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Investigation and Comparison of State-of-the-Art Approaches in Underwater Localization

Investigation and Comparison of State-of-the-Art Approaches in Underwater Localization. Supervisor : Dr. Oleksandr Artemenko Description: Underwater Networks became very interesting for research in the last time. Tasks Literature study on robust algorithms for underwater localization

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Investigation and Comparison of State-of-the-Art Approaches in Underwater Localization

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  1. Investigation and Comparison of State-of-the-Art Approaches in Underwater Localization • Supervisor: Dr.Oleksandr Artemenko • Description: Underwater Networks became very interesting for research in the last time. • Tasks • Literature study on robust algorithms for underwater localization • Selection of two approaches for the comparison • Simulation of the selected approaches • Extension of the approaches with the improvement scheme designed by Mr.Artemenko (optional) • Simulation of the improved scheme (optional) • References [1] DibaMirza, Curt Schurgers, and Ryan Kastner. 2012. Real-time collaborative tracking for underwater networked systems. In Proceedings of the Seventh ACM International Conference on Underwater Networks and Systems (WUWNet '12). ACM [2] DibaMirza , Curt Schurgers, Collaborative tracking in mobile underwater networks, Proceedings of the Fourth ACM International Workshop on UnderWater Networks, p.1-8, November 03-03, 2009, Berkeley, California [3] Artemenko, O.; Mitschele-Thiel, A.; Schorcht, G., "Improvement of localization results in wireless networks using estimation of distances between unknown nodes: Simulation and real testbed evaluation," Personal Indoor and Mobile Radio Communications (PIMRC), 2012 IEEE 23rd International Symposium on , vol., no., pp.693,697, 9-12 Sept. 2012

  2. Robust Reference Selection Algorithms for Localization in Wireless Networks • Supervisor: Dr.Oleksandr Artemenko • Description: In case of redundant reference data (anchors) available for the localization, smart selection strategy can be applied to provide more accurate localization results. The main idea of this project is to compare different approaches using measurement data collected from UAV missions. • Tasks • Literature study on approaches for anchor selection • Selection of two approaches for the implementation (optional) • References [1] Artemenko, O.; Simon, T.; Mitschele-Thiel, A.; Schulz, D.; Ta, R.S., "Comparison of Anchor Selection algorithms for improvement of position estimation during the Wi-Fi localization process in disaster scenario," Local Computer Networks (LCN), 2012 IEEE 37th Conference on , vol., no., pp.44,49, 22-25 Oct. 2012

  3. Study on routing protocols in cognitive radio ad-hoc networks (CRAHNs) • Supervisor: Mehdi Harounabadi • Description: Routing in CRAHNs is usually a cross layer approach which can improve the routing performance providing spectrum information on the higher layers • Tasks • Literature study on routing protocols in wireless ad-hoc networks • Study on the existing routing protocols in cognitive radio ad-hoc networks • Finding the differences between routing in wireless ad-hoc networks and CRAHNs • Study on new trends of routing in CRAHNs • Preparing a survey paper (optional) • References • IEEE digital library

  4. Model Traffic and Networks for Next Generation Applications • (math intensive) • Show futurestrategiesto route flowsthrough a network (accordingtopaper)

  5. Automatically Switched Optical Networks • Research on features, challengesand open problemsof ASONs

  6. ResourceAllocation in Optical Transfer Networks • Find out howresources (wavelengthfor WDM) aremappedtoconnectionstoday • Show in whichway MPLS/MPλS works Router Router λ 1 λ2 λ3 λ4

  7. Investigation of Possibilities to Model Flow Setup Times in OpenFlow Enabled Networks • Model • Traffic andflowsetupcosts • Synchronisation costs • Switch reassignmentcosts

  8. Distributed Determination ofEquilibria in Non-cooperative Games • Non-cooperativegame: severalentitiescompete on resources • Agentswouldliketohaveasmuchresourcesaspossible (increasetheirutilityfunction) • Only limited scopeofnetworkisknown • Maximiseutilityofeachagent

  9. Investigation of Methods for Distributed Geographical Data Management • Find nodethatcontainsdataofcertaingeographicalareaaccordingtoprovidedcoordinates

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