Internet admission control based on short and long flows classification

In the context of the present evolution of the Internet architecture, recent papers have shown the interest of introducing flow level admission control mechanisms. The key idea is to manage guaranteeing to each accepted flow a minimum of resources by limiting the number of flows accepted in the network. Most of the current works suppose that the bandwidth sharing between several flows is of "Processor Sharing" type. This assumption is valid for long TCP flows. Nevertheless, it is more difficult to justify it for short flows. In this paper, we propose a model of admission control for TCP flows that deals with short and long flows, as well as with the specific QoS constraints of each type of flow. We show by simulation the interest of the proposed approach in terms of performances. Moreover, we evaluate the impact of allocating ressources to the long and short flows aggregates through a WFQ scheduling. We have solved an analytical model, which gives an approximation of what could be the optimal values of thresholds for the two types of flow. IINTRODUCTION The Internet of first generation is based on an extreme approach which consists on the acceptance of all flows that arise at the network and on the effort of sharing the resources in an equitable way between the various transported flows (we concentrate here on TCP flows). Even in the theoretical case where an equitable share is obtained, the network cannot assure any level of QoS. Indeed, the available resources for each individual flow decrease with the number of flows sharing the resources while the number of accepted flows is not controlled. To satisfy the QoS requirements, admission control is required. Per flow admission control is commonly used in connection oriented networks (PSTN, ATM, etc.) but has only recently been studied in the IP networking context. Admission control mainly determines if a new flow could be admitted, with a decision depending on whether the network can support the QoS of the new flow and still maintain the QoS requirements of previously accepted flows. Recently, various admission control approaches have been proposed to improve network utilization [1-6]. While admission control is generally agreed to be necessary for stream traffic, it has been shown that it is also essential for elastic traffic. Admission control for elastic traffic has been used in order to ensure a minimum bandwidth for each admitted flow and to avoid unnecessary traffic in the network due to retransmissions of packets or even whole transfers after a temporary overload situation. Most of the current work in the literature do not make any distinction between short and long flows. It is usually assumed that the bandwidth sharing between several flows is of "Processor Sharing" type. This assumption is valid, in certain contexts, for long TCP flows. Nevertheless, it is more difficult to justify it for short flows because of the behavior of the TCP congestion control mechanism. Moreover, short flows are transmitted with small TCP windows, which implies that a loss is often detected only after a timeout and possibly after all data has been sent to the network. As a result, timeouts on short TCP connections are not very effective in reducing the overall traffic and stabilizing the network [7]. A loss occurrence for a short TCP transfer may thus increase the transfer time manifold. On the other hand, a reduction in the latency of the order of one second would be a significant improvement for short transactions [8]. Oscillatory behavior and unfairness towards short connections have also been noticed in a previous studies [9-12]. The authors address the differentiation between short and long flows in Internet networks. The proposed implementation mechanisms and simulation studies have the drawbacks of relying on buffer architectures that requires the tuning of many parameters such as RIO and RED. In addition, they didn’t use any approach of admission control for limiting the active connections. In contrast, in this paper, we propose the use of simple queue with Drop Tail that has the advantage of being robust and scalable. This queue is used with a model of admission control for TCP flows that deals with short and long flows, as well as with the specific QoS constraints of each type of flow (we are not interested here in UDP flows which remain still minority in number and volume of consumed resources). Using simulations, we show the interest of such approach in terms of performances. In particular, we are interested in calculating the mean sojourn time of a flow. The other metrics of interest are the throughput and the blocking probability induced by the admission control. First, we are interested in case where all flows (long and short) are mixed with each other in the same buffer. Then, the impact of allocating resources to the long and short flows aggregates is evaluated. In order to avoid wasting resources, the bandwidth allocation between aggregates is made by a WFQ scheduling. If an aggregate does not use the minimal P75/2 bandwidth, the residual bandwidth can thus be used by the other aggregate. This approach is used for each network link or source routed path (in an MPLS context, for example). The rest of the paper is organized as follows. In section II, the characteristics of short and long TCP flows are presented. In section III, we present our admission control approach. The impact of the proposed approach is analysed in section IV, both for FIFO and WFQ cases. The impact of delaying flows before acceptance in case of congestion is analized. In section V we define an analytical model to study the optimum thresholds. In section VI we show that Processor sharing could be a very bad approach for TCP congestion control mechenism. Concluding remarks are given in section VII. II. TRAFFIC CHARACTERIZATION A significant amount of today’s Internet traffic is carried out by the TCP transport protocol [13]. The measurements reported in http://ipmon.sprintlabs. com and [14] show that TCP traffic represents more than 90% of the volume of Internet traffic in bytes and more than 80% of flows. Nevertheless, it is important to highlight that this numbers vary significantly between ISPs and will probably change in the futur with the generalization of innovative applications. The results of several series of measurements [15] show that a great majority of elastic flows is of small volume (called short or mice) while a weak minority of flows is of large volume (called long or elephant). This minority of flows generates the greatest part of the volume of the traffic. Short and Long Flows Requirements Short and long flows have different characteristics and QoS requirements. Short-lived TCP flows arrive in a more bursty fashion, which prevents long TCP flows from operating in a predictable mode. Short TCP flows seldom need to operate beyond the slow-start phase of TCP to finish their transmission and consequently their window size is generally small. As such, they generate smaller packet bursts. Since long-lived TCP connections mostly operate in congestion avoidance phase probing for bandwidth with larger windows, they produce larger packet bursts. TCP connections with large window sizes are more tolerant of packet loss than those with small windows. While long TCP flows may recover from multiple packet losses in one round-trip time (RTT) [16], short TCP flows have to wait for a time-out period to recover from a single packet loss. It is observed that long TCP flows may completely shut off short TCP flows [17]. This causes performance problems for short TCP flows, which generally carry interactive/delay sensitive data. From the user perception, the mean response time and its variance are an appropriate metrics for short flows, whereas the average throughput is an appropriate metric for the long flows. These metrics are discussed in depth in section III. Flow Identification In this paper we define a flow as a TCP connection. We suppose that at a given router, a list of state information is kept for active flows and the flow identity of all arriving packets is systematically compared with this list to detect new flows for which an admission control decision is required. The flow identity is determined from certain fields in the packet header (e.g. source and destination address and port numbers in IPv4). It may also be envisaged to define a specific flow ID field as in IPv6, which provides added flexibility in the designation of what constitutes a “flow”. III. PROPOSED ADMISSION CONTROL APPROACH We present in this section our admission control approach. We focus our investigation on a single link (Fig.1). There are two types of arrivals to the system; short and long flows. An independent admission control is applied on each class. Two scheduling cases are studied: 1) FIFO: Packets of short and long flows aggregates share the available bandwidth according to a FIFO policy. All flows are mixed with each other in the same buffer. 2) WFQ: Short and long flows are separated into two classes and a specific buffer is used for each class. Bandwidth is allocated to each flow aggregate (long and short flows aggregates) based on a WFQ scheduler. Thus, the scheduler does not distinguish individual flows but only the aggregates of long and short flows.