A Cooperative MAC Protocol for Wireless LAN
Pei Liu, Zhifeng Tao, Shivendra S. Panwar
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Motivation: In the legacy 802.11 system, source station transmits to the receiver directly and transmissions
received by other stations will be discarded. However, we can achieve better performance if user cooperation
is allowed.
Protocol illustration:
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–
–
–
Neighboring nodes detection
Chosen of the helper
Channel reservation
Data frame and acknowledgement
Th
2 HTS
1 RTS
3 CTS
Ts
3 CTS
Td
1 RTS
T1
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Protocol Validation:
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–
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Analytical model
Software simulation
Higher throughput and lower delay
T2
Performance Evaluation of IEEE
802.11e
Jeffrey (Zhifeng) Tao, Shivendra S. Panwar
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Protocol objective: Provide QoS support to upper layer applications (e.g., VoIPoWLAN, video streaming)
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Protocol illustration:
Contention window from [1, 1+2mCWMin[Priority Class]]
Low Priority
AIFS[ Low Priority ]
AIFS[ Medium Priority ]
Channel Busy
SIFS
Random backoff
Medium Priority
High Priority
Next Frame
Contention Window
PIFS
Slot Time
Randomly choose a backoff window
size and decrement backoff counter
as long as the medium stays idle
Defer Access
AIFS[ High Priority]
= DIFS
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Analytical model:
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Embedded Markov chain
Compute saturation throughput and service delay distribution
Capable of capturing all major QoS-specific features for the EDCF mode
* Reference: Z. Tao, S.S.Panwar, “An Analytical Model for the IEEE 802.11e Enhanced Distributed Coordination Function”, ICC 2004
Cooperation Medium Access Control
Pei Liu, Jeffrey (Zhifeng) Tao, Shivendra S. Panwar
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•
Objective: Design new medium access control protocol to exploit the novel idea of “user
cooperative”.
Protocol features:
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Backward compatible
Improve the throughput and delay performance of the legacy 802.11 network
Helper
Data
Source
Data
Data
Destination
* Reference: P. Liu, Z. Tao, S.S.Panwar, “A Cooperative MAC Protocol for Wireless Local Area Networks,” submitted to ICC 2005
A P2P Video Streaming System with Multiple
Description Coding
Yanming Shen, Shivendra S. Panwar, Keith W. Ross, Yao Wang
• Motivation: Provide On-Demand video streaming service in a Peer-to-Peer network
• System architecture::
2
2
3
4
Cloud
1
Server &
Client
Server
6
5
• System design:
Client
– Multiple description video coding
– Sub-stream placement
– Admission control, server selection, sub-stream delivery
A Mobile Ad Hoc Bio-Sensor Network
Y. Li, S. Panwar, S. Burugupalli
• Achievements by Dr. John Chapin and his group at SUNY Downstate Medical
Center.
– Stimulate multiple brain regions of rats to produce stimulus cues for various
commanded movements and rewards to reinforce their movements.
– Use wireless communication to deliver brain stimulation.
• Remotely guided animals are ideal for search and rescue operations.
– Natural disaster recovery
– Homeland security
– Military operations
• System architecture
– Ad hoc network infrastructure
– Control center
– Mobile bio-sensor nodes: seeker, follower, relay
• Technical issues for wireless networking
– Routing
– Transport protocol
– Backpack prototype development
Scheduling in High Speed Packet Switches
Y. Li, Y. Shen, S. Panwar and H. J. Chao
• Fixed length Virtual Output Queueing (VOQ) switches
• Matching algorithms for scheduling in VOQ switches
– Maximum Weighted Matching: stable, O(N3)
– Maximal Matching: stable with speedup of 2
– Algorithms with memory: stable, with lower complexity, without
speedup
– Exhaustive Service Matching with Hamiltonian Walk (HE-iSLIP,
HEDRRM)
• Stable under any admissible traffic
• Low implementation complexity, O(logN)
• Packet delay: much lower than other O(logN) algorithms, comparable to higher
complexity algorithms.
• Load-balanced switch
- No scheduler, 100% throughput
- Packet delay: re-assembly delay + re-sequencing delay
Scheduling in High Speed Packet Switches
Y. Li, S. Panwar and H. J. Chao
• Fixed length Virtual Output Queueing (VOQ) switches
• Matching algorithms for scheduling in VOQ switches
– Maximum Weighted Matching: stable, O(N3)
– Maximal Matching: stable with speedup of 2
– Algorithms with memory: stable, with lower complexity, without
speedup
• Polling system based matching
– Exhaustive Service Matching with Hamiltonian Walk (HE-iSLIP,
HEDRRM)
• Stable under any admissible traffic
• Low implementation complexity, O(logN)
• Packet delay: much lower than other O(logN) algorithms, comparable to
higher complexith algorithms.
– Limited Service Matching (L-iSLIP, LDRRM)