Transport Control Protocol Flows Research Articles

TCP Acknowledgment Optimization in Low Power and Embedded Devices

Paper investigates transport control protocol (TCP) acknowledgment (ACK) optimization in low power or embedded devices to improve their performance on high-speed links by limiting the ACK rate. Today the dominant protocol for interconnecting network devices is the TCP and it has a great influence on the entire network operation if the processing power of network devices is exhausted to the processing data from the TCP stack. Therefore, on high-speed not congested networks the bottleneck is no longer the network link but low-processing power network devices. A new ACK optimization algorithm has been developed and implemented in the Linux kernel. Proposed TCP stack modification minimizes the unneeded technical expenditure from TCP flow by reducing the number of ACKs. The results of performed experiments show that TCP ACK rate limiting leads to the noticeable decrease of CPU utilization on low power devices and an increase of TCP session throughput but does not impact other TCP QoS parameters, such as session stability, flow control, connection management, congestion control or compromises link security. Therefore, more resources of the low-power network devices could be allocated for high-speed data transfer.

A Performance Analysis Model of TCP over Multiple Heterogeneous Paths for 5G Mobile Services

Driven by the primary requirement of emerging 5G mobile services, the demand for concurrent multipath transfer (CMT) is still prominent. Yet, multipath transport protocols are not widely adopted and CMT schemes based on Transport Control Protocol (TCP) will still be in dominant position in 5G. However, the performance of TCP flow transferred over multiple heterogeneous paths is prone to the link quality asymmetry, the extent of which was revealed to be significant by our field investigation. In this paper, we present a performance analysis model for TCP over multiple heterogeneous paths in 5G scenarios, where both bandwidth and delay asymmetry are taken into consideration. The evaluation using large-scale simulation and field experiment shows that the proposed model can achieve high accuracy in practical environments. Some interesting inferences can be drawn from the proposed model, such as the dominant factors that affect the performance of TCP over heterogeneous networks, and the criteria of determining the appropriate number of links to be used under different circumstances of path heterogeneity. Thus, the proposed model can provide a guidance to the design of TCP-based CMT solutions for 5G mobile services.

Analytical modeling of TCP dynamics in infrastructure-based IEEE 802.11 WLANs

IEEE 802.11 wireless local area network (WLAN) has become the prevailing solution for wireless Internet access while transport control protocol (TCP) is the dominant transport-layer protocol in the Internet. It is known that, in an infrastructure-based WLAN with multiple stations carrying long-lived TCP flows, the number of TCP stations that are actively contending to access the wireless channel remains very small. Hence, the aggregate TCP throughput is basically independent of the total number of TCP stations. This phenomenon is due to the closed-loop nature of TCP flow control and the bottleneck downlink (i.e., access point-to-station) transmissions in infrastructure-based WLANs. In this paper, we develop a comprehensive analytical model to study TCP dynamics in infrastructure-based 802.11 WLANs. We calculate the average number of active TCP stations and the aggregate TCP throughput using our model for given total number of TCP stations and the maximum TCP receive window size. We find out that the default minimum contention window sizes specified in the standards (i.e., 31 and 15 for 802.11b and 802.11a, respectively) are not optimal in terms of TCP throughput maximization. Via ns-2 simulation, we verify the correctness of our analytical model and study the effects of some of the simplifying assumptions employed in the model. Simulation results show that our model is reasonably accurate, particularly when the wireline delay is small and/or the packet loss rate is low.

Cluster processes: a natural language for network traffic

We introduce a new approach to the modeling of network traffic, consisting of a semi-experimental methodology combining models with data and a class of point processes (cluster models) to represent the process of packet arrivals in a physically meaningful way. Wavelets are used to examine second-order statistics, and particular attention is paid to the modeling of long-range dependence and to the question of scale invariance at small scales. We analyze in depth the properties of several large traces of packet data and determine unambiguously the influence of network variables such as arrival patterns, durations, and volumes of transport control protocol (TCP) flows and internal flow structure. We show that session-level modeling is not relevant at the packet level. Our findings naturally suggest the use of cluster models. We define a class where TCP flows are directly modeled, and each model parameter has a direct meaning in network terms, allowing the model to be used to predict traffic properties as networks and traffic evolve. The class has the key advantage of being mathematically tractable, in particular, its spectrum is known and can be readily calculated, its wavelet spectrum deduced, interarrival distributions can be obtained, and it can be simulated in a straightforward way. The model reproduces the main second-order features, and results are compared against a simple black box point process alternative. Discrepancies with the model are discussed and explained, and enhancements are outlined. The elephant and mice view of traffic flows is revisited in the light of our findings.