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Making the Most of Your Contacts: Transfer Ordering in Data-Centric Opportunistic Networks
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. (Communication Research)
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. (Communication Research)
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. (Communication Research)
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. (Communication Research)
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2012 (English)In: Proceedings of the 2012 ACM MobiOpp Workshop on Mobile Opportunistic Networks, Zürich: ACM Press, 2012Conference paper, Published paper (Refereed)
Abstract [en]

Opportunistic networks use unpredictable and time-limited con- tacts to disseminate data. Therefore, it is important that protocols transfer useful data when contacts do occur. Specifically, in a data- centric network, nodes benefit from receiving data relevant to their interests. To this end, we study five strategies to select and order the data to be exchanged during a limited contact, and measure their ability to promptly and efficiently deliver highly relevant data.

Our trace-driven experiments on an emulation testbed suggest that nodes benefit in the short-term from ordering data transfers to satisfy local interests. However, this can lead to suboptimal longterm system performance. Restricting sharing based on matching nodes’ interests can lead to segregation of the network, and limit useful dissemination of data. A non-local understanding of other nodes’ interests is necessary to effectively move data across the network. If ordering of transfers for data relevance is not explicitly considered performance is comparable to random, which limits the delivery of individually relevant data. 

Place, publisher, year, edition, pages
Zürich: ACM Press, 2012.
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:uu:diva-171587OAI: oai:DiVA.org:uu-171587DiVA: diva2:511649
Conference
ACM MobiOpp
Projects
ResumeNet
Available from: 2012-03-22 Created: 2012-03-22 Last updated: 2014-06-30
In thesis
1. Opportunistic Networking: Congestion, Transfer Ordering and Resilience
Open this publication in new window or tab >>Opportunistic Networking: Congestion, Transfer Ordering and Resilience
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Opportunistic networks are constructed by devices carried by people and vehicles. The devices use short range radio to communicate. Since the network is mobile and often sparse in terms of node contacts, nodes store messages in their buffers, carrying them, and forwarding them upon node encounters. This form of communication leads to a set of challenging issues that we investigate: congestion, transfer ordering, and resilience.

Congestion occurs in opportunistic networks when a node's buffers becomes full. To be able to receive new messages, old messages have to be evicted. We show that buffer eviction strategies based on replication statistics perform better than strategies that evict messages based on the content of the message.

We show that transfer ordering has a significant impact on the dissemination of messages during time limited contacts. We find that transfer strategies satisfying global requests yield a higher delivery ratio but a longer delay for the most requested data compared to satisfying the neighboring node's requests.

Finally, we assess the resilience of opportunistic networks by simulating different types of attacks. Instead of enumerating all possible attack combinations, which would lead to exhaustive evaluations, we introduce a method that use heuristics to approximate the extreme outcomes an attack can have. The method yields a lower and upper bound for the evaluated metric over the different realizations of the attack. We show that some types of attacks are harder to predict the outcome of and other attacks may vary in the impact of the attack due to the properties of the attack, the forwarding protocol, and the mobility pattern.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2014. 45 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1148
Keyword
Opportunistic Networking, Congestion, Transfer Ordering, Resilience, Testbed, WISENET
National Category
Computer Science Communication Systems
Research subject
Computer Science with specialization in Computer Communication
Identifiers
urn:nbn:se:uu:diva-223492 (URN)978-91-554-8953-3 (ISBN)
Public defence
2014-06-09, Room 2446, Polacksbacken, Lägerhyddsvägen 2, Uppsala, 13:15 (English)
Opponent
Supervisors
Projects
WISENET
Available from: 2014-05-15 Created: 2014-04-22 Last updated: 2014-07-21Bibliographically approved

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Rohner, ChristianBjurefors, FredrikGunningberg, PerMcNamara, Liam

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