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Node Failure Localization: Theorem Proof

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 Added by Liang Ma
 Publication date 2020
and research's language is English




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This is a technical report, containing all the theorem proofs in paper On Optimal Monitor Placement for Localizing Node Failures via Network Tomography by Liang Ma, Ting He, Ananthram Swami, Don Towsley, and Kin K. Leung, published in IFIP WG 7.3 Performance, 2015.



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This is a technical report, containing all the theorem proofs and additional evaluations in paper Network Capability in Localizing Node Failures via End-to-end Path Measurements by Liang Ma, Ting He, Ananthram Swami, Don Towsley, and Kin K. Leung, published in IEEE/ACM Transactions on Networking, vol. 25, no. 1, pp. 434-450, 2017.
This is a technical report, containing all the theorem proofs in paper Node Failure Localization in Communication Networks via Network Tomography by Liang Ma, Ting He, Ananthram Swami, Don Towsley, Kin K. Leung, and Jessica Lowe, published in ITA Annual Fall Meeting, 2014.
49 - Liang Ma , Ting He , Kin K. Leung 2020
This is a technical report, containing all the theorem proofs and additional evaluations in paper Monitor Placement for Maximal Identifiability in Network Tomography by Liang Ma, Ting He, Kin K. Leung, Ananthram Swami, Don Towsley, published in IEEE INFOCOM, 2014.
The use of aerial anchors for localizing terrestrial nodes has recently been recognized as a cost-effective, swift and flexible solution for better localization accuracy, providing localization services when the GPS is jammed or satellite reception is not possible. In this paper, the localization of terrestrial nodes when using mobile unmanned aerial vehicles (UAVs) as aerial anchors is presented. We propose a novel framework to derive localization error in urban areas. In contrast to the existing works, our framework includes height-dependent UAV to ground channel characteristics and a highly detailed UAV energy consumption model. This enables us to explore different tradeoffs and optimize UAV trajectory for minimum localization error. In particular, we investigate the impact of UAV altitude, hovering time, number of waypoints and path length through formulating an energy-constrained optimization problem. Our results show that increasing the hovering time decreases the localization error considerably at the cost of a higher energy consumption. To keep the localization error below 100m, shorter hovering is only possible when the path altitude and radius are optimized. For a constant hovering time of 5 seconds, tuning both parameters to their optimal values brings the localization error from 150m down to 65m with a power saving around 25%
We give a general method of extending unital completely positive maps to amalgamated free products of C*-algebras. As an application we give a dilation theoretic proof of Bocas Theorem.
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