Dynamic Call Admission Control Research Articles

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English

An optimum dynamic priority-based call admission control scheme for universal mobile telecommunications system

The dynamism associated with quality of service (QoS) requirement for traffic emanating from smarter end users devices founded on the internet of things (IoTs) drive, places a huge demand on modern telecommunication infrastructure. Most telecom networks, currently utilize robust call admission control (CAC) policies to ameliorate this challenge. However, the need for smarter CAC has becomes imperative owing to the sensitivity of traffic currently being supported. In this work, we developed a prioritized CAC algorithm for third Generation (3G) wireless cellular network. Based on the dynamic priority CAC (DP-CAC) model, we proposed an optimal dynamic priority CAC (ODP-CAC) scheme for Universal Mobile Telecommunication System (UMTS). We then carried out simulation under heavy traffic load while also exploiting renegotiation among different call traffic classes. Also, we introduced queuing techniques to enhance the new calls success probability while still maintaining a good handoff failure across the network. Results show that ODP-CAC provides an improved performance with regards to the probability of call drop for new calls, network load utilization and grade of service with average percentage value of 15.7%, 5.4% and 0.35% respectively.

Congestion Control Call Admission Control (CC-CAC) Algorithm for Mobile Broadband Networks

Mobile broadband networks are continuously faced with the challenge of limited resources due to the increasing demand for high speed Internet services. To manage these resources, call admission control (CAC) which determines whether or not a connection request should be accepted or rejected is one of the resource management techniques usually deployed. A Dynamic QoS-aware CAC algorithm was recently proposed to improve resource utilization. However, the algorithm detects congestion of the network only after it has occurred, which leads to increase in blocking probability and thus lead to reduction in throughput. In this paper, a congestion control call admission control (CC-CAC) algorithm is proposed to reduce call blocking and increase throughput of all connection classes. The CC-CAC employs a congestion control mechanism that regulates the base station buffer to operate at a target threshold. It also employs a dynamic bandwidth degradation mechanism to degrade the resources of the admitted connections when resources are not sufficient to admit more connections. The algorithm is evaluated using simulation. The results show that the proposed scheme outperforms the benchmark scheme in terms of decrease in blocking probability and increase in throughput for all connection classes.

A QoS Guaranteed Call Admission Control (QOG-CAC) Algorithm for Broadband Networks

Call admission control (CAC) is one of the techniques deployed in managing network resources. Recently, the dynamic QoSaware CAC (DQA-CAC) algorithm was proposed to reduce the new connection blocking rate and improve resource utilization. However, the algorithm admits new connections and degrades existing ones without recourse to delay requirements of delay-intolerant extended real-time polling service (ertPS) and real-time polling service (rtPS) connections—which may incur additional delay, leading to an increase in packet drop rate and, consequently, reduced throughput. In this article, a QoS-guaranteed call admission control (QOG-CAC) algorithm is proposed to ensure QoS and consequently increase the throughput of all class of connections. The proposed QOG-CAC is simulated using a Java-based discrete event simulator. The results of the extensive simulation experiments conducted show that the proposed algorithm outperforms the compared scheme with regard to average system throughput, new connection blocking rate, and per-flow throughput of real-time as well as non-real-time connections

A cross layer framework of Radio Resource Allocation for QoS provisioning in multi-channel fading wireless networks

In this paper, we present an analytical framework for the performance evaluation of Radio Resource Allocation (RRA) in Orthogonal Frequency Division Multiple Access (OFDMA) networks. We focus on Quality of Service (QoS) guaranteed traffic whose capacity, in terms of the number of active user connections, depends on the users’ QoS requirements and channel conditions, and the RRA algorithm. The required QoS is guaranteed by restricting the number of admitted calls, which in turn requires an accurate estimate of the QoS metrics and capacity supported by the RRA when a new call arrives. These estimates for OFDMA networks are variable and usually obtained through time-consuming offline computer simulations. Mathematical frameworks on the other hand yield timely and accurate results. However, earlier known works on analytical modelling of RRA either consider a single channel with random traffic arrivals or multiple channels with full buffer data traffic. In contrast, we develop a queueing theoretic framework considering randomly arriving QoS-guaranteed traffic in a variable-rate multi-channel multi-class OFDMA network. The framework can be used online leading to better dynamic Call Admission Control. We characterize the RRA algorithm using a scheduler control parameter which can regulate the call blocking probability while providing predefined QoS constraints. We model the RRA as a variable service rate, multi-server, multi-class, finite buffer queueing system and verify the derived QoS metrics using extensive Monte-Carlo discrete event simulations.

