Efficient Multisource Broadcast in Wireless Networks

Vocabulary
Terms used in this paper
Unit disk graph
the intersection graph of a family of unit disks in the Euclidean plane.
Competitive ratio
Worst time competitive ratio
Single-source broadcast schedule
Multisource Broadcast Schedule
Multisource broadcast schedule family
Minimum-latency multi-source broadcast
Aggregate
Shared backbone
primary nodes
Algorithm 1
Tertiary nodes
Problem
The problem presented in the paper
How to propagate information efficiently?
When message sources vary
From time to time
Solution
How did the paper approach the problem
Solution phases
Distributed Multisource Broadcast
Algorithm 2
Algorithm 3
Algorithm 4
Distributed 2-Seperated Multi-Source
Broadcast
Algorithm 7
Algorithm 8
questions
My questions on the paper
How to store vary message source
?Indexed in the backbone
How much memory rebuilding the backbone
costs?
?If this memory overheads is bigger than that of without backbone
What is \ operation among sets?
How the arbitrary numbers are determined?
How to merge messages into a packet?
?Method
?Complexity
What is the worse case upperbound?
?Infinity upperbound
critics
Some flaws might be in the paper
Latency defintion
? N1-N0=Latency
? Average case
Algorithm descriptive
Not very detailed/ overviewed.
Verbose introductory statements.
Precondition needs some other algorithms as well.
Message merging coupling issue
? Backbone is highly depending on each packet merging to be
successful
extension
Ideas for future works
Leadership for backbone
Base station voting?
Backbone building optimization
Building Fastest Broadcast Trees in Periodically-Varying Graphs
Optimization based message input size(average?)
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This paper delves into the challenges of propagating information efficiently in wireless networks with varying message sources. It introduces concepts like unit disk graphs, competitive ratio, and minimum-latency multi-source broadcast to address the problem. The solution involves a multi-phase approach to optimize the broadcast schedules while considering factors like shared backbones and primary nodes. Key visuals and algorithmic representations aid in understanding the proposed solutions for achieving efficient information propagation in dynamic network environments.

  • Wireless Networks
  • Broadcast Efficiency
  • Information Propagation
  • Network Optimization
  • Multi-source

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  1. Multisource Broadcast in Wireless Networks Zijing Zhang

  2. Vocabulary Terms used in this paper

  3. Unit disk graph the intersection graph of a family of unit disks in the Euclidean plane.

  4. Competitive ratio

  5. Worst time competitive ratio

  6. Single-source broadcast schedule

  7. Multisource Broadcast Schedule

  8. Multisource broadcast schedule family

  9. Minimum-latency multi-source broadcast

  10. Aggregate

  11. Shared backbone

  12. primary nodes

  13. Algorithm 1

  14. Tertiary nodes

  15. Problem The problem presented in the paper

  16. How to propagate information efficiently? When message sources vary From time to time

  17. Solution How did the paper approach the problem

  18. Solution phases

  19. Distributed Multisource Broadcast

  20. Algorithm 2

  21. Algorithm 3

  22. Algorithm 4

  23. Distributed 2-Seperated Multi-Source Broadcast

  24. Algorithm 7

  25. Algorithm 8

  26. questions My questions on the paper

  27. How to store vary message source ?Indexed in the backbone

  28. How much memory rebuilding the backbone costs? ?If this memory overheads is bigger than that of without backbone

  29. What is \ operation among sets?

  30. How the arbitrary numbers are determined?

  31. How to merge messages into a packet? ?Method ?Complexity

  32. What is the worse case upperbound? ?Infinity upperbound

  33. critics Some flaws might be in the paper

  34. Latency defintion ? N1-N0=Latency ? Average case

  35. Algorithm descriptive Not very detailed/ overviewed. Verbose introductory statements. Precondition needs some other algorithms as well.

  36. Message merging coupling issue ? Backbone is highly depending on each packet merging to be successful

  37. extension Ideas for future works

  38. Leadership for backbone Base station voting?

  39. Backbone building optimization Building Fastest Broadcast Trees in Periodically-Varying Graphs Optimization based message input size(average?)

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