title: Avoiding Biased-Feeding in the Scheduling of Collaborative Multipath TCP.
abstract: Smartphones have become the major communication and portable computing devices that access the Internet through Wi-Fi or mobile networks. Unfortunately, users without a mobile data subscription can only access the Internet at limited locations, such as hotspots. In this paper, we propose a collaborative bandwidth sharing protocol (CBSP) built on top of MultiPath TCP (MPTCP). CBSP enables users to buy bandwidth on demand from neighbors (called Helpers) and uses virtual interfaces to bind the subflows of MPTCP to avoid modifying the implementation of MPTCP. However, although MPTCP provides the required multi-homing functionality for bandwidth sharing, the current packet scheduling in collaborative MPTCP (e.g., Co-MPTCP) leads to the so-called biased-feeding problem. In this problem, the fastest link might always be selected to send packets whenever it has available cwnd, which results in other links not being fully utilized. In this work, we set out to design an algorithm, called Scheduled Window-based Transmission Control (SWTC), to improve the performance of packet scheduling in MPTCP, and we perform extensive simulations to evaluate its performance.
authors.affiliation: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan.
authors.forename: Meng-Hsun
authors.initials: MH
authors.lastname: Tsai
authors.affiliation: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan.
authors.forename: Chien-Ming
authors.initials: CM
authors.lastname: Chou
authors.affiliation: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan.
authors.forename: Kun-Chan
authors.initials: KC
authors.lastname: Lan
mesh_terms: D003195:Computer Communication Networks / Q000706:statistics & numerical data*; D020407:Internet / Q000191:economics / Q000706:statistics & numerical data*; D059015:Wireless Technology / Q000191:economics / Q000706:statistics & numerical data