A QoS-Aware CAC with Bandwidth Reservation and Degradation Scheme in IEEE 802.16e Networks

Call admission control (CAC) schemes play a critical role in providing quality-of-service (QoS) guarantees for various classes of traffic with diverse QoS requirements in IEEE 802.16e networks. The dynamic CAC and bandwidth reservation scheme is one of the current schemes that simultaneously provides efficient utilization of network resources and guarantees QoS for admitted connections. However, its admission criteria starved high and low service classes due to its linear adaptation policy to accommodate more users into the network under moderate-to-heavy traffic load conditions. Its adaptive threshold for handoff connections is adjusted based on the arrival of new and handoff connections, that results in a waste of resources when the new and handoff connection arrival rate occurs frequently. In this paper, a new CAC scheme for Mobile WiMAX networks is proposed to prevent starvation of service classes and enhance the efficient utilization of network resources. The scheme determines a new admission criteria based on a scheduling service class. In the admission criteria, bandwidth degradation policy is used to admit more users when there is no available bandwidth to admit a more users. The adaptive threshold has been introduced dynamically to adjust the quantity of reserved bandwidth for handoff connections based on the traffic intensity of handoff requests. In addition, an analytical model for the proposed scheme is also developed. Extensive simulation experiments have been conducted to evaluate the performance of our proposed approach. The simulation results illustrate that the proposed scheme significantly improves the network efficiency compared to other schemes in terms of accepting more connections into the network and assuring QoS for all service classes. The numerical results have shown similar performance to the simulation results.

A Dynamical Hybrid CAC Scheme and Its Performance Analysis for Mobile Cellular Network with Multi-Service

Call admission control (CAC) plays an important role in mobile cellular network to guarantee the quality of service (QoS). In this paper, a dynamic hybrid CAC scheme with integrated cutoff priority and handoff queue for mobile cellular network is proposed and some performance metrics are derived. The unique characteristic of the proposed CAC scheme is that it can support any number of service types and that the cutoff thresholds for handoff calls are dynamically adjusted according to the number of service types and service priority index. Moreover, timeouts of handoff calls in queues are also considered in our scheme. By modeling the proposed CAC scheme with a one-dimensional Markov chain (1DMC), some performance metrics are derived, which include new call blocking probability ( P nb ) , forced termination probability (PF), average queue length, average waiting time in queue, offered traffic utilization, wireless channel utilization and system performance which is defined as the ratio of channel utilization to Grade of Service (GoS) cost function. In order to validate the correctness of the derived analytical performance metrics, simulation is performed. It is shown that simulation results match closely with the derived analytic results in terms of Pnb and PF. And then, to show the advantage of 1DMC modeling for the performance analysis of our proposed CAC scheme, the computing complexity of multi-dimensional Markov chain (MDMC) modeling in performance analysis is analyzed in detail. It is indicated that state-space cardinality, which reflects the computing complexity of MDMC, increases exponentially with the number of service types and total channels in a cell. However, the state-space cardinality of our 1DMC model for performance analysis is unrelated to the number of service types and is determined by total number of channels and queue capacity of the highest priority service in a cell. At last, the performance comparison between our CAC scheme and Mahmoud ASH’s scheme is carried out. The results show that our CAC scheme performs well to some extend.

Performance evaluation of priority based adaptive multiguard channel call admission control for multiclass services in mobile networks

SUMMARYThe CAC (call admission control), which can guarantee call services to meet their QoS (Quality of Service) requirements, plays a significant role in providing QoS in wireless mobile networks. In this paper, an adaptive multiguard channel scheme‐based CAC strategy is proposed to prioritize traffic types and handoff calls. The major aim of the study is to develop the analytical model of the priority traffic and handoff calls based adaptive multiguard channel scheme and examining the performance through setting the value of the adaptive ratio parameters. Our proposed scheme tries to mediate the advantages and drawbacks of the static and dynamic CAC schemes. The proposed scheme is quite different from previous studies because multithreshold values have been considered for multiclass traffic by adaption parameters, and a closed form analytical model is developed The numerical results show that this scheme can be used to keep the targeted QoS requirement by suitably setting the adaptive ratio parameters. Copyright © 2011 John Wiley & Sons, Ltd.

