minimum-latency broadcast scheduling for cognitive radio networks
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Minimum-Latency Broadcast Scheduling for Cognitive Radio Networks. Shouling Ji and Raheem Beyah CAP group, School of Electrical and Computer Engineering Georgia Institute of Technology Zhipeng Cai Department of Computer Science Georgia State University. OUTLINE. 1. Introduction. - PowerPoint PPT PresentationTRANSCRIPT
Minimum-Latency Broadcast Scheduling for Cognitive Radio Networks
Shouling Ji and Raheem BeyahCAP group, School of Electrical and Computer Engineering
Georgia Institute of Technology
Zhipeng Cai Department of Computer Science
Georgia State University
OUTLINE
4
Introduction1
2
3
5
Broadcasting Tree and Coloring
System Model and Problem Definition
Broadcast Scheduling
Simulation
6 Conclusion and Future Work
3
Introduction
4
Cognitive Radio Networks (CRNs)
Cognitive Radio Networks (CRNs) The utilization of spectrum assigned
to licensed users varies from 15% to 85% temporally and geographically (FCC report)
Unlicensed users (Secondary Users, SUs) can sense and learn the communication environment, and opportunistically access the spectrum without causing any unacceptable interference to licensed users (Primary Users, PUs)
5
Broadcast Scheduling in CRNs
Task and goal Broadcast a data packet from the source to all the other nodes
Minimum-latency and minimum-redundancy
Motivation NP-hard even in traditional wireless networks under the simple UDG model
It is not straightforward to move traditional broadcast algorithms to CRNs
Existing solutions are either heuristic solutions without performance guarantee or with performance far from the optimal solution
Our contributions A Mixed Broadcast Scheduling (MBS) algorithm for CRNs under both the Unit Disk Graph
(UDG) model and the Protocol Interference Model (PrIM)
Comprehensive latency and redundancy analysis
Broadcast Scheduling in CRNs
6
System Model and Problem Definition
7
Primary Network N Primary Users (PUs):
Transmission/interference radius:
Network time is slotted:
Primary transmitters are Poisson distributed with density
Secondary Network A source and n randomly distributed Secondary Users (SUs)
Transmission/interference radius:
Topology graph:
Network Model
8
Interference Model Unit Disk Graph (Model):
Protocol Interference Model (PrIM):
Problem definition To seek a broadcast scheduling strategy of minimum latency
Low broadcast redundancy the maximum possible transmission times of the broadcast packet by a SU during the scheduling
Interference Model and Problem Definition
9
Broadcasting Tree and Coloring
10
Connected Dominating Set (CDS) Dominators (black), Connectors (blue), and Dominatees (white)
CDS-based broadcasting tree
CDS-based Broadcasting Tree
11
Tesselation A tessellation of a plane is to cover
this plane with a pattern of flat shapes so that there are no overlaps or gaps
A regular tessellation is a pattern made by repeating a regular polygon, e.g. hexagon
Tessellation and Coloring
12
Broadcast Scheduling
13
MBS-UDG: Idea Phase I: broadcast to all the
dominators by Unicast
Phase II: broadcast to all the dominatees
by mixed Unicast and Broadcast
Depending on how many dominatee children are waiting for receiving the broadcast packet
Broadcast Scheduling under UDG
14
Latency and redundancy performance analysis The expected time consumption of MBS-UDG is upper bounded by
and
(Theorem 3).
The broadcast redundancy of MBS-UDG is at most
and
(Theorem 4).
Broadcast Scheduling under UDG
15
MBS-PrIM No significant difference with MBS-UDG
Performance analysis Let . The expected number of time slots consumed by MBS-PrIM is
upper bounded by if
and
if (Theorem 7).
The broadcast redundancy of MBS-PrIM is upper bounded by if
, and if
(Theorem 8).
Broadcast Scheduling under PrIM
16
Simulation
17
Latency performance
Simulation Results and Analysis
18
Redundancy performance
Simulation Results and Analysis
19
A Mixed Broadcast Scheduling (MBS) algorithm is proposed
Comprehensive latency and redundancy performance analysis
Simulations are conducted
Future Research Directions Considering more accurate dynamic spectrum model and access model
Distributed broadcasting algorithm with performance guarantee
Conclusion and Future Work
THANK YOU!
Minimum-Latency Broadcast Scheduling for Cognitive Radio Networks
Shouling Ji and Raheem BeyahCAP Group, Georgia Institute of Technology
[email protected]://www.ece.gatech.edu/cap/
Zhipeng CaiGeorgia State University