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Data Network Architectures Group 2
Presentation Outline
• Background
• Wireless Networks and IEEE 802.11
• The Distributed Coordination Function
• Performance Analysis & Modeling
• Modeling the Losses Incurred by DCF
• The IEEE 802.11 Test Bed
• The Bigger Picture
• Questions
Data Network Architectures Group 3
My Background & Future
• Business Science (Computer Science) at UCT
• Currently pursuing an MSc in DNA Group
• Would like to continue to PhD in the UK
• No long-term academic path (yet)
• Plan for the future
– Embedded Systems
– Wireless Telecommunication
– Or a combination of the two!
Data Network Architectures Group 4
DNA Group Research Areas
• Group is fairly new (<2yrs) to wireless networks
• Wireless research focus currently on :
– General Mesh Networks
• 802.16 and wireless Internet delivery
– 802.11 Security
• OLSR - previous talk
– 802.11 Performance Modeling
• DCF
Data Network Architectures Group 5
Wireless Topologies
Possible Topologies
• Point-to-point (line replacements)
• Point-to-multipoint (infrastructure)
• Multipoint-to-multipoint (ad hoc)
– Mobile ad hoc networks (MANETs)
– Mesh networks
Infrastructure
Ad hoc
Data Network Architectures Group 6
IEEE 802.11 Background
• Set of standards guiding WLAN development
• Split OSI Data Link layer into MAC and LLC
• IEEE 802.11n in draft - promises 248 Mbps
– Theoretical vs. Actual rates differ
LLC Flow control & Multiplexing
MAC
MAC-level Security
Distributed
Coordination
Function
Point Coordinator
Function
Enhanced
Distributed Channel
Access
PHY802.11
IR
802.11
FHSS
802.11
DSSS
802.11a
OFDM
802.11b
HR-DSSS
802.11g
OFDM
Data Network Architectures Group 7
The Distributed Coordination Function
• Medium Access Control technique
• Ensures equal, but NOT fair, access to the channel
• A form of CSMA/CA
– CSMA/CD not possible with wireless
– Uses Exponential Binary Back-off
• Inter-frame Spaces define frame priority
• Designed for a Best-Effort service
– No service guarantee
– No QoS for multimedia
Data Network Architectures Group 8
Factors Affecting DCF
• Collisions Recovery
– Hidden Nodes
– Exposed Nodes
• RTS / CTS
– Longer Handshake
– Reduces Error
• Increased Nodes
• Increased Traffic
• Topology
Data Network Architectures Group 9
My Research Focus
• “Modeling the performance of the Distributed Coordination Function in 802.11 mesh networks”
– Performance : Degree of QoS provided
– Acknowledge that DCF is inefficient
• Thus, existence of 802.11e
– Exacerbated by mesh networks
• Number of hidden / exposed nodes
– But, by how much? And can we predict it?
– Pave the way for EDCA analysis
Data Network Architectures Group 10
What is Quality of Service?
“A set of qualities relating to the collective behaviour of one or more objects” - ITU X.605
• More specifically, for IEEE 802.11
– Throughput
– Response time
– Jitter
– Packet loss
• Increasingly NB for multimedia
• IEEE 802.11e and IEEE 802.11T (draft)
– Not widely-adopted
Data Network Architectures Group 11
Modeling Process
• Developing an analytic model is not a trivial process
• It’s NOT Simulation!
• Workloads NB
– Trace
– Synthetic
Data Network Architectures Group 12
Existing Analytic Models for DCF• Bianchi’s Model is widely-adopted
• DCF back-off modeled as Markov process
• Assumes a constant collision probability p
Stage
Back-off Counter
Data Network Architectures Group 13
Bianchi’s Model
• p is a function of the number of contending nodes
• Using the Markov model, Bianchi derives :– The probability of successfully
transmitting in a randomly chosen slot time
– And, using , derives the normalised expected throughput at a node
• Normalised Throughput
– Fraction of the base PHY rate offered
– Indicates losses due to DCF overhead
Data Network Architectures Group 14
Integration with MicroSnap
• Tool written as a DNA Project
• MicroSnap models stochastic queuing networks
• Environment Comprised of
– Service Centres
– Workloads
– Traffic Classes
– Routes (static)
• Program in MicroSnapL interface language
Data Network Architectures Group 15
Fitting Models to MicroSnap
• Convert wireless links service centers
Data Network Architectures Group 16
Workflow Diagram
CONCLUDE
DERIVE MACHINE MODEL FOR MESH DCF
GENERATE TEST CASES (WORKLOADS/METRICS)
EXPERIMENTAL(TEST BED)
COMPARE RESULTS
ANALYTIC(MICROSNAPL)
SIMULATION(OMNET++)
Data Network Architectures Group 17
The Mesh Test Bed
• The DNA Group is currently assembling an 802.11 multi-hop wireless mesh network
• The DNA Group feels that the test bed will
– Compliment research
– Strengthen results
– Provide a means to implement
and test concepts
– Attract students to the field
Data Network Architectures Group 18
Progress on the Test Bed
• Short term goal of 9 nodes (double within a year)
• Already purchased a large portion of the hardware
• Challenges
– PCI 2.1 / 2.2 Incompatibility
– Limiting Signal
• Noise Injectors
• Attenuators
– Interference
• More questions? Speak to me afterwards!
Data Network Architectures Group 19
The Bigger Picture
• DNA Group is developing a suite of tools for wireless network performance modeling
– Analytical
– Simulation
– Experimental (via test bed)
• Paolo Pileggi currently developing the framework as part of Honours project
• The work done in my research will contribute to a module within the IEEE 802.11 MAC
• More specifically, it will assist in generating the machine model for arbitrary mesh networks