Performance Enhancement of Multipath TCP for Wireless Communications with Multiple Radio Interfaces

ArticleMultipath TCP (MPTCP) allows a TCP connection to operate across multiple paths simultaneously and becomes highly attractive to support the emerging mobile devices with various radio interfaces and to improve resource utilization as well as connection robustness. The existing multipath congestion control algorithms, however, are mainly loss-based and prefer the paths with lower drop rates, leading to severe performance degradation in wireless communication systems where random packet losses occur frequently. To address this challenge, this paper proposes a new mVeno algorithm, which makes full use of the congestion information of all the subflows belonging to a TCP connection in order to adaptively adjust the transmission rate of each subflow. Specifically, mVeno modifies the additive increase phase of Veno so as to effectively couple all subflows by dynamically varying the congestion window increment based on the receiving ACKs. The weighted parameter of each subflow for tuning the congestio

A study of the effects of TCP designs on server efficiency and throughputs on wired and wireless networks.

Yeung, Fei-Fei.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 144-146).Abstracts in English and Chinese.Introduction --- p.1Chapter Part I: --- A New Socket API for Enhancing Server Efficiency --- p.5Chapter Chapter 1 --- Introduction --- p.6Chapter 1.1 --- Brief Background --- p.6Chapter 1.2 --- Deficiencies of Nagle's Algorithm and Goals and Objectives of this Research --- p.7Chapter 1.2.1 --- Effectiveness of Nagle's Algorithm --- p.7Chapter 1.2.2 --- Preventing Small Packets via Application Layer --- p.9Chapter 1.2.3 --- Minimum Delay in TCP Buffer --- p.10Chapter 1.2.4 --- Maximum Delay in TCP Buffer --- p.11Chapter 1.2.5 --- New Socket API --- p.12Chapter 1.3 --- Scope of Research and Summary of Contributions --- p.12Chapter 1.4 --- Organization of Part 1 --- p.13Chapter Chapter 2 --- Background --- p.14Chapter 2.1 --- Review of Nagle's Algorithm --- p.14Chapter 2.2 --- Additional Problems Inherent in Nagle's Algorithm --- p.17Chapter 2.3 --- Previous Proposed Modifications on Nagle's Algorithm --- p.22Chapter 2.3.1 --- The Minshall Modification --- p.22Chapter 2.3.1.1 --- The Minshall Modification --- p.22Chapter 2.3.1.2 --- The Minshall et al. Modification --- p.23Chapter 2.3.2 --- The Borman Modification --- p.23Chapter 2.3.3 --- The Jeffrey et al. Modification --- p.25Chapter 2.3.3.1 --- The EOM and MORE Variants --- p.25Chapter 2.3.3.2 --- The DLDET Variant --- p.26Chapter 2.3.4 --- Comparison Between Our Proposal and Related Works --- p.26Chapter Chapter 3 --- Min-Delay-Max-Delay TCP Buffering --- p.28Chapter 3.1 --- Minimum Delay --- p.29Chapter 3.1.1 --- Why Enabling Nagle's Algorithm Alone is Not a Solution? --- p.29Chapter 3.1.2 --- Advantages of Min-Delay TCP-layer Buffering versus Application-layer Buffering --- p.30Chapter 3.2 --- Maximum Delay --- p.32Chapter 3.2.1 --- Why Enabling Nagle's Algorithm Alone is Not a Solution? --- p.32Chapter 3.2.2 --- Advantages of Max-delay TCP Buffering versus Nagle's Algorithm --- p.33Chapter 3.3 --- Interaction with Nagle's Algorithm --- p.34Chapter 3.4 --- When to Apply Our Proposed Scheme? --- p.36Chapter 3.5 --- New Socket Option Description --- p.38Chapter 3.6 --- Implementation --- p.40Chapter 3.6.1 --- Small Packet Transmission Decision Logic --- p.42Chapter 3.6.2 --- Modified API --- p.44Chapter Chapter 4 --- Experiments --- p.46Chapter 4.1 --- The Effect of Kernel Buffering Mechanism on the Service Time --- p.47Chapter 4.1.1 --- Aims and Methodology --- p.47Chapter 4.1.2 --- Comparison of Transmission Time Required --- p.49Chapter 4.2 --- Performance of Min-Delay-Max-Delay Scheme --- p.56Chapter 4.2.1 --- Methodology --- p.56Chapter 4.2.1.1 --- Network Setup --- p.56Chapter 4.2.1.2 --- Traffic Model --- p.58Chapter 4.2.1.3 --- Delay Measurement --- p.60Chapter 4.2.2 --- Efficiency of Busy Server --- p.62Chapter 4.2.2.1 --- Performance of Nagle's algorithm --- p.62Chapter 4.2.2.2 --- Performance of Min-Delay TCP Buffering Scheme --- p.67Chapter 4.2.3 --- Limiting Delay by Setting TCP´ؤMAXDELAY --- p.70Chapter 4.3 --- Performance Sensitivity Discussion --- p.77Chapter 4.3.1 --- Sensitivity to Data Size per Invocation of send() --- p.77Chapter 4.3.2 --- Sensitivity to Minimum Delay --- p.83Chapter 4.3.3 --- Sensitivity to Round Trip Time --- p.85Chapter Chapter 5 --- Conclusion --- p.88Chapter Part II: --- Two Analytical Models for a Refined TCP Algorithm (TCP Veno) for Wired/Wireless Networks --- p.91Chapter Chapter 1 --- Introduction --- p.92Chapter 1.1 --- Brief Background --- p.92Chapter 1.2 --- Motivation and Two Analytical Models --- p.95Chapter 1.3 --- Organization of Part II --- p.96Chapter Chapter 2 --- Background --- p.97Chapter 2.1 --- TCP Veno Algorithm --- p.97Chapter 2.1.1 --- Packet Loss Type Identification --- p.97Chapter 2.1.2 --- Refined AIMD Algorithm --- p.99Chapter 2.1.2.1 --- Random Loss Management --- p.99Chapter 2.1.2.2 --- Congestion Management --- p.100Chapter 2.2 --- A Simple Model of TCP Reno --- p.101Chapter 2.3 --- Stochastic Modeling of TCP Reno over Lossy Channels --- p.103Chapter Chapter 3 --- Two Analytical Models --- p.104Chapter 3.1 --- Simple Model --- p.104Chapter 3.1.1 --- Random-loss Only Case --- p.105Chapter 3.1.2 --- Congestion-loss Only Case --- p.108Chapter 3.1.3 --- The General Case (Random + Congestion Loss) --- p.110Chapter 3.2 --- Markov Model --- p.115Chapter 3.2.1 --- Congestion Window Evolution --- p.115Chapter 3.2.2 --- Average Throughput Formulating --- p.119Chapter 3.2.2.1 --- Random-loss Only Case --- p.120Chapter 3.2.2.2 --- Congestion-loss Only Case --- p.122Chapter 3.2.2.3 --- The General Case (Random + Congestion Loss) --- p.123Chapter Chapter 4 --- Comparison with Experimental Results and Discussions --- p.127Chapter 4.1 --- Throughput versus Random Loss Probability --- p.127Chapter 4.2 --- Throughput versus Normalized Buffer Size --- p.132Chapter 4.3 --- Throughput versus Bandwidth in Asymmetric Networks --- p.135Chapter 4.3 --- Summary --- p.136Chapter Chapter 5 --- Sensitivity of TCP Veno Throughput to Various Parameters --- p.137Chapter 5.1 --- Multiplicative Decrease Factor (α) --- p.137Chapter 5.2 --- Number of Backlogs (β) and Fractional Increase Factor (γ) --- p.139Chapter Chapter 6 --- Conclusions --- p.142Bibliography --- p.14

