A New Algorithm for Measurement-based Admission Control in Integrated Services Packet Networks

Adaptive admission control algorithm in a QoS-aware Web system

The General Packet Radio Service (GPRS) provides the predictive services for the users by applying the similar algorithm in the QoS management mechanisms used by the ATM. Research shows that a connective Measurement-Based Admis- sion Control (MBAC) algorithm is more adaptable to and efficient for the GPRS network than other admission control algorithms. Based on sufficient analysis of the characteristics of GPRS, a MBAC algorithm is presented which is suitable for GPRS using a worst-case delay calculation model with a priority queue, and equivalent leaky bucket approximation and delay normalization. The most char- acteristic of this algorithm is that it used both bandwidth and delay at the same time for the control admission. The emulation result shows that this algorithm can achieve a rate of as high as 80% resource utilization while satisfying the requirements of GPRS QoS.

We address two issues in this work: on one hand, we consider and compare five throughput predictors to be used in a Web system in order to estimate its future performance and, on the other hand, we propose an adaptive QoS-aware admission control algorithm that is based on a resource allocation scheme that includes a throughput predictor. In order to obtain a low overhead, the monitoring of the arrival traffic to the Web system is done following an adaptive time slot scheduling based on the burstiness factor that we defined in a previous work. Simulation results of the behaviour of the five throughput predictors and the admission control algorithm are presented and discussed.

A measurement-based admission control algorithm using a variable-size window is developed. The size of the measurement window is varied according to the estimate of the variance of the traffic in the measurement window. We use a small measurement window when the traffic is smooth (small variations) and we use large measurement window when the traffic is bursty (large variations). Our simulation studies provide results that complement two existing works (see Breslau, L. et al., 2000; Lee, S.K. and Song, J.S., 1998). On the one hand, we conclude that when the desired utilization rate is low, measurement-based admission control algorithms using a variable-size measurement window can improve the performance over algorithms using a fixed-size window. On the other hand, when the desired utilization rate is high, measurement-based admission control algorithms using a variable-size window and using a fixed-size window provide nearly identical performance results.

Wireless multimedia services have to rely on strict quality of service (QoS) requirements to reach the feasibility, including guaranteed available bandwidth, tight delay constraint, and hard jitter tolerance. WiMAX has emerged as one of the most promising broadband wireless access technologies to support these types of services. To guarantee the QoS of connections, CAC (Call Admission Control) can grant a new call only while the required bandwidth is available. With concern about connection capacity, the CAC seems rigid and turns into an obstacle instead while the bandwidth of some connections could be stolen temporarily. Thus, adaptive admission control, differing from the conventional CAC, can flexibly increase connection capacity by stealing bandwidth based on user streaming buffer (USB). A connection in sufficient USB state implies that the undergoing streaming application can perform smoothly even if its bandwidth is stolen temporarily. Therefore, how to determine the USB state of each connection is the most important topic in this study. In order to effectively decrease the risk of system overuse arising from stealing bandwidth, the adaptive admission control is extended by means of an intelligent mechanism to decide the USB states. The simulation results show the proposed intelligent mechanism utilizing fuzzy neural network (FNN) really outperforms than the adaptive admission control in terms of controlling the probability of poor application performance. With approximate connection capacity (or call blocking probability), the intelligent resource management indeed decreases the risk of system overuse.

The paper proposes an adaptive admission control (AC) policy, that reduces call dropping probability, resorting to rate adaptation in accordance with the instantaneous connection configurations. We describe the philosophy of the proposed adaptive scheme and analyze the effective call dropping probability when considering a single cell UMTS scenario with an additive white Gaussian noise (AWGN) channel. Our simulations demonstrate that, by employing the proposed scheme, the network performance can be extremely increased while the quality of service (QoS) requested is respected.

We present an adaptive service (or call) admission control algorithm (ASACA) for integrated services packet networks. The proposed algorithm does not require a priori knowledge of the source characteristics, and it consists of two steps. The first step adapts the service rate of the system based on the number of frames lost during the observation period, and the second step estimates the expected delay associated with each class of service upon admitting or rejecting a service in the system. For this purpose, we use an M/M/1 queueing model such that the current statistical delay is added to the error estimates of the delay scaled by its gradient. While admitting a service, we ensure that the delay commitments towards the requirement profile of ongoing services are preserved. Further the sum of the statistical arrival rates for each class of service and the peak rate of the new call is not allowed to exceed the current system service rate. Simulation experiments demonstrate that our adaptive service control algorithm, ASACA, performs twice as well as a non-adaptive algorithm using an M/M/1 model, in meeting the service requirements but at the cost of a reduced number of calls admitted into the system, the number of which depends on the system load.

