity through encounters, and the robustness of such an ad hoc communication network. Our analysis shows that while the encounter events are “sparse ” (i.e., any given node does not encounter with many other nodes), the connectivity of the whole network is well-maintained, and a Small World pattern of nodal encounter emerges for the observation periods longer than one day. More interestingly, the encounter events collectively form a robust communication network, in which store-carry-forward message dissemination can be mostly successful with at least 20 % of non-cooperative nodes or removal of short-lived (up to minutes) encounter events.

Forwarding in Delay Tolerant Networks(DTNs) is a challenging problem. We focus on the specific issue of forwarding in an environment where mobile devices are carried by people in a restricted physical space (a conference) and contact patterns are not predictable. We show for the first time a path explosion phenomenon between most pairs of nodes. This means that, once the first path reaches the destination, the number of subsequent paths grows rapidly with time, so there usually exist many near-optimal paths. We study the path explosion phenomenon both analytically and empirically. Our results highlight the importance of unequal contact rates across nodes for understanding the performance of forwarding algorithms. We also find that a variety of well-known forwarding algorithms show surprisingly similar performance in our setting and we interpret this fact in light of the path explosion phenomenon.

Abstract — In this work we study WLAN traces from five different sources and focus on investigation of encounter patterns between users. We find that typical wireless LAN users encounter with a small portion of the whole population (no more than 60 % in all traces, and on average between 1.88 % to 6.70%). Total encounters of MNs follow BiPareto distribution. These few encounters are sufficient to build a connected relationship network, which is a Small World graph. We further investigate the potential of node-to-node information diffusion, and find that the richness of encounter pattern provides a reliable platform on which information diffusion without infrastructure is feasible and robust. I.

Abstract—Delay Tolerant Networks are wireless networks where disconnections may occur frequently due to propagation phenomena, node mobility, and power outages. Propagation delays may also be long due to the operational environment (e.g. deep space, underwater). In order to achieve data delivery in such challenging networking environments, researchers have proposed the use of store-carry-and-forward protocols: there, a node may store a message in its buffer and carry it along for long periods of time, until an appropriate forwarding opportunity arises. Additionally, multiple message replicas are often propagated to increase delivery probability. This combination of long-term storage and replication imposes a high storage overhead on untethered nodes (e.g. handhelds). Thus, efficient buffer management policies are necessary to decide which messages should be discarded, when node buffers are operated close to their capacity. In this paper, we propose efficient buffer management policies for delay tolerant networks. We show that traditional buffer management policies like drop-tail or drop-front fail to consider all relevant information in this context and are, thus, sub-optimal. Using the theory of encounter-based message dissemination, we propose an optimal buffer management policy based on global knowledge about the network. Our policy can be tuned either to minimize the average delivery delay or to maximize the average delivery rate. Finally, we introduce a distributed algorithm that uses statistical learning to approximate the global knowledge required by the the optimal algorithm, in practice. Using simulations based on a synthetic mobility model and real mobility traces, we show that our buffer management policy based on statistical learning successfully approximates the performance of the optimal policy in all considered scenarios. At the same time, our policy outperforms existing ones in terms of both average delivery rate and delivery delay. I.