Design and analysis of TCP AIMD in wireless networks

The class of additive-increase/multiplicative-decrease (AIMD) algorithms constitutes a key mechanism for congestion control in modern communication networks, like the current Internet. The algorithmic behaviour may, however, be distorted when wireless links are present. Specifically, spurious window reductions may be triggered due to packet reordering and non-congestive loss. In this paper, we develop a framework for AIMD in TCP to analyze the aforementioned problem. The framework enables a systematic analysis of the existing AIMD-based TCP variants and assists in the design of new TCP variants. It classifies the existing AIMD-based TCP variants into two main streams, known as compensators and differentiators, and develops a generic expression that covers the rate adaptation processes of both approaches. It further identifies a new approach in enhancing the performance of TCP, known as the compensation scheme. A tax-rebate approach is proposed as an approximation of the compensation scheme, and used to enhance the AIMD-based TCP variants to offer unified solutions for effective congestion control, sequencing control, and error control. In traditional wired networks, the new family of TCP variants with the proposed enhancements automatically preserves the same inter-flow fairness and TCP friendliness. We have conducted a series of simulations to examine their performance under various network scenarios. In most scenarios, significant performance gains are attained. © 2013 IEEE.published_or_final_versio

STCP: A New Transport Protocol for High-Speed Networks

Transmission Control Protocol (TCP) is the dominant transport protocol today and likely to be adopted in future high‐speed and optical networks. A number of literature works have been done to modify or tune the Additive Increase Multiplicative Decrease (AIMD) principle in TCP to enhance the network performance. In this work, to efficiently take advantage of the available high bandwidth from the high‐speed and optical infrastructures, we propose a Stratified TCP (STCP) employing parallel virtual transmission layers in high‐speed networks. In this technique, the AIMD principle of TCP is modified to make more aggressive and efficient probing of the available link bandwidth, which in turn increases the performance. Simulation results show that STCP offers a considerable improvement in performance when compared with other TCP variants such as the conventional TCP protocol and Layered TCP (LTCP)