TY - GEN
T1 - Inferring loss causes to improve link rate adaptation in wireless networks
AU - Kulkarni, Parag
AU - Motz, Benjamin
AU - Lewis, Tim
AU - Quadri, Sadia
PY - 2011
Y1 - 2011
N2 - Most of the link rate adaptation algorithms reduce transmission rate on a failed transmission assuming the cause of the loss to be due to radio channel impairment. However, if this failure is due to collision, then lowering the transmission rate in response is unnecessary. This paper proposes a solution to address this problem by augmenting the rate adaptation algorithm with a loss classification component. The main idea underlying this approach is to determine if channel condition is improving or deteriorating by identifying trends in the signal strength. On encountering frame loss, the estimated value of signal strength is used to infer the cause of loss. If estimation indicates a deteriorating channel condition, then the loss is classified as a likely 'channel loss'. Otherwise, the loss is classified as a likely 'non-channel loss'. Thus, in the former case, the rate adaptation algorithm lowers the transmission rate whereas in the latter case, it continues using existing transmission rate. Simulation based evaluation reveals that the use of such a simple heuristic significantly improves performance compared to the case of not using any loss classification mechanism. This was further confirmed by measurements conducted in an experimental test-bed.
AB - Most of the link rate adaptation algorithms reduce transmission rate on a failed transmission assuming the cause of the loss to be due to radio channel impairment. However, if this failure is due to collision, then lowering the transmission rate in response is unnecessary. This paper proposes a solution to address this problem by augmenting the rate adaptation algorithm with a loss classification component. The main idea underlying this approach is to determine if channel condition is improving or deteriorating by identifying trends in the signal strength. On encountering frame loss, the estimated value of signal strength is used to infer the cause of loss. If estimation indicates a deteriorating channel condition, then the loss is classified as a likely 'channel loss'. Otherwise, the loss is classified as a likely 'non-channel loss'. Thus, in the former case, the rate adaptation algorithm lowers the transmission rate whereas in the latter case, it continues using existing transmission rate. Simulation based evaluation reveals that the use of such a simple heuristic significantly improves performance compared to the case of not using any loss classification mechanism. This was further confirmed by measurements conducted in an experimental test-bed.
KW - Link rate adaptation
KW - Loss classification
UR - http://www.scopus.com/inward/record.url?scp=79957703276&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79957703276&partnerID=8YFLogxK
U2 - 10.1109/AINA.2011.79
DO - 10.1109/AINA.2011.79
M3 - Conference contribution
AN - SCOPUS:79957703276
SN - 9780769543376
T3 - Proceedings - International Conference on Advanced Information Networking and Applications, AINA
SP - 659
EP - 666
BT - Proceedings - 25th IEEE International Conference on Advanced Information Networking and Applications, AINA 2011
T2 - 25th IEEE International Conference on Advanced Information Networking and Applications, AINA 2011
Y2 - 22 March 2011 through 25 March 2011
ER -