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D2FL: design and Implementation of Distributed Dynamic Fault Localization
Shanghai Key Laboratory of Scalable Computing and Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University.ORCID iD: 0000-0002-6698-1046
School of Software, Shanghai Jiao Tong University, Shanghai Key Laboratory of Scalable Computing and Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University.
Shanghai Key Laboratory of Scalable Computing and Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-1902-9877
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Number of Authors: 52018 (English)In: IEEE Transactions on Dependable and Secure Computing, ISSN 1545-5971, E-ISSN 1941-0018, Vol. 15, no 3, p. 378-392Article in journal (Refereed) Published
Abstract [en]

Compromised or misconfigured routers have been a major concern in large-scale networks. Such routers sabotage packet delivery, and thus hurt network performance. Data-plane fault localization (FL) promises to solve this problem. Regrettably, the path-based FL fails to support dynamic routing, and the neighbor-based FL requires a centralized trusted administrative controller (AC) or global clock synchronization in each router and introduces storage overhead for caching packets. To address these problems, we introduce a dynamic distributed and low-cost model, D2FL. Using random 2-hop neighborhood authentication, D2FL supports volatile path without the AC or global clock synchronization. Besides, D2FL requires only constant tens of KB for caching which is independent of the packet transmission rate. This is much less than the cache size of DynaFL or DFL which consumes several MB. The simulations show that D2FL achieves low false positive and false negative rate with no more than 3% bandwidth overhead. We also implement an open source prototype and evaluate its effect. The result shows that the performance burden in user space is less than 10% with the dynamic sampling algorithm. 

Place, publisher, year, edition, pages
IEEE, 2018. Vol. 15, no 3, p. 378-392
National Category
Media and Communication Technology
Research subject
Pervasive Mobile Computing
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URN: urn:nbn:se:ltu:diva-13619DOI: 10.1109/TDSC.2016.2599881ISI: 000432024700002Scopus ID: 2-s2.0-85047228823Local ID: cddaf122-2392-4369-b20c-a7c5f34e3189OAI: oai:DiVA.org:ltu-13619DiVA, id: diva2:986572
Note

Validerad;2018;Nivå 2;2018-05-31 (andbra)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-08-16Bibliographically approved

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Zhou, FanfuVasilakos, Athanasios

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