Social-context based routing and security in delay tolerant networks

Delay Tolerant Networks (DTNs) were originally intended for interplanetary communications and have been applied to a series of difficult environments: wireless sensor networks, unmanned aerial vehicles, and short-range personal communications. There is a class of such environments in which nodes follow semi-predictable social patterns, such as wildlife tracking or personal devices. This work introduces a series of algorithms designed to identify the social patterns present in these environments and apply this data to difficult problems, such as efficient message routing and content distribution. Security is also difficult in a mobile environment. This is especially the case in the event that a large portion of the network is unreliable, or simply unknown. As the network size increases nodes have difficulty in securely distributing keys, especially using low powered nodes with limited keyspace. A series of multi-party security algorithms were designed to securely transmit a message in the event that the sender does not have access to the destinations public key. Messages are routed through a series of nodes, each of which partially decrypts the message. By encrypting for several proxies, the message can only be intercepted if all those nodes have been compromised. Even a highly compromised network has increased security using this algorithm, with a trade-off of reduced delivery ratio and increased delivery time -- Abstract, page iv

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

Prediction and optimization techniques for performance enhancement of vehicular ad-hoc networks

Imperial Users onl

Efficient and adaptive congestion control for heterogeneous delay-tolerant networks

Detecting and dealing with congestion in delay-tolerant networks (DTNs) is an important and challenging problem. Current DTN forwarding algorithms typically direct traffic towards more central nodes in order to maximise delivery ratios and minimise delays, but as traffic demands increase these nodes may become saturated and unusable. We pro- pose CafRep, an adaptive congestion aware protocol that detects and reacts to congested nodes and congested parts of the network by using implicit hybrid contact and resources congestion heuristics. CafRep exploits localised relative utility based approach to offload the traffic from more to less congested parts of the network, and to replicate at adaptively lower rate in different parts of the network with non-uniform congestion levels. We extensively evaluate our work against benchmark and competitive protocols across a range of metrics over three real connectivity and GPS traces such as Sassy [44], San Francisco Cabs [45] and Infocom 2006 [33]. We show that CafRep performs well, independent of network connectivity and mobility patterns, and consistently outperforms the state-of-the-art DTN forwarding algorithms in the face of increasing rates of congestion. CafRep maintains higher availability and success ratios while keeping low delays, packet loss rates and delivery cost. We test CafRep in the presence of two application scenarios, with fixed rate traffic and with real world Facebook application traffic demands, showing that regardless of the type of traffic CafRep aims to deliver, it reduces congestion and improves forwarding performance

Forward correction and fountain codes in delay tolerant networks

Abstract—Delay tolerant Ad-hoc Networks make use of mobility of relay nodes to compensate for lack of permanent connectivity and thus enable communication between nodes that are out of range of each other. To decrease delivery delay, the information that needs to be delivered is replicated in the network. Our objective in this paper is to study replication mechanisms that include coding in order to improve the probability of successful delivery within a given time limit. We propose an analytical approach that allows to quantify tradeoffs between resources and performance measures (energy and delay). We study the effect of coding on the performance of the network while optimizing parameters that govern routing. Our results, based on fluid approximations, are compared to simulations which validate the model 1. Index Terms—Forward correction, fountain codes, delay tolerant networks I

Congestion control framework for delay-tolerant communications

Detecting and dealing with congestion in delay tolerant networks is an important and challenging problem. Current DTN forwarding algorithms typically direct traffic towards particular nodes in order to maximise delivery ratios and minimise delays, but as traffic demands increase these nodes may become unusable. This thesis proposes Café, an adaptive congestion aware framework that reduces traffic entering congesting network regions by using alternative paths and dynamically adjusting sending rates, and CafRep, a replication scheme that considers the level of congestion and the forwarding utility of an encounter when dynamically deciding the number of message copies to forward. Our framework is a fully distributed, localised, adaptive algorithm that evaluates a contact’s next-hop potential by means of a utility comparison of a number of congestion signals, in addition to that contact’s forwarding utility, both from a local and regional perspective. We extensively evaluate our work using two different applications and three real connectivity traces showing that, independent of the network inter-connectivity and mobility patterns, our framework outperforms a number of major DTN routing protocols. Our results show that both Café and CafRep consistently outperform the state-of-the-art algorithms, in the face of increasing traffic demands. Additionally, with fewer replicated messages, our framework increases success ratio and the number of delivered packets, and reduces the message delay and the number of dropped packets, while keeping node buffer availability high and congesting at a substantially lower rate, demonstrating our framework’s more efficient use of network resources

