mingyuan yan shouling ji and zhipeng cai presented by mingyuan yan
Download
Skip this Video
Download Presentation
Time efficient Data aggregation scheduling in cognitive radio networks

Loading in 2 Seconds...

play fullscreen
1 / 22

Time efficient Data aggregation scheduling in cognitive radio networks - PowerPoint PPT Presentation


  • 154 Views
  • Uploaded on

Mingyuan Yan, Shouling Ji , and Zhipeng Cai Presented by: Mingyuan Yan. Time efficient Data aggregation scheduling in cognitive radio networks. Outline. Introduction System model and problem formulation Scheduling under the UDG/ PHIM model Experimental Results

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Time efficient Data aggregation scheduling in cognitive radio networks' - anoush


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
outline
Outline
  • Introduction
  • System model and problem formulation
  • Scheduling under the UDG/ PHIM model
  • Experimental Results
  • Conclusion & future work
motivation
Motivation
  • CRNs
    • a promising solution to alleviate the spectrum shortage and under-utilization problem
    • Unicast, broadcast, multicast have been investigated, no data aggregation
    • Data aggregation
    • An effective strategy for saving energy and reducing medium access contention
    • Widely investigated in wireless networks
    • Has a broad potential in CRNs
    • Existing works can not be intuitively applied to CRNs
      • Links are not symmetric
      • Interference is more complicated
contributions
Contributions
  • Data aggregation scheduling in CRNs with minimum delay
    • Formalize the problem
    • Scheduling under UDG interference model
    • Scheduling under PHIM interference model
    • Performance evaluation based on simulations
network model
Network model
  • Primary network
    • N randomly deployed Pus, P1 , P2 , ..., PN
    • K orthogonal parallel licensed spectrums –{C1, C2, …, CK}
    • Transmission radius R
    • Interference radius RI
    • PU is either active or inactive in a time slot
      • test
network model1
Network model
  • Secondary network
    • Dense with n randomly deployed Pus, S1 , S2 , ..., SN
    • Base station Sb
    • Each SU is equipped with a single, half-duplex cognitive radio
    • Transmission radius r
    • Interference radius rI
    • Channel accessing probability
      • test
definitions
Definitions
  • Logical link
  • SU-PU collision
  • SU-SU collision
problem formalization
Problem formalization
  • Minimum Latency Data Aggregation Scheduling (MLDAS)
udg phim model
UDG/PHIM Model
  • UDG Interference Model
    • Under this model, the interference range and transmission range of wireless devices are denoted by equally likely disks. That is, R = RI and r = rI .
  • Physical Interference Model (PhIM) with Signal to Interference Ratio (SIR)
conclusion future work1
Conclusion & Future Work
  • Conclusion
    • we investigate the minimum latency data aggregation problem in CRNs
    • Two distributed algorithms under the Unit Disk Graph interference model and the Physical Interference Model are proposed, respectively
  • Future work
    • solution with theoretical performance guarantee
    • improving the performance of data gathering in conventional wireless networks with cognitive radio capability
ad