Jó Ágila Bitsch

Enabling disruption tolerant services


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ISBN:

978-3-8440-5164-3

Reihe:

Reports on Communications and Distributed Systems
Herausgeber: Prof. Dr.-Ing. Klaus Wehrle
Aachen

Band:

Schlagwörter:

Disruption Tolerant Networking; Neighbor Discovery; Routing

Publikationsart:

Dissertation

Sprache:

Englisch

Seiten:

146 Seiten

Gewicht:

205 g

Format:

21 x 14,8 cm

Bindung:

Paperback

Preis:

35,80 € / 44,80 SFr

Erscheinungsdatum:

März 2017

Kaufen:

DOI:

10.2370/9783844051643 (Online-Gesamtdokument)

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Zusammenfassung:

Disruption tolerant networking allows us to provide communication and information services in low connectivity and challenged network scenarios. These range from previously underserved rural areas to highly energy constrained special purpose sensor networks. Compared to wired-to-the-last-hop, infrastructure-based networks, infrastructure-less networks face a number of additional challenges, the fundamental one being varying connectivity over time. Building successful services for disruption tolerant networking requires three different key steps: (1) identification and characterization of possible applications and services, (2) optimization of neighbor discovery, and (3) efficient routing of data bundles.

We developed an initial model for users and services in the context of disruption tolerant networks that combines the service communication structure, with user experience and user expectations to predict a user’s Quality of Experience. For this, we identify key characteristics of services and networks that make them suitable for challenged scenarios. These characteristics include: (1) Data Prefetching and Bundling, (2) Bursty Communication Style, (3) Soft Time Constraints, (4) Lenient Delivery Order Constraints, (5) One-Way Communication, and (6) Hop-to-Hop Usability. We propose initial quantitative metrics that may capture the user perceived quality. These metrics are: (1) Speed of Interaction, (2) Comfort and Frustration Level, (3) Delivery Effectiveness, and (4) Intercontact Times / Idle Period.

Overall, we argue that there is no particular killer app for DTNs, but rather, we show how considering these challenges to network communication in the design of an application can lead to a universally better experience for all users. In this context, we develop a set of sample applications particularly well-suited for challenging network environments, which are a collaborative event scheduling and a Wikipedia access application. We further explored map dissemination for indoor navigation and mobile sensor networks for wildlife monitoring.

We propose a new scheme for wireless neighbor discovery between unsynchronized nodes based on perfect difference sets. The construction is a mathematically provable optimal trade-off between the discovery delay and power consumption for discovering the presence of a potential communication partner in range. The application of Perfect Difference Sets (PDS) allows the provable optimal trade-off. Using PDS with a duty cycle of 2 % only has a discovery latency of about 4 min whereas U-Connect, the best related work, has a latency of 9 min, assuming a slot length of 100 ms. We further investigate discovery between devices with differing energy budgets. Through an exhaustive search of all possible combinations of schedule lengths and phase shifts, we show that PDS also performs fair in practice, that is with a duty cycle of greater or equal to 1%.

To enable efficient routing of messages, we model human mobility in a novel way using only local information. We propose two routing protocols: SimBetAge which bases on the frequency that particular people met in the past, and GeoDTN, which works on the frequency at which certain locations were visited in the past. Instead of modeling the social interactions in a binary graph, in SimBetAge, we capture the temporal change of a social network in a weighted graph. Edges in the graph degrade over time, if not refreshed. In turn, we extend the definition of similarity and betweenness to capture real-valued edge weights and further propose the directed ego flow betweenness as a novel metric to capture the usefulness of a node as a carrier for data bundles. We evaluated this approach against a number of existing routing schemes, in particular: Direct Delivery, Epidemic Routing, Prophet and the original SimBet. Using the MIT Reality Mining trace, the Haggle imote trace, and the Dartmouth Outdoor Experiment traces, we show that routing performance can be drastically improved when temporal changes are considered.

In GeoDTN, we modeled human mobility as a time dependent probability distribution around known anchor points. Based on this model, we developed a heuristic to predict future connectivity. To be able to evaluate this approach in the absence of widely deployed disruption tolerant consumer applications, we presented traces of self reported global mobility from an online social network website for 221 active users. The evaluation shows that geoDTN works similarly well as algorithms based on social group characteristics such as SimBetAge and outperforms binary movement algorithms as Move. In less periodic networks, geoDTN significantly outperformed the other algorithms in hop count and delivery time. It performs in general 130%, in individual cases even 200%, better in hop count. In terms of delivery time, it outperforms the related work on average by a factor of 3, PRoPHET by factor 6.

In combinations, these algorithms and methods can contribute to an overall disruption tolerant networking architecture, enabling improved services for all users, but in particular extending data network availability further into areas previously devoid of the otherwise necessary communication infrastructure.