LIAD: Adaptive bandwidth prediction based Logarithmic Increase Adaptive Decrease for TCP congestion control in heterogeneous wireless networks

For accessing plentiful resources in the Internet through wireless mobile hosts, diverse wireless network standards and technologies have been developed and progressed significantly. The most successful examples include IEEE 802.11 WiFi for wireless networks and 3G/HSDPA/HSUPA for cellular communications. All IP-based applications are the primary motivations to make these networks successful. In TCP/IP transmissions, the TCP congestion control operates well in the wired network, but it is difficult to determine an accurate congestion window in a heterogeneous wireless network that consists of the wired Internet and various types of wireless networks. The primary reason is that TO connections are impacted by not only networks congestion but also error wireless links. This paper thus proposes a novel adaptive window congestion control (namely Logarithmic Increase Adaptive Decrease, LIAD) for TCP connections in heterogeneous wireless networks. The proposed RTT-based LIAD has the capability to increase throughput while achieving competitive fairness among connections with the same TCP congestion mechanism and supporting friendliness among connections with different TCP congestion control mechanisms. In the Congestion Avoidance (CA) phase, an optimal shrink factor is first proposed for Adaptive Decreasing cwnd rather than a static decreasing mechanism used by most approaches. Second, we adopt a Logarithmic Increase algorithm to increase cwnd while receiving each ACK after causing three duplicate ACKs. The analyses of congestion window and throughput under different packet loss rate are analyzed. Furthermore, the state transition diagram of LIAD is detailed. Numerical results demonstrate that the proposed LIAD outperforms other approaches in goodput, fairness, and friendliness under diverse heterogeneous wireless topologies. Especially, in the case of 10% packet loss rate in wireless links, the proposed approach increases goodput up to 156% and 1136% as compared with LogWest-wood+ and NewReno, respectively. (C) 2009 Elsevier B.V. All rights reserved.