Traffic Characteristics-based Flow Assignment Method for Reducing Queuing Delay Yoshinor Kitatsuji ∗ , Satoshi Katsuno † , Masato Tsuru ‡ , Tetsuya Takine § and Yuji Oie ‡ ∗ National Institute of Information and Communications Technology, Fukuoka Japan Email: kitaji[at]kyushu.jgn2.jp † KDDI R&D Laboratories, Inc., Saitama Japan Email: katsuno[at]kddilabs.jp ‡ Kyushu Institute of Technology, Fukuoka Japan Email: {tsuru[at]ndrc, oie[at]cse}.kyutech.ac.jp § Osaka University, Osaka Japan Email: takine[at]comm.osaka-u.ac.jp Abstract— In traffic engineering, for effectively distributing traffic flows over multiple network paths, it is vital to take traffic characteristics of individual flows into account in appro- priately assigning the flows to the network paths to achieve better delay performance as a whole. We have developed a traffic characteristic-based flow assignment method that reduces queuing delay in a buffer at the beginning of each network path. By taking the traffic characteristics of individual flows into account the method can effectively assigns flows to the paths so as to minimize overall queuing delay. We consider the simple case in which two types of flows with distinct traffic characteristics (burstiness) are assigned to two bandwidth-guaranteed paths. The flow assignment of our method reduces the queuing delay (at the edge router) of the worse path, by attempting to optimize the min-max fairness between the paths in terms of queuing delay. Numerical simulation showed that the method assigned the flows such that the queuing delay was reduced up to 40% compared with that when conventional path utilization based flow assignment was used. This means that taking the traffic characteristics of flows into account significantly improves the queuing delay performance when the flows have distinct characteristics. I. I NTRODUCTION Internet service providers are facing the challenge of dy- namically and adaptively designing their networks to satisfy customer demands for fast, reliable, and differentiated services with the minimal cost. Internet traffic engineering (TE) [1] is a key tool for meeting this challenge because it can effectively map traffic demands onto the network topology and adaptively reconfigure the mapping as network conditions change. More specifically, TE can adaptively distribute traffic flows over networks so that network resources are efficiently allocated. The fundamental philosophy for making the Internet scal- able is that an algorithmically complex processing should be pushed to the edge of the network whenever possible. When designing a backbone network that supports TE the backbone network having two levels of components – a high-speed core and edge routers surrounding the core – reflects this philosophy. Consider the case in which individual pairs of edge routers establish multiple paths to convey traffic from one edge (ingress) router to another edge (egress) router. Effective Edge Router Edge Router Backbone network Fig. 1. Simple case considered in this paper: a number of flows, each having one of two distinct sets of traffic characteristics, are assigned to one of two paths with different bandwidths. traffic distribution can be achieved by balancing traffic flows among these paths. [2] [3]. In distributing the traffic flows, however, inadequate traffic balancing into multiple paths significantly degrades queuing delay performance, especially when the path is highly utilized [4] [5]. When different (bursty and non-bursty) types of flows are given to be balanced over multiple paths, the non-bursty flows assigned to the same path as the bursty flows encounter the same queuing delay performance as the bursty ones. In addition, when the path bandwidths are different, conventional path utilization based flow assignment, that is, assigning flows on the basis of the ratio of path bandwidths for each flow type, results in dropping the queuing delay performance of the narrower path more severely. Therefore, given a set of flows with distinct traffic characteristics and different path bandwidths, it is not trivial to determine how to distribute them so as to minimize overall queuing delay, that is, to achieve a good balance of the flows in terms of their queuing delays. In this paper, we consider a simple case: a number of flows, each having one of two distinct traffic characteristics, are assigned to one of two paths with different bandwidths (Figure 1). A queuing delay statistic, such as, the mean queuing delay, the standard deviation of the queuing delay, or the 99.5-th