LC-PCN: The Load Control PCN Solution

There is an increased interest of simple and scalable resource provisioning solution for Diffserv network. The Load Control PCN (LC-PCN) addresses the following issues:\ud o Admission Control for real time data flows in stateless Diffserv Domains\ud o Flow Termination: Termination of flows in case of exceptional events, such as severe congestion after re-routing.\ud Admission control in a Diffserv stateless domain is a combination of:\ud o Probing, whereby a probe packet is sent along the forwarding path in a network to determine whether a flow can be admitted based upon the current congestion state of the network\ud o Admission Control based on data marking, whereby in congestion situations the data packets are marked to notify the PCN-egress-node that a congestion occurred on a particular PCN-ingress-node to PCN-egress-node path.\ud \ud The scheme provides the capability of controlling the traffic load in the network without requiring signaling or any per-flow processing in the PCN-interior-nodes. The complexity of Load Control is kept to a minimum to make implementation simple.\u

Optimization flow control with estimation error

We analyze the effects of price estimation error in a dual-gradient optimization flow control scheme, and characterize the performance of the algorithm in this case. By treating estimation error as inexactness of the gradient, we utilize sufficient conditions for convergence subject to bounded error to characterize the long-term dynamics of the link utilization in terms of a region, which the trajectory enters in finite time. We explicitly find bounds for this region under a particular quantization error model, and provide simulation results to verify the predicted behavior of the system. Finally, we analyze the effects of the stepsize on the convergence of the algorithm, and provide analytical and numerical results, which suggest a particular choice for this parameter

Joint in-network video rate adaptation and measurement-based admission control: algorithm design and evaluation

The important new revenue opportunities that multimedia services offer to network and service providers come with important management challenges. For providers, it is important to control the video quality that is offered and perceived by the user, typically known as the quality of experience (QoE). Both admission control and scalable video coding techniques can control the QoE by blocking connections or adapting the video rate but influence each other's performance. In this article, we propose an in-network video rate adaptation mechanism that enables a provider to define a policy on how the video rate adaptation should be performed to maximize the provider's objective (e.g., a maximization of revenue or QoE). We discuss the need for a close interaction of the video rate adaptation algorithm with a measurement based admission control system, allowing to effectively orchestrate both algorithms and timely switch from video rate adaptation to the blocking of connections. We propose two different rate adaptation decision algorithms that calculate which videos need to be adapted: an optimal one in terms of the provider's policy and a heuristic based on the utility of each connection. Through an extensive performance evaluation, we show the impact of both algorithms on the rate adaptation, network utilisation and the stability of the video rate adaptation. We show that both algorithms outperform other configurations with at least 10 %. Moreover, we show that the proposed heuristic is about 500 times faster than the optimal algorithm and experiences only a performance drop of approximately 2 %, given the investigated video delivery scenario

Adaptive Deterministic Packet Marking

An efficient method is presented for signaling link price information using single-bit marks. It exploits side information in the IPid field of the IP header to allow the maximum price on a flow’s path to be estimated. It automatically adapts the resolution with which the price is quantized, depending on how quickly the price changes. The algorithm does not depend on the number of hops in a link. A marking scheme with improved compatibility with current ECN (RFC 3168) is also proposed

RMD-QOSM: The NSIS Quality-of-Service Model for Resource Management in Diffserv

This document describes a Next Steps in Signaling (NSIS) Quality-of- Service (QoS) Model for networks that use the Resource Management in Diffserv (RMD) concept. RMD is a technique for adding admission control and preemption function to Differentiated Services (Diffserv) networks. The RMD QoS Model allows devices external to the RMD network to signal reservation requests to Edge nodes in the RMD network. The RMD Ingress Edge nodes classify the incoming flows into traffic classes and signals resource requests for the corresponding traffic class along the data path to the Egress Edge nodes for each flow. Egress nodes reconstitute the original requests and continue forwarding them along the data path towards the final destination. In addition, RMD defines notification functions to indicate overload situations within the domain to the Edge nodes