Measurement-based Admission Control Algorithms Research Articles

Admission Control in IMS Networks

In our paper there is an emphasis on simulations of admission control methods in MATLAB environment. The main task of admission control method is to make a decision if the connection requiring network access should be accepted to the network or the access should be rejected. If the connection is accepted to the network, the admission control has to ensure that Quality of Service of this connection will be satisfied, as well as Quality of Service of all other existing connections. We have observed several Measurement based admission control algorithms and the result is the identification of the suitable algorithm which can estimate the required bandwidth.

Measurement of packet loss probability by optimal design of packet probing experiments

Packet-level measurement is now critical to many aspects of broadband networking, for example for guaranteeing service level agreements, facilitating measurement-based admission control algorithms and performing network tomography. Because it is often impossible to measure all the data passing across a network, the most widely used method of measurement works by injecting probe packets. The probes provide samples of the packet loss and delay, and from these samples the loss and delay performance of the traffic as a whole can be deduced. However, measuring performance like this is prone to errors. Recent work has shown that some of these errors are minimised by using a gamma renewal process as the optimal pattern for the time instants at which to inject probes. This leaves the best rate at which to inject probes as the key unsolved problem, and this is addressed here by using the statistical principles of the design of experiments. The experimental design approach allows one to treat packet-level measurements as numerical experiments that can be designed optimally. Modelling the overflow of buffers as a 2-state Markov chain, the system's likelihood function is deduced, and from this a technique (using the Fisher information matrix) to determine the upper-bound on the optimal rate of probing is developed. A generalisation of this method accounts for the effect of the probed observations interfering with the experiment. The numerical results focus on VoIP traffic, allowing one to show how this methodology would be used in practice. One application of this is in measurement-based admission control algorithms, where the technique can be used to provide an upper-bound on the rate at which probes should be injected to monitor the loss performance of the target network, prior to making an admit/do not admit decision.

A coarse-grain analysis for the performance of measurement-based admission control algorithms

Network load control mechanisms have become important due to merging towards IP-packet switched networks, Fixed-Mobile Convergence (FMC) and the growing diversity of Internet applications. These applications vary in terms of size, content, time duration, and Quality of Service (QoS) requirements. These current advancements require new design criteria for traffic control mechanisms to cope with the growing complexity of future networks and the increasing diversity of network applications. Previous work on the design and performance evaluation criteria of Call Admission Control (CAC) algorithms has taken link utilization as a measure of efficient allocation of available network resources while enhancing QoS. We believe that considering only link utilization to evaluate the performance of CAC algorithms is not an accurate criterion. In this paper, we propose a simple and robust method for evaluating the performance and design considerations of CAC algorithms. The proposed approach is based on flow parameters such as call admission rate, call rejection rate, average call duration and provided QoS parameters with respect to link utilization level. This flow-based evaluation method is particularly important for optimal resource allocation, efficient service management and content-based pricing.

Statistical admission control using delay distribution measurements

Growth of performance sensitive applications, such as voice and multimedia, has led to widespread adoption of resource virtualization by a variety of service providers (xSPs). For instance, Internet Service Providers (ISPs) increasingly differentiate their offerings by means of customized services, such as virtual private networks (VPN) with Quality of Service (QoS) guarantees or QVPNs. Similarly Storage Service Providers (SSPs) use storage area networks (SAN)/network attached storage (NAS) technology to provision virtual disks with QoS guarantees or QVDs. The key challenge faced by these xSPs is to maximize the number of virtual resource units they can support by exploiting the statistical multiplexing nature of the customers' input request load.While a number of measurement-based admission control algorithms utilize statistical multiplexing along the bandwidth dimension, they do not satisfactorily exploit statistical multiplexing along the delay dimension to guarantee distinct per-virtual-unit delay bounds. This article presents Delay Distribution Measurement (DDM) based admission control algorithm, the first measurement-based approach that effectively exploits statistical multiplexing along the delay dimension. In other words, DDM exploits the well-known fact that the actual delay experienced by most service requests (packets or disk I/O requests) for a virtual unit is usually far smaller than its worst-case delay bound requirement because multiple virtual units rarely send request bursts at the same time. Additionally, DDM supports virtual units with distinct probabilistic delay guarantees---virtual units that can tolerate more delay violations can reserve fewer resources than those that tolerate less, even though they require the same delay bound. Comprehensive trace-driven performance evaluation of QVPNs (using Voice over IP traces) and QVDs (using video stream, TPC-C, and Web search I/O traces) shows that, when compared to deterministic admission control, DDM can potentially increase the number of admitted virtual units (and resource utilization) by up to a factor of 3.

A structural comparison of measurement-based admission control algorithms

Measurement-based admission control (MBAC) algorithm is designed for the relaxed real-time service. In contrast to traditional connection admission control mechanisms, the most attractive feature of MBAC algorithm is that it does not require a prior traffic model and that is very difficult for the user to come up with a tight traffic model before establishing a flow. Other advantages of MBAC include that it can achieve higher network utilization and offer quality service to users. In this article, the study of the equations in the MBAC shows that they can all be expressed in the same form. Based on the same form, some MBAC algorithms can achieve same performance only if they satisfy some conditions.

Dynamic resizing of utilization target in measurement-based admission control

A major issue in design of measurement-based admission control (MBAC) algorithms relies on how to maximize link utilization while meeting applications’ QoS constraints. Studies have claimed that many proposed MBAC algorithms would give the same performance if the parameters were properly tuned. In this paper, we study the effects of tuning two of the most important parameters in MBAC algorithms: Measurement Window and Utilization Target. We show that the measurement window is not a good tuning knob for enforcing rigid loss probability constraints. We propose a new parameter called Soft Utilization Target combined with a simple flow admittance policy called the Latch algorithm. The simulation results show that this scheme can achieve better enforcement of loss probability constraint while maintaining higher link utilization.