5,242 research outputs found

    Content dissemination in participatory delay tolerant networks

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    As experience with the Web 2.0 has demonstrated, users have evolved from being only consumers of digital content to producers. Powerful handheld devices have further pushed this trend, enabling users to consume rich media (for example, through high resolution displays), as well as create it on the go by means of peripherals such as built-in cameras. As a result, there is an enormous amount of user-generated content, most of which is relevant only within local communities. For example, students advertising events taking place around campus. For such scenarios, where producers and consumers of content belong to the same local community, networks spontaneously formed on top of colocated user devices can offer a valid platform for sharing and disseminating content. Recently, there has been much research in the field of content dissemination in mobile networks, most of which exploits user mobility prediction in order to deliver messages from the producer to the consumer, via spontaneously formed Delay Tolerant Networks (DTNs). Common to most protocols is the assumption that users are willing to participate in the content distribution network; however, because of the energy restrictions of handheld devices, usersā€™ participation cannot be taken for granted. In this thesis, we design content dissemination protocols that leverage information about user mobility, as well as interest, in order to deliver content, while avoiding overwhelming noninterested users. We explicitly reason about battery consumption of mobile devices to model participation, and achieve fairness in terms of workload distribution. We introduce a dynamic priority scheduling framework, which enables the network to allocate the scarce energy resources available to support the delivery of the most desired messages. We evaluate this work extensively by means of simulation on a variety of real mobility traces and social networks, and draw a comparative evaluation with the major related works in the field

    The Quest for a Killer App for Opportunistic and Delay Tolerant Networks (Invited Paper)

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    Delay Tolerant Networking (DTN) has attracted a lot of attention from the research community in recent years. Much work have been done regarding network architectures and algorithms for routing and forwarding in such networks. At the same time as many show enthusiasm for this exciting new research area there are also many sceptics, who question the usefulness of research in this area. In the past, we have seen other research areas become over-hyped and later die out as there was no killer app for them that made them useful in real scenarios. Real deployments of DTN systems have so far mostly been limited to a few niche scenarios, where they have been done as proof-of-concept ļ¬eld tests in research projects. In this paper, we embark upon a quest to ļ¬nd out what characterizes a potential killer applications for DTNs. Are there applications and situations where DTNs provide services that could not be achieved otherwise, or have potential to do it in a better way than other techniques? Further, we highlight some of the main challenges that needs to be solved to realize these applications and make DTNs a part of the mainstream network landscape

    From MANET to people-centric networking: Milestones and open research challenges

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    In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications

    Effective and Efficient Communication and Collaboration in Participatory Environments

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    Participatory environments pose significant challenges to deploying real applications. This dissertation investigates exploitation of opportunistic contacts to enable effective and efficient data transfers in challenged participatory environments. There are three main contributions in this dissertation: 1. A novel scheme for predicting contact volume during an opportunistic contact (PCV); 2. A method for computing paths with combined optimal stability and capacity (COSC) in opportunistic networks; and 3. An algorithm for mobility and orientation estimation in mobile environments (MOEME). The proposed novel scheme called PCV predicts contact volume in soft real-time. The scheme employs initial position and velocity vectors of nodes along with the data rate profile of the environment. PCV enables efficient and reliable data transfers between opportunistically meeting nodes. The scheme that exploits capacity and path stability of opportunistic networks is based on PCV for estimating individual link costs on a path. The total path cost is merged with a stability cost to strike a tradeoff for maximizing data transfers in the entire participatory environment. A polynomial time dynamic programming algorithm is proposed to compute paths of optimum cost. We propose another novel scheme for Real-time Mobility and Orientation Estimation for Mobile Environments (MOEME), as prediction of user movement paves way for efficient data transfers, resource allocation and event scheduling in participatory environments. MOEME employs the concept of temporal distances and uses logistic regression to make real time estimations about user movement. MOEME relies only on opportunistic message exchange and is fully distributed, scalable, and requires neither a central infrastructure nor Global Positioning System. Indeed, accurate prediction of contact volume, path capacity and stability and user movement can improve performance of deployments. However, existing schemes for such estimations make use of preconceived patterns or contact time distributions that may not be applicable in uncertain environments. Such patterns may not exist, or are difficult to recognize in soft-real time, in open environments such as parks, malls, or streets

    SAROS: A social-aware opportunistic forwarding simulator

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    Many applications are being developed to leverage the popularity of mobile opportunistic networks. However, building adaptive testbeds can be costly and challenging. This challenge motivates the need for effective opportunistic network simulators to provide a variety of opportunistic environment setups, and evaluate proposed applications and protocols with a comprehensive set of metrics. This paper presents SAROS, a simulator of opportunistic networking environments with a variety of interest distributions, power consumption distributions, imported real traces, and social network integration. The simulator provides a wide variety of evaluation metrics that are not offered by comparable simulators. Finally, SAROS also implements several opportunistic forwarding algorithms ranging from social-oblivious algorithms to interest and power-aware social-based algorithms

    Internet Predictions

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    More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section

    Reputation aware obfuscation for mobile opportunistic networks

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    Ā© 2013 IEEE. Current anonymity techniques for mobile opportunistic networks typically use obfuscation algorithms to hide node's identity behind other nodes. These algorithms are not well suited to sparse and disconnection prone networks with large number of malicious nodes and new opportunistic, adaptive. So, new, opportunistic, adaptive fully localized mechanisms are needed for improving user anonymity. This paper proposes reputation aware localized adaptive obfuscation for mobile opportunistic networks that comprises of two complementary techniques: opportunistic collaborative testing of nodes' obfuscation behaviour (OCOT) and multidimensional adaptive anonymisation (AA). OCOT-AA is driven by both explicit and implicit reputation building, complex graph connectivity analytics and obfuscation history analyses. We show that OCOT-AA is very efficient in terms of achieving high levels of node identity obfuscation and managing low delays for answering queries between sources and destinations while enabling fast detection and avoidance of malicious nodes typically within the fraction of time within the experiment duration. We perform extensive experiments to compare OCOT-AA with several other competitive and benchmark protocols and show that it outperforms them across a range of metrics over a one month real-life GPS trace. To demonstrate our proposal more clearly, we propose new metrics that include best effort biggest length and diversity of the obfuscation paths, the actual percentage of truly anonymised sources' IDs at the destinations and communication quality of service between source and destination

    Efficient and adaptive congestion control for heterogeneous delay-tolerant networks

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    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
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