Optimal per-node rate allocation to provide per-flow end-to-end delay guarantees in a network of routers supporting guaranteed service class

Abstract

Abstract-In this paper, we investigate the problem of providing worst-case end-to-end delay guarantee to a token bucket constrained flow traversing a series of N packet schedulers. We consider a network of routers that support the Guaranteed Service class of the IETF Integrated Services (IntServ) Working Group; this service class is proposed to provide Quality of Service (QoS) in the Internet. Under this framework, a worst-case end-to-end delay bound to a flow is provided by allocating a rate at each network element on the path of the flow. We associate a cost with allocating a rate at each link. The cost is assumed to be a convex and non-decreasing function of rate. We investigate the problem of obtaining an optimal rate allocation for a flow that minimizes the total cost subject to the delay requirement and the available link capacity constraints. Allocating an identical rate at each link on the path of a flow is a widely used approach under the Guaranteed Service framework. We investigate the optimality of this approach and show that under certain conditions, it need not be optimal. Moreover, we investigate the optimal solution to the total cost minimization problem and give scenarios in which we can explicitly obtain the optimal solution. Based on these results, we present an algorithm for optimal rate allocation that is based on multiple rates. However, with blocking probability as the performance criterion, we find through simulations, that the optimal rate allocation algorithm is only marginally better for connections with longer path lengths at the expense of those with shorter path lengths. We also observe that the performances of both the algorithms are very close and so, in practice, the simpler identical rate algorithm may be sufficient.

Capacity assignment in multiservice packet networks with soft maximum waiting time guarantees

“…The studies in Verma et al (1998), Diwan et al (2002) and Choi (2008) address the problem of capacity assignment with hard endto-end delay guarantees. The authors in Verma et al (1998) and Diwan et al (2002) present efficient resource allocation approaches based on mapping the end-to-end quality requirements into perhop requirements. A network dimensioning method for multiservice IP networks with hard quality guarantees is presented in Choi (2008).…”

On the advantages of optimal end-to-end QoS budget partitioning

“…The variables C are then fixed at the values obtained from the dimensioning. Next we change the traffic matrix in some way and solve problem (7-13) but this time with g s (C s ) = 0, without the GoS constraints (10), and given C.…”

“…The derivation of the optimality conditions for other variations of the model is similar. For the remainder of this section, we drop the revenue term in the objective function of the model (7)(8)(9)(10)(11)(12)(13) and present the first-order optimality conditions for this reduced formulation. We also give an economic interpretation of the path marginal price and induced costs.…”

“…The work of Diwan et al [10] is based on a fluid service model. They use a Weighted Fair Queueing (WFQ) service policy, a cost function equal to the rate allocated to a service class and a min-hop path routing.…”

“…We solve model (7)(8)(9)(10)(11)(12)(13) with w l,m i = 0 so that we are optimizing only the construction cost. This is an example of the flexibility afforded by the model which can be tailored to specific situations with much of the analysis still valid.…”