SELECT: Self-Learning Collision Avoidance for Wireless Networks

SELECT: Self-Learning Collision Avoidance for Wireless Networks Chun-Cheng Chen, Eunsoo, Seo,Hwangnam Kim, and HaiyunLuoDepartment of Computer Science, University of Illinois, Urbana-ChampaignIEEE 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 B’s CTS, Cannot reply E’s RTS C’s RTS collidewith A->B Restrain by RTS Restrain by CTS

Drawbacks of hidden/ exposed receiver problem • Sender drops the head-of-line data packet • Resulting in a contention-induced packet loss • 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 problem • Unsuccessful RTS attempts inflate sender’s contention window • Repeated RTS attempts prevent the sender’s neighbor from transmitting • Low channel utilization • Hidden/exposed terminal problem will persists until the clients move and contention relation changes

Motivation Potentialsender Exposedreceiver • Use MICA2 CC1000 to simulate the operation of 802.11 devices

RSS at motes C and D while A is transmitting to B

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

RSS vs. RTS SR at mote A

RSS vs. RTS SR over time

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 algorithm Calculate α Set updatevariable Update variable & timestamp

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

RSS-SR mapping lookup Channel Busy Return SR

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

Exposed receiver • Station 3 is an exposed receiver

Result of exposed receiver(w/o RTS/CTS) # of drop packets at Node 2 Throughput gain at Node 2

Result of exposed receiver (w/o RTS/CTS) Successful ratio at Node 2 Throughput profile

Result of exposed receiver(with RTS/CTS) # of drop packets at Node 2 Throughput gain at Node 2

Result of exposed receiver (with RTS/CTS) Successful ratio at Node 2 Throughput profile

Hidden receiver • Station 0 and 3 are hidden receivers to each other

Normalized throughputx: with △: w/o RTS/CTS • 802.11 DCF • SELECT

Normalized instantaneous throughput: 0->1

Random topology • # of drop packets • Throughput gain

Real experiment results by using MICA2 Throughput (pkt/second) RTS successful ratio

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

Thank you!!

SELECT: Self-Learning Collision Avoidance for Wireless Networks