Dynamic Preemption Call Admission Control Scheme Based on Markov Decision Process in Traffic Groomed Optical Networks

In optical grooming networks, the capacity fairness issue can be resolved by utilizing a call admission control (CAC) mechanism. Existing CAC schemes are generally based on one of four different techniques, namely, static bandwidth reservation, static threshold setting, mathematical statistics, and Markov decision processing without buffer implementation (NB). However, irrespective of the technique used, a trade-off exists between the network fairness and the network throughput. In our previous work, a conditional-preemption CAC (CP-CAC) mechanism was proposed to increase the network throughput while simultaneously maintaining the fairness. However, a CP-CAC mechanism considers only the blocking probability at particular instants of preemption. This paper proposes the use of a dynamic-preemption call admission control scheme (DP-CAC) to decide whether or not to preempt existing requests based on the optimal policy derived from a Markov decision process. Similar to CP-CAC, the DP-CAC method is also based on a dynamic threshold setting concept and is implemented using a single connection buffer and an associated set of virtual indicators. The simulation results show that compared to the CP-CAC mechanism, the proposed DP-CAC further improves the network throughput without sacrificing the fairness. Additionally, the average waiting time induced by the buffer implementation for DP-CAC is just 0.23 time units shorter compared to 0.25 for CP-CAC. Finally, it is shown that the proposed method also ensures fairness in a variety of common network topologies including 6 × 6mesh-torus, NSF, and Cost239.

Using traffic prediction and estimation of provider revenue for a joint GEO satellite MAC/CAC scheme

Satellite networks present an attractive solution in providing worldwide access to the present and future generation multimedia communication services. However, the burstiness of multimedia traffic and the long propagation delays in Geostationary (GEO) satellite systems call for an efficient Medium Access Control (MAC) protocol and an equally efficient Call Admission Control (CAC) scheme, in order to provide acceptable Quality of Service (QoS) to multimedia users. This paper proposes a fair and dynamic CAC and MAC framework, named Fair Predictive Resource Reservation Access (FPRRA), which is based on accurate videoconference traffic prediction and makes decisions after taking into account the provider revenue. The framework's performance is evaluated in comparison to other efficient schemes from the literature.

A novel dynamic call admission control policy for wireless network

To address the issue of resource scarcity in wireless communication, a novel dynamic call admission control scheme for wireless mobile network was proposed. The scheme established a reward computing model of call admission of wireless cell based on Markov decision process, dynamically optimized call admission process according to the principle of maximizing the average system rewards. Extensive simulations were conducted to examine the performance of the model by comparing with other policies in terms of new call blocking probability, handoff call dropping probability and resource utilization rate. Experimental results show that the proposed scheme can achieve better adaptability to changes in traffic conditions than existing protocols. Under high call traffic load, handoff call dropping probability and new call blocking probability can be reduced by about 8%, and resource utilization rate can be improved by 2%–6%. The proposed scheme can achieve high source utilization rate of about 85%.

Policy Gradient SMDP for Resource Allocation and Routing in Integrated Services Networks

In this paper, we solve the call admission control (CAC) and routing problem in an integrated network that handles several classes of calls of different values and with different resource requirements. The problem of maximizing the average reward (or cost) of admitted calls per unit time is naturally formulated as a semi-Markov Decision Process (SMDP) problem, but is too complex to allow for an exact solution. Thus in this paper, a policy gradient algorithm, together with a decomposition approach, is proposed to find the dynamic (state-dependent) optimal CAC and routing policy among a parameterized policy space. To implement that gradient algorithm, we approximate the gradient of the average reward. Then, we present a simulation-based algorithm to estimate the approximate gradient of the average reward (called GSMDP algorithm), using only a single sample path of the underlying Markov chain for the SMDP of CAC and routing problem. The algorithm enhances performance in terms of convergence speed, rejection probability, robustness to the changing arrival statistics and an overall received average revenue. The experimental simulations will compare our method's performance with other existing methods and show the robustness of our method.

