Call Admission Controller Research Articles

A Load-Balanced Call Admission Controller for IMS Cloud Computing

Network functions virtualization provides opportunities to design, deploy, and manage networking services. It utilizes cloud computing virtualization services that run on high-volume servers, switches, and storage hardware to virtualize network functions. Virtualization techniques can be used in IP multimedia subsystem (IMS) cloud computing to develop different networking functions (e.g., load balancing and call admission control). IMS network signaling happens through session initiation protocol (SIP). An open issue is the control of overload that occurs when an SIP server lacks sufficient CPU and memory resources to process all messages. This paper proposes a virtual load balanced call admission controller (VLB-CAC) for the cloud-hosted SIP servers. VLB-CAC determines the optimal call admission rates and signaling paths for admitted calls along with the optimal allocation of CPU and memory resources of the SIP servers. This optimal solution is derived through a new linear programming model. This model requires some critical information of SIP servers as input. Further, VLB-CAC is equipped with an autoscaler to overcome resource limitations. The proposed scheme is implemented in smart applications on virtual infrastructure (SAVI) which serves as a virtual testbed. An assessment of the numerical and experimental results demonstrates the efficiency of the proposed work.

A Soft Computing Based Adaptive Call Admission Control Scheme for Bi-Class Traffic in CDMA Cellular Network

Soft handoff in CDMA cellular system increases system capacity as compared to hard handoff as interference is reduced by transmitting signals as lower power level. A CDMA cellular system involving voice and data calls is considered in this paper. The model proposed in this paper is for data and voice services (Bi-class). It is based on reservation for handoff voice and data calls along with call queuing scheme for handoff data calls. Preemptive priority scheme is used for handoff voice calls over ongoing data calls. Upper channel limits are set for new voice as well as data calls to give priority to handoff calls. For better resource management and efficient call admission to originating and handoff calls, Neuro-fuzzy call admission controller is designed. This controller uses the adaptable feature of soft handoff threshold parameters to accommodate important voice and data calls. The proposed ASNFC controller is compared with the two variants of Bi-class CAC scheme. General Terms Call Admission Control, Soft Computing

A Comparative Analysis of Queuing and Fuzzy Logic based Admission Control Schemes in CDMA Cellular Network

In CDMA cellular system, the coverage area of the cell is greatly influenced by soft handoff process. The variation in soft handoff coverage area can be taken as the parameter influencing the performance parameters of the CDMA cellular system. This paper is concerned with a comparative analysis of two queuing based call admission control schemes with a fuzzy based CAC (call admission controller) model. The analytical models developed are based on channel reservation scheme for handoff calls. Finite queuing scheme for handoff call is used in first model whereas finite queuing for both handoff as well as new call is considered in the second model. The fuzzy call admission controller is implemented on Mamdani inference scheme taking relative mobility of user and number of reserved channels for handoff calls as input parameters. The output parameter is taken as handoff queue capacity. The fuzzy CAC searches for optimum handoff queue capacity to meet the QoS requirements.

Intelligent Data Rate Control in Cognitive Mobile Heterogeneous Networks

An adaptive rate controller (ARC) based on an adaptive neural fuzzy inference system (ANFIS) is designed to autonomously adjust the data rate of a mobile heterogeneous network to adapt to the changing traffic load and the user speed for multimedia call services. The effect of user speed on the handoff rate is considered. Through simulations, it has been demonstrated that the ANFIS-ARC is able to maintain new call blocking probability and handoff failure probability of the mobile heterogeneous network below a prescribed low level over different user speeds and new call origination rates while optimizing the average throughput. It has also been shown that the mobile cognitive wireless network with the proposed CS-ANFIS-ARC protocol can support more traffic load than neural fuzzy call-admission and rate controller (NFCRC) protocol.

A Self-Learning Call Admission Control Scheme for CDMA Cellular Networks

In the present paper, a call admission control scheme that can learn from the network environment and user behavior is developed for code division multiple access (CDMA) cellular networks that handle both voice and data services. The idea is built upon a novel learning control architecture with only a single module instead of two or three modules in adaptive critic designs (ACDs). The use of adaptive critic approach for call admission control in wireless cellular networks is new. The call admission controller can perform learning in real-time as well as in offline environments and the controller improves its performance as it gains more experience. Another important contribution in the present work is the choice of utility function for the present self-learning control approach which makes the present learning process much more efficient than existing learning control methods. The performance of our algorithm will be shown through computer simulation and compared with existing algorithms.

A Unified Mechanism for Multimedia Downlink Scheduling and Call Admission Control for Future Error-Prone Wireless Networks

In this paper we design and evaluate the performance of a unified mechanism for downlink scheduling and call admission control of multimedia traffic in a high-capacity TDMA wireless channel. In our scheme, the Base Station interacts with the Call Admission Controller and incorporates predictions on the channel condition in its decision making. Our results show that, with the use of the "intelligent" scheduler-admission controller mechanism, system performance is significantly enhanced compared to two other schemes without prediction on the channel condition.

