TY - GEN
T1 - Network cooperation for client-AP association optimization
AU - Baid, Akash
AU - Schapira, Michael
AU - Seskar, Ivan
AU - Rexford, Jennifer
AU - Raychaudhuri, Dipankar
PY - 2012
Y1 - 2012
N2 - In a WiFi deployment with multiple access points, optimizing the way each client selects an AP from amongst the available choices, has a significant impact on the realized performance. When two or more such multi-AP networks are deployed in the same region, APs from different networks can cause severe interference to one another. In this paper, we study how inter-network interference effects the intra-network association optimization and propose a cooperative optimization scheme to mitigate the interference. We model the interference between multiple overlapping WiFi deployments, determine the information that networks need to share, and formulate a non-linear program that each network can solve for optimal proportional-fair association of clients to APs. Assuming a sum of log rates utility function, we apply a known 2+∈ approximation algorithm for solving the NP-hard problem in polynomial time. We evaluate the performance gain through large-scale simulations with multiple overlapping networks, each consisting of 15-35 access points and 50-250 clients in a 0.5×0.5 sq.km. urban setting. Results show an average of 150% improvement in random deployments and upto 7× improvements in clustered deployments for the least-performing client throughputs with modest reductions in the mean client throughputs.
AB - In a WiFi deployment with multiple access points, optimizing the way each client selects an AP from amongst the available choices, has a significant impact on the realized performance. When two or more such multi-AP networks are deployed in the same region, APs from different networks can cause severe interference to one another. In this paper, we study how inter-network interference effects the intra-network association optimization and propose a cooperative optimization scheme to mitigate the interference. We model the interference between multiple overlapping WiFi deployments, determine the information that networks need to share, and formulate a non-linear program that each network can solve for optimal proportional-fair association of clients to APs. Assuming a sum of log rates utility function, we apply a known 2+∈ approximation algorithm for solving the NP-hard problem in polynomial time. We evaluate the performance gain through large-scale simulations with multiple overlapping networks, each consisting of 15-35 access points and 50-250 clients in a 0.5×0.5 sq.km. urban setting. Results show an average of 150% improvement in random deployments and upto 7× improvements in clustered deployments for the least-performing client throughputs with modest reductions in the mean client throughputs.
UR - http://www.scopus.com/inward/record.url?scp=84866936375&partnerID=8YFLogxK
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AN - SCOPUS:84866936375
SN - 9783901882456
T3 - 2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2012
SP - 431
EP - 436
BT - 2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2012
T2 - 2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2012
Y2 - 14 May 2012 through 18 May 2012
ER -