DTN Routing as a Resource Allocation Problem

Routing protocols for disruption-tolerant networks (DTNs) use a variety of mechanisms, including discovering the meeting probabilities among nodes, packet replication, and network coding. The primary focus of these mechanisms is to increase the likelihood of finding a path with limited information, and so these approaches have only an incidental effect on routing such metrics as maximum or average delivery delay. In this paper, we present rapid, an intentional DTN routing protocol that can optimize a specific routing metric such as the worst-case delivery delay or the fraction of packets that are delivered within a deadline. The key insight is to treat DTN routing as a resource allocation problem that translates the routing metric into per-packet utilities which determine how packets should be replicated in the system. We evaluate rapid rigorously through a prototype deployed over a vehicular DTN testbed of 40 buses and simulations based on real traces. To our knowledge, this is the first paper to report on a routing protocol deployed on a real DTN at this scale. Our results suggest that rapid significantly outperforms existing routing protocols for several metrics. We also show empirically that for small loads RAPID is within 10% of the optimal performance

DTN Routing as a Resource Allocation Problem

Routing protocols for disruption-tolerant networks (DTNs) use a variety of mechanisms, including discovering the meeting probabilities among nodes, packet replication, and network coding. The primary focus of these mechanisms is to increase the likelihood of finding a path with limited information, and so these approaches have only an incidental effect on routing such metrics as maximum or average delivery delay. In this paper, we present rapid, an intentional DTN routing protocol that can optimize a specific routing metric such as the worst-case delivery delay or the fraction of packets that are delivered within a deadline. The key insight is to treat DTN routing as a resource allocation problem that translates the routing metric into per-packet utilities which determine how packets should be replicated in the system. We evaluate rapid rigorously through a prototype deployed over a vehicular DTN testbed of 40 buses and simulations based on real traces. To our knowledge, this is the first paper to report on a routing protocol deployed on a real DTN at this scale. Our results suggest that rapid significantly outperforms existing routing protocols for several metrics. We also show empirically that for small loads RAPID is within 10% of the optimal performance

Congestion control framework for delay-tolerant communications

Detecting and dealing with congestion in delay tolerant networks is an important and challenging problem. Current DTN forwarding algorithms typically direct traffic towards particular nodes in order to maximise delivery ratios and minimise delays, but as traffic demands increase these nodes may become unusable. This thesis proposes Café, an adaptive congestion aware framework that reduces traffic entering congesting network regions by using alternative paths and dynamically adjusting sending rates, and CafRep, a replication scheme that considers the level of congestion and the forwarding utility of an encounter when dynamically deciding the number of message copies to forward. Our framework is a fully distributed, localised, adaptive algorithm that evaluates a contact’s next-hop potential by means of a utility comparison of a number of congestion signals, in addition to that contact’s forwarding utility, both from a local and regional perspective. We extensively evaluate our work using two different applications and three real connectivity traces showing that, independent of the network inter-connectivity and mobility patterns, our framework outperforms a number of major DTN routing protocols. Our results show that both Café and CafRep consistently outperform the state-of-the-art algorithms, in the face of increasing traffic demands. Additionally, with fewer replicated messages, our framework increases success ratio and the number of delivered packets, and reduces the message delay and the number of dropped packets, while keeping node buffer availability high and congesting at a substantially lower rate, demonstrating our framework’s more efficient use of network resources