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Distributed Wireless Ad Hoc Grids With Bandwidth Control For Collaborative Node Localisation Elisa Rondini University College London, London, UK (e.rondini@cs.ucl.ac.uk) Stephen Hailes University College London, London, UK (s.hailes@cs.ucl.ac.uk) Li Li Communications Research Centre, Canada (li.li@crc.ca)
Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Tactical WSNs Military Scenario ,[object Object],[object Object],[object Object],[object Object],* L. Li and T. Kunz, “Cooperative Node Localization for Tactical Wireless Sensor Networks”, in Proceedings of the IEEE/Boeing MILCOM, October 2007. * L. Li and T. Kunz, “Cooperative Node Localization Using Non-Linear Data Projection”, in ACM Transactions on Sensor Networks, 2008.
Motivations ,[object Object],[object Object]
Contributions ,[object Object],[object Object]
Distributed Wireless Ad hoc Grid DWAG Paradigm
DWAG Applicability Steps ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CCA-MAP Localisation Algorithm Task 2 : GA computes its “ local map ” with  CCA . GA chooses among its neighbours the one that shares the greatest number of neighbours with itself, request and obtains its local map. Deliverable : GA has two maps to be patched together . Task 4 : TE performs the SVD transformation. Deliverable :  TE outputs three matrices back to GA. Task 3 : GA patches a “ global map ” by merging neighbouring map with its own local one. Deliverable :  GA outputs a “global map” . Grid Activator: Task Executor: Task 1 : GA broadcasts a message to discover its neighbours and collect their adjacency matrices.  Deliverable :  GA establishes its own neighbourhood.
Existing Work Assumptions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Previous CCA-MAP evaluations used  centralised simulations  (i.e. Matlab V7.2 – 1.60GHz Pentium M – 1GB RAM) and  perfect radio communication .
The Bandwidth Problem ,[object Object],[object Object],[object Object]
Load Distribution Algorithm ,[object Object],* E. Rondini, S. Hailes and L. Li, “Load Sharing and Bandwidth Control in Mobile 2P2 Wireless Sensor Networks”, in Proceedings of the 5 th  IEEE MP2P08 in conjunction with PerCom, March 2008. GA broadcasts a Task request message (with CPU and Bandwidth details). TE i  sends a Bid (with CPU and Bandwidth availability details). The Winner is...  TE2!!! GA selects the Best Available Node (through BATS scheme). GA uploads the Task Result back. GA offloads the Task to the Auction Winner.
Bandwidth-Aware Task Scheduling BATS Strategy S(i)  =  w C  *  C(i)  +  w B  *  B(i) S max   = max{ S(i) } i=1,...,N ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Best Candidate TE ,[object Object],[object Object],C(i )  = difference between the maximum number of processes executable on each TE and the ones actively running on it at the request time. B(i)   = percentage of TE local bandwidth availability calculated by maintaining the historical information of the last 100 temporal time slots in which the radio channel was clear or busy (reading CCA value from CC2420). The percentage was calculated by dividing the “m” number of times in which the channel was clear by 100.
Experimental Set-Up ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Experimental Set-Up (II) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Performance Results – 1 st  Set
Performance Results – 2 st  Set
Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Thank you! ... questions?

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Milcom 2008 - Elisa Rondini

  • 1. Distributed Wireless Ad Hoc Grids With Bandwidth Control For Collaborative Node Localisation Elisa Rondini University College London, London, UK (e.rondini@cs.ucl.ac.uk) Stephen Hailes University College London, London, UK (s.hailes@cs.ucl.ac.uk) Li Li Communications Research Centre, Canada (li.li@crc.ca)
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  • 6. Distributed Wireless Ad hoc Grid DWAG Paradigm
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  • 8. CCA-MAP Localisation Algorithm Task 2 : GA computes its “ local map ” with CCA . GA chooses among its neighbours the one that shares the greatest number of neighbours with itself, request and obtains its local map. Deliverable : GA has two maps to be patched together . Task 4 : TE performs the SVD transformation. Deliverable : TE outputs three matrices back to GA. Task 3 : GA patches a “ global map ” by merging neighbouring map with its own local one. Deliverable : GA outputs a “global map” . Grid Activator: Task Executor: Task 1 : GA broadcasts a message to discover its neighbours and collect their adjacency matrices. Deliverable : GA establishes its own neighbourhood.
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  • 18. Thank you! ... questions?

Notas del editor

  1. Presentation Title June 6, 2009 Speaker Name