TY - JOUR
T1 - AMUSE
T2 - Empowering Users for Cost-Aware Offloading with Throughput-Delay Tradeoffs
AU - Im, Youngbin
AU - Joe-Wong, Carlee
AU - Ha, Sangtae
AU - Sen, Soumya
AU - Kwon, Ted Taekyoung
AU - Chiang, Mung
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/5/1
Y1 - 2016/5/1
N2 - To cope with recent exponential increases in demand for mobile data, wireless Internet service providers (ISPs) are increasingly changing their pricing plans and deploying Wi-Fi hotspots to offload their mobile traffic. However, these ISP-centric approaches for traffic management do not always match the interests of mobile users. Users face a complex, multi-dimensional tradeoff between cost, throughput, and delay in making their offloading decisions: while they may save money and receive a higher throughput by waiting for Wi-Fi access, they may not wait for Wi-Fi if they are sensitive to delay. To navigate this tradeoff, we develop Adaptive bandwidth Management through USer-Empowerment (AMUSE), a functional prototype of a practical, cost-aware Wi-Fi offloading system that takes into account a user's throughput-delay tradeoffs and cellular budget constraint. Based on predicted future usage and Wi-Fi availability, AMUSE decides which applications to offload to what times of the day. Since nearly all traffic flows from mobile devices are TCP flows, we introduce a new receiver-side bandwidth allocation mechanism to practically enforce the assigned rate of each TCP application. Thus, AMUSE users can optimize their bandwidth rates according to their own cost-throughput-delay tradeoff without relying on support from different apps' content servers. Through a measurement study of 20 smartphone users' traffic usage traces, we observe that though users already offload a large amount of some application types, our framework can offload a significant additional portion of users' cellular traffic. We implement AMUSE on Windows 7 tablets and evaluate its effectiveness with 3G and Wi-Fi usage data obtained from a trial with 37 mobile users. Our results show that AMUSE improves user utility; when compared with AMUSE, other offloading algorithms yield 14 and 27 percent lower user utilities for light and heavy users, respectively. Intelligently managing users' competing interests for cost, throughput, and delay can therefore improve their offloading decisions.
AB - To cope with recent exponential increases in demand for mobile data, wireless Internet service providers (ISPs) are increasingly changing their pricing plans and deploying Wi-Fi hotspots to offload their mobile traffic. However, these ISP-centric approaches for traffic management do not always match the interests of mobile users. Users face a complex, multi-dimensional tradeoff between cost, throughput, and delay in making their offloading decisions: while they may save money and receive a higher throughput by waiting for Wi-Fi access, they may not wait for Wi-Fi if they are sensitive to delay. To navigate this tradeoff, we develop Adaptive bandwidth Management through USer-Empowerment (AMUSE), a functional prototype of a practical, cost-aware Wi-Fi offloading system that takes into account a user's throughput-delay tradeoffs and cellular budget constraint. Based on predicted future usage and Wi-Fi availability, AMUSE decides which applications to offload to what times of the day. Since nearly all traffic flows from mobile devices are TCP flows, we introduce a new receiver-side bandwidth allocation mechanism to practically enforce the assigned rate of each TCP application. Thus, AMUSE users can optimize their bandwidth rates according to their own cost-throughput-delay tradeoff without relying on support from different apps' content servers. Through a measurement study of 20 smartphone users' traffic usage traces, we observe that though users already offload a large amount of some application types, our framework can offload a significant additional portion of users' cellular traffic. We implement AMUSE on Windows 7 tablets and evaluate its effectiveness with 3G and Wi-Fi usage data obtained from a trial with 37 mobile users. Our results show that AMUSE improves user utility; when compared with AMUSE, other offloading algorithms yield 14 and 27 percent lower user utilities for light and heavy users, respectively. Intelligently managing users' competing interests for cost, throughput, and delay can therefore improve their offloading decisions.
KW - Bandwidth management
KW - Wi-Fi offloading
KW - mobile data
UR - http://www.scopus.com/inward/record.url?scp=84963799896&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84963799896&partnerID=8YFLogxK
U2 - 10.1109/TMC.2015.2456881
DO - 10.1109/TMC.2015.2456881
M3 - Article
AN - SCOPUS:84963799896
SN - 1536-1233
VL - 15
SP - 1062
EP - 1076
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 5
M1 - 7159083
ER -