Outage-based fuzzy call admission controller with multiuser detection for WCDMA systems

An outage-based fuzzy call admission controller with multiuser detection (OFCAC–MUD) is proposed for wideband code division multiple access (WCDMA) systems. The OFCAC–MUD determines the new call admission based on the uplink signal-to-interference ratios from home and adjacent cells and system outage probabilities. The OFCAC–MUD possesses both the effective reasoning capability of a fuzzy logic system and the aggressive processing ability of MUD. Simulation results reveal that OFCAC–MUD without power control (PC) improves the system capacity by 70.5% as compared to an SIR-based CAC–RAKE with perfect PC. It also enhances the system capacity by 53.9% as compared to an OFCAC–RAKE with perfect PC, by 6.7% as compared to an SIR-based CAC–MUD without PC and by 12.9% as compared to an OFCAC–MUD with perfect PC, given the same outage probability requirements. Moreover, OFCAC–MUD can prevent the violation of outage probability requirements in the hotspot environment, which is hardly achieved by SIR-based CAC.

Intelligent Call Admission Control for Wideband CDMA Cellular Systems

In this paper, we propose intelligent call admission control for wideband code-division multiple-access (CDMA) cellular systems to support differentiated quality-of-service (QoS) requirements, guarantee the forced termination probability of handoffs, and maximize the spectrum utilization. The intelligent call admission controller (ICAC) contains a fuzzy call admission processor to make admission decision for a call request by considering QoS measures such as the forced termination (drop call) probability of handoff, the outage probability of all service types, the predicted next-step existing-call interference, the link gain, and the estimated equivalent interference of the call request. The pipeline recurrent neural network (PRNN) is used to accurately predict the next-step existing-call interference, and the fuzzy logic theory is applied to estimate the new/handoff call interference based on knowledge of effective bandwidth method. Simulation results indicate that ICAC achieves system capacity higher than conventional CAC schemes by an amount of more than 10% in both low and high moving speed cases. Moreover, ICAC can cope with the unpredictable statistical fluctuation of wireless multimedia traffic; it always fulfill QoS requirements for all service types and keep the forced termination probability satisfied, while the CAC of multimedia calls (MCAC) and SIR-based CAC with intercell interference prediction (PSIR-CAC) fail to adapt to the variation of traffic conditions.

Hierarchical neuro-fuzzy call admission controller for ATM networks

In this work, a hierarchical neuro-fuzzy call admission controller for ATM networks based on the GARIC architecture is proposed. The controller contains a neural network as a critic, using the reinforcement learning scheme, and three fuzzy sub-networks, controlling cell loss ratio, queue size and link utilization in the ATM multiplexer. The final decision of the call admission controller is obtained as a weighted combination of the decisions generated by the fuzzy sub-networks. In order to study the performance of the proposed controller, it is simulated under various variable bit rate traffic patterns and the results obtained are evaluated in terms of network utilization. Introduction of an initial knowledge base to improve training times is discussed and the results with and without the knowledge base are given. Finally, methods to enhance the performance of the proposed controller are mentioned.

Simulation of controlled queuing systems and its application to optimal resource management in multiservice cellular networks

We consider a controlled queuing model and derive the corresponding Markov decision process for simple G/M/1 call admission controller. As an application of the controlled queuing model, we look into an optimal resource management problem arising in the context of multiservice cellular network with reuse partitioning. In particular, we consider a channel borrowing scheme between zones in two-zone reuse partitioning in a two-class cellular network and investigated the performance of various channel borrowing policies via simulation. We also introduce the simulator developed for controlled queuing systems. Most importantly, we demonstrate that Markov decision processes are well suited to this kind of optimization problem.

Design of a real-time call admission controller for ATM networks

In this paper, we present a real-time computation algorithm based on the bufferless fluid flow model [Jabbari and Yegenolu, 1992] for call admission control (CAC) on one link of an asynchronous transfer mode (ATM) network with heterogeneous bursty traffic. Cell loss probability is adopted as the measure of quality-of-service (QoS). Our computation algorithm requires a constant memory size and needs only two multiplications and one division to determine whether a connection request can be accepted or not. It is known [Murase et al., 1991], that due to the interference between different types of traffic the individual cell loss probability may not meet the requirement even though the global one does. In this paper, we provide a close upper-bound for individual cell loss probability which can easily be obtained with our computation algorithm. Numerical examples using typical traffic parameters are studied to corroborate the upper-bound. We also compare the performance of the investigated CAC scheme with that of the effective bandwidth technique [Elwalid and Mitra, 1993].