Wireless multicasting is becoming increasingly important for efficient distribution of streaming media and location-aware services to mobile and hand-held devices, network management, and software updates over cellular (UMTS-LTE) and indoor/outdoor wireless networks (e. g., 802.11/16). Multicast beamforming was recently proposed as a means of exploiting the broadcast nature of the wireless medium to boost spectral efficiency and meet Quality of Service (QoS) requirements. Infeasibility is a key issue in this context, due to power or mutual interference limitations. We therefore consider the joint multicast beamforming and admission control problem for one or more co-channel multicast groups, with the objective of maximizing the number of subscribers served and minimizing the power required to serve them. The problem is NP-hard even for an isolated multicast group and no admission control; but drawing upon our earlier work for the multiuser SDMA downlink, we develop an efficient approximation algorithm that yields good solutions at affordable worst-case complexity. For the special case of an isolated multicast, Lozano proposed a particularly simple adaptive algorithm for implementation in UMTS-LTE. We identify strengths and drawbacks of Lozano's algorithm, and propose two simple but worthwhile improvements. All algorithms are carefully tested on publicly available indoor/outdoor measured channel data.

Mobility model and call admission control (CAC) algorithm are important for wireless mobility networks. This paper firstly sets a practical mobility model, and then presents a novel measurement-based CAC algorithm utilizing time series analysis under the random model. The algorithm updates the reservation threshold by directly forecasting the next possible number of handoff dropping calls, using ARMA (auto regressive moving average) model. The simulation results suggest that the approach achieves a higher resource utilization than existing approaches while reliably meeting the target handoff-call-dropping probability. Also, the algorithm provides lower new-call-blocking probability.

Measurement based admission control (MBAC) has long been recognized as the best method for providing stochastic service guarantees. Since MBAC relies on measurements, the actual performance of MBAC can only be established through simulations or on real networks. There are two main performance measures: 1) how well the MBAC can actually meet the QoS target specified by a flow; and 2) how well the MBAC can utilize the network resources. The main work in the literature has mostly been on finding optimal MBAC algorithms that increase network utilization. In this simulation study we focus on an MBAC's ability to meet the QoS target under variations in the number of flow attempts within an interval and variations inflow lifetimes. We introduce an ideal admission controller based on analytical values and show the importance of using this ideal when assessing the performance of an MBAC. Most MBAC algorithms rely on tuning parameters to help in the decision making. Tuning these parameters is a difficult task, and a setting that gives excellent performance under one scenario, may give a very pessimistic or too optimistic performance in another scenario. We show that by adding two policies, the so called pessimistic policy together with a back-off policy, the reliance on tuning parameters diminishes. With these two policies in place we show that an MBAC can perform close to the ideal admission controller under various traffic loads without relying on explicit tuning parameters

In the future, communications networks are expected to become less an end itself than a means to an end by exploiting them not only for telecommunications per se but also across other relevant economic sectors in order to reap larger benefits from interdisciplinary research across traditional borders, e.g., an increased overall reduction of greenhouse gas emissions across multiple sectors such as energy and transportation, as envisioned by the future Smart Grid. The two main quality attributes of a Smart Grid communications infrastructure are reliability and latency, as defined in IEEE P2030. This paper proposes to aggregate triple-play and Smart Grid services into a converged fiber-wireless (FiWi) broadband access network based on low cost Ethernet passive optical network (EPON) and wireless mesh networks. We first show that, as the load of the FiWi network increases, performance degradation in terms of packet drop and latency of Smart Grid applications occurs due to the lack of quality-of-service (QoS) protection. To mitigate this problem, we propose an adaptive admission control algorithm to provide QoS support for FiWi Smart Grid communications networks. Simulation results show that the proposed admission control enables QoS guarantees for triple-play applications as well as future Smart Grid applications over the same FiWi infrastructure.

ETXOP: A resource allocation protocol for QoS-sensitive services provisioning in 802.11 networks

An integrated bandwidth allocation and admission control framework for the support of heterogeneous real-time traffic in class-based IP networks

In this paper, we propose an adaptive bandwidth allocation (BA) and connection admission control (CAC) mechanism based on game theory for polling services in IEEE 802.16 broadband wireless networks. A noncooperative two-person general-sum game is formulated where the base station and a new connection are the players of this game. The game formulation provides not only the decision on accepting or rejecting a connection, but also the amount of bandwidth allocated to a new connection (if admitted). A queueing model considering adaptive modulation and coding (AMC) in the physical layer is used to analyze quality of service (QoS) performances, namely, delay and throughput performances, respectively, for real-time and non-real-time polling services. This queueing model is used by the proposed bandwidth allocation and admission control game to ensure that the payoffs for both the base station and the new connection are maximized. The performance of the proposed scheme is evaluated by simulation and compared with that of traditional admission control with static and adaptive bandwidth allocation.

Adaptive call admission control for QoS provisioning in multimedia wireless networks