Quality Of Service Goals Research Articles

Policy refinement for IP differentiated services Quality of Service management

Policy-based management provides the ability to dynamically re-configure DiffServ networks such that desired Quality of Service (QoS) goals are achieved. This includes network provisioning decisions, performing admission control, and adapting bandwidth allocation dynamically. QoS management aims to satisfy the Service Level Agreements (SLAs) contracted by the provider and therefore QoS policies are derived from SLA specifications and the provider's business goals. This policy refinement is usually performed manually with no means of verifying that the policies written are supported by the network devices and actually achieve the desired QoS goals. Tool support is lacking and policy refinement has rarely been addressed in the literature. This paper extends our previous approach to policy refinement and shows how to apply it to the domain of DiffServ QoS management. We make use of goal elaboration and abductive reasoning to derive strategies that will achieve a given high-level goal. By combining these strategies with events and constraints, we show how policies can be refined, and what tool support can be provided for the refinement process using examples from the QoS management domain. The approach presented here can be used in other application domains such as storage area networks or security management.

Using adaptive routing to achieve Quality of Service

Self-monitoring allows a network to observe its own behavior via probing and measurement mechanisms. This can then be exploited by the system to take autonomous decisions for the purpose of system management, performance management and user Quality of Service (QoS). In this paper, we experimentally explore how QoS goals that are externally set by network users, can then be explicitly exploited by a self-aware network to control its own behavior to attain these goals. The experiments we report are conducted in two distinct Cognitive Packet Network (CPN) test-beds which use probing to select the routes which best satisfy the QoS goal. Our experiments validate this concept with QoS goals which include end-to-end delay, packet loss, and a mixture of these two metrics. We observe that using only delay in the QoS goal is a good way to reduce delay and loss if losses result only from congestion. However, using loss in the QoS goal is seen to be useful if the paths that are adaptively selected avoid nodes where packet losses occur for reasons other than congestion. In general we observe that CPN networks effectively adapt routing behavior to the QoS goal that is specified.

Performance Tradeoffs in Scheduling Techniques for Mixed Workloads

Many modern multimedia applications require the retrieval of different “classes” of data with drastically different characteristics. For instance, digital libraries type systems must be designed to deliver not only text files and still images, but voice and video as well. These applications can benefit from the sharing of resources such as disk and network bandwidth, instead of the conservative approach of partitioning the resources according to the characteristics of each type of data being retrieved. Continuous and non-continuous media applications, require different performance metrics to be achieved, so that the necessary quality of service (QoS) is satisfied. As a consequence, the proper managing of resources is a major issue in order to provide the complete sharing of resources and yet reaching the QoS goals. This work focuses on multimedia storage systems that are capable of serving a mixture of continuous and non-continuous workloads. Our main objective is to expose and investigate the tradeoffs involved in managing the system resources, in particular, I/O bandwidth. The performance metrics of interest are the mean and variance of response time for non-continuous media requests and the probability of missing an imposed deadline for continuous media workloads. Different scheduling algorithms are considered and tradeoffs to achieve performance goals are studied, including those involving buffer sizing.

Adaptive marking for assured forwarding service

This letter looks at the problem of achieving specific quality of service (QoS) goals of individual flows by flexibly managing resources available to an aggregated source. We present an adaptive marker based on a TCP performance model within a Diffserv network, and show that the aggregated marker can maintain state of individual flows at the edge of the network and utilize this state effectively in adaptively marking packets of individual flows to meet their QoS goals.

Design and performance of cognitive packet networks

We discuss a packet network architecture called a cognitive packet network (CPN), in which intelligent capabilities for routing and flow control are moved towards the packets, rather than being concentrated in the nodes and protocols. Our architecture contains “smart” and “dumb” packets, as well as acknowledgement packets. Smart CPN packets route themselves, and learn to avoid congestion and losses from their own observations about the network and from the experience of other packets. They use a reinforcement learning algorithm to route themselves based on a goal function which has been assigned to them for each connection. Dumb CPN packets of a specific quality of service (QoS) class use routes which have been selected by the smart packets (SPs) of that class. Acknowledgement (ACK) packets are generated by the destination when an SP arrives there; the ACK heads back to the source of the SP along the inverse route and is used to update mailboxes in CPN routers, as well as to provide source routing information for dumb packets. We first summarize the basic concepts behind CPN, and present simulations illustrating their performance for different QoS goals, and analytical results for best and worst case performance. We then describe a test-bed network we have designed and implemented in order to demonstrate these ideas. We provide measurement data on the test-bed to illustrate the capacity of the network to adapt to changes in traffic load and to failures of links. Finally, we use measurements to evaluate the impact of the ratio of smart to dumb packets on the end-to-end delay experienced by all of the packets.

QoS Management by Means of ApplicationControl

The complexity and sophistication of integrated broadband networks call for a broad repertoire of management methods. Foreseen intensive competition of the communications market, and the upgrade of end-customer's satisfaction as the focal point of any management policy, raise a very important problem: how to utilize efficiently the resources of the network while maintaining the Quality of Service (QoS) provided to end-users within a pre-negotiated range. In this paper, a QoS management architecture for multimedia applications based on an application control scheme is proposed. Adhering to the Total Quality Management (TQM) paradigm, we let management span over the entire communication stack, the entire network (end-to-end) and the entire call duration. Application control scheme aims to meet pre-specified QoS goals by adjusting the traffic produced by the end-user applications. The adjustment technique is based on the notion that each multimedia session is allowed to operate on a set of discrete application quality levels. A method for monitoring and assessing the end-user perceived quality is presented. The mathematical problem of optimal resources allocation and an associated heuristic are specified. Finally, a specific instantiation of the introduced QoS management architecture on a real testbed is described and experimentation results are presented and evaluated.