select: self-learning collision avoidance for wireless networks chun-cheng chen, eunsoo, seo,...
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SELECT: Self-Learning Collision Avoidance for Wireless Networks
Chun-Cheng Chen, Eunsoo, Seo,Hwangnam Kim, and Haiyun Luo
Department of Computer Science,University of Illinois, Urbana-Champaign
IEEE Transactions on Mobile Computing,Vol. 7, No.3, 2008
Outline
Introduction Hidden/exposed terminal problem
in 802.11 networks Motivation SELECT
a self-learning collision avoidance mechanism
Performance evaluation Conclusion
Introduction
Limited number of orthogonal channels restricts the deployment of 802.11 APs.– 3 channels for 802.11b/g, 12 for
802.11a– Interference range is long compared
with communication range
Introduction
Recent published data shows 40% of 802.11 APs are operating on channel 6
In Boston, a max number of 85 APs are detected in the interference range– At least 30 APs are directly
interfering with each other
Hidden/exposed terminal problem
Restrain by RTS
Restrain by CTS
Restrain by B’s CTS,Cannot reply E’s RTS
C’s RTS collidewith A->B
Drawbacks of hidden/ exposed receiver problem1. Sender drops the head-of-line data
packet– Resulting in a contention-induced
packet loss
2. Unsuccessful RTS transmission, misled the sender to conclude– Receiver is unavailable
(false link breakage is triggered)– Channel quality at the receiver side is
low (Using low data transfer rate)
Drawbacks of hidden/ exposed receiver problem3. Unsuccessful RTS attempts
inflate sender’s contention window
4. Repeated RTS attempts prevent the sender’s neighbor from transmitting– Low channel utilization
5. Hidden/exposed terminal problem will persists until the clients move and contention relation changes
Motivation
Use MICA2 CC1000 to simulate the operation of 802.11 devices
Exposedreceiver
Potentialsender
RSS vs. SR (successful ratio) C→D, G →H are active E →F serves as an additional
interference A →B, A records the RTS
successful ratio
Summary of RSS vs. RS
The RSS at the sender and the receiver has strong correlation
To estimate the RSS at the receiver from the sender is complex
The sender can use its RSS as an indicator of the status at receiver
Overview of SELECT
Sender uses the detected RSS to map the receiver’s condition (successful ratio)
RSS is divided into several intervals, each interval has a corresponding SR
RSS ≧ CSthred → channel busy SR ≧ threshold → transmit the data SR < threshold → pretend the
transmission is failed
SELECT: self-learning collision avoidance RSS-SR mapping maintenance RSS-SR mapping lookup Integration with 802.11 DCF Intelligent SR threshold setup
RSS-SR mapping maintenance To update the SR within an interval
Twin Using a variable α (from 0 to 1) to
indicate the weight of old data– α~1: the stored data is very new– α~0: the stored data is almost useless
Current time
Last update time
RSS-SR mapping lookup When a sender wants to send
data to a receiver, the sender lookup the corresponding SR under current RSS– Remove out-of-date data first
Integration with 802.11 DCF
When MAC module access the channel and the result is determined– Udp_RSS_SR
RSS_SR_Look-UP
Integration with 802.11 DCF: when backoff expired
RSS ≧ CSthred → channel busy– Performs random backoff
RSS < CSthred → channel idle– SR ≧ threshold → transmit the data– SR < threshold → pretend the
transmission is failed, also performs random Backoff
Intelligent SR threshold setup (1) The authors assume the
successful ratio (SR) of each RSS is distributed according to the measured RSS distribution
When can a station measure RSS?– During random backoff
Intelligent SR threshold setup (2)
Crssi = number of measured signal strength falls within interval RSSi
T=update interval Trssi= the time that channel
quality falls within interval RSSi
Intelligent SR threshold setup (3) If SRi < threshold, station won’t
transmit during period T The lose of throughput
– △rssj= time spend to transmit a packet within interval RSSj interval
Intelligent SR threshold setup (4) Try to maximize the expected
throughput Total spend time
Time saved by a node at the low-SR
rssi
Available throughput
Simulation setup
Ns-2 2.28 Two-Ray Ground model Communication range: 115m RSSmin=-100dBm RSS validation windows= 2
second CBR/UDP traffic
Conclusion
The paper proposes SELECT– An effective and efficient self-
learning collision mechanism SELECT improves throughput by
up to 140 % and the successful ratio by 302 percent