In recent years elephant flows are increasing by expansion of peer-to-peer (P2P) applications on the Internet. As a result, bandwidth is occupied by specific users triggering unfair resource allocation. The main packet-scheduling mechanism currently employed is first-in first-out (FIFO) where the available bandwidth of short flows is limited by elephant flows. Least attained service (LAS), which decides transfer priority of packets by the total amount of transferred data in all flows, was proposed to solve this problem. However, routers with LAS limit flows with large amount of transferred data even if they are low-rate. Therefore, it is necessary to improve the quality of low-rate flows with long holding times such as voice over Internet protocol (VoIP) applications. This paper proposes rate-based priority control (RBPC), which calculates the flow rate and control the priority by using it. Our proposed method can transfer short flows and low-rate flows in advance. Moreover, its fair performance is shown through simulations.

With the emergence of bandwidth-greedy application services, high-speed transport protocols are expected to effectively and aggressively use large amounts of bandwidth in current broadband and multimedia networks. However, when high-speed transport protocols compete with other standard TCP flows, they can occupy most of the available bandwidth leading to disruption of service. To deploy high-speed transport protocols on the Internet, such unfair situations must be improved. In this paper, therefore, we propose a method to improve fairness, called Kyushu-TCP (KTCP), which introduces a non-aggressive period in the congestion avoidance phase to give other standard TCP flows more chances of increasing their transmission rates. This method improves fairness in terms of the throughput by estimating the stably available bandwidth-delay product and adjusting its transmission rate based on this estimation. We show the effectiveness of the proposed method through simulations.

This proposes a scalable QoS control scheme, called Elephant Flow Control Scheme (EFCS) for high-speed large-capacity networks; it controls congestion and provides appropriate bandwidth to normal users' flows by controlling just the elephant flows. EFCS introduces a sampling packet threshold and drops packets considering flow size. EFCS also adopts a compensation parameter to control elephant flows to an appropriate level. Numerical results show that the sampling threshold increases control accuracy by 20% while reducing the amount of memory needed for packet sampling by 60% amount of memory by packet sampling; the elephant flows are controlled as intended by the compensation parameter. As a result, EFCS provides sufficient bandwidth to normal TCP flows in a scalable manner.

Analysing and modeling of traffic play a vital role in designing and controlling of networks effectively. To construct a practical traffic model that can be used for various networks, it is necessary to characterize aggregated traffic and user traffic. This paper investigates these characteristics and their relationship. Our analyses are based on a huge number of packet traces from five different networks on the Internet. We found that: (1) marginal distributions of aggregated traffic fluctuations follow positively skewed (non-Gaussian) distributions, which leads to the existence of "spikes", where spikes correspond to an extremely large value of momentary throughput, (2) the amount of user traffic in a unit of time has a wide range of variability, and (3) flows within spikes are more likely to be "elephant flows", where an elephant flow is an IP flow with a high volume of traffic. These findings are useful in constructing a practical and realistic Internet traffic model.