Dynamic Call Admission Control Scheme Based on Predictive User Mobility Behavior for Cellular Networks

In this paper, we propose a modified scheme of MSODB and PMS, called Predictive User Mobility Behavior (PUMB) to improve performance of resource reservation and call admission control for cellular networks. This algorithm is proposed in which bandwidth is allocated more efficiently to neighboring cells by key mobility parameters in order to provide QoS guarantees for transferring traffic. The probability is used to form a cluster of cells and the shadow cluster, where a mobile unit is likely to visit. When a mobile unit may change the direction and migrate to the cell that does not belong to its shadow cluster, we can support it by making efficient use of predicted nonconforming call. Concomitantly, to ensure continuity of on-going calls with better utilization of resources, bandwidth is borrowed from predicted nonconforming calls and existing adaptive calls without affecting the minimum QoS guarantees. The performance of the PUMB is demonstrated by simulation results in terms of new call blocking probability, handoff call dropping probability, bandwidth utilization, call successful probability, and overhead message transmission when arrival rate and speed of mobile units are varied. Our results show that PUMB provides the better performances comparing with those of MSODB and PMS under different traffic conditions.

Efficient Methods for Performance Evaluations of Call Admission Control Schemes in Multi-Service Cellular Networks

Many dynamic call admission control (CAC) schemes have been proposed in the literature for adaptive reservations in cellular networks. Efficient application of these schemes requires reliable and up-to-date feedback of system performance to the CAC mechanism. However, exact analyses of these schemes in real time using multi-dimensional Markov chain models are challenging due to the need to solve large sets of flow equations. One dimensional Markov chain models have been widely used to derive performance metrics such as call blocking probabilities of multiple traffic classes assuming that all classes of calls have equal capacity requirements and exponentially distributed channel holding times with equal mean values. These assumptions need to be relaxed for a more general evaluation of CAC performance in multi-service cellular networks. In this paper we classify CAC schemes according to their Markov chain models into two categories: symmetric and asymmetric, and develop computationally efficient analytical methods to compute call blocking probabilities of various traffic classes for several widely known CAC schemes under relaxed assumptions. We obtain a product form solution to evaluate symmetric schemes and propose a novel performance evaluation approximation method with low computational cost for asymmetric schemes. Numerical results demonstrate the accuracy and efficiency of the proposed method.

Dynamic Multiple-Threshold Call Admission Control Based on Optimized Genetic Algorithm in Wireless/Mobile Networks

Due to the dynamics of topology and resources, Call Admission Control (CAC) plays a significant role for increasing resource utilization ratio and guaranteeing users' QoS requirements in wireless/mobile networks. In this paper, a dynamic multi-threshold CAC scheme is proposed to serve multi-class service in a wireless/mobile network. The thresholds are renewed at the beginning of each time interval to react to the changing mobility rate and network load. To find suitable thresholds, a reward-penalty model is designed, which provides different priorities between different service classes and call types through different reward/penalty policies according to network load and average call arrival rate. To speed up the running time of CAC, an Optimized Genetic Algorithm (OGA) is presented, whose components such as encoding, population initialization, fitness function and mutation etc., are all optimized in terms of the traits of the CAC problem. The simulation demonstrates that the proposed CAC scheme outperforms the similar schemes, which means the optimization is realized. Finally, the simulation shows the efficiency of OGA.

Dynamic Call Admission Control for Uplink in 3G/4G CDMA-Based Systems

Call admission control (CAC) strongly influences the performance of 3G/4G spread spectrum systems because it determines the number of active users that are admitted to the network, i.e., influences spectral efficiency. A novel air interface CAC algorithm is introduced in this paper. It optimizes the utilization of radio resources and provides real-time adaptation to the radio channel with generalized multiplicative fading. Users are handled as memory-less traffic sources. The suggested CAC method was evaluated for lognormal fading and on/off traffic.

Adaptive Call Admission Control Based on Reward-Penalty Model in Wireless/Mobile Network

A dynamic threshold-based Call Admission Control (CAC) scheme used in wireless/mobile network for multi-class services is proposed. In the scheme, each class's CAC thresholds are solved through establishing a reward-penalty model which strives to maximize network's revenue. In order to lower Handoff Dropping Probability (HDP), the scheme joints packet and connection levels Quality of Service constraints, designing a bandwidth degradation algorithm to accept handoff calls by degrading existing calls' bandwidth during network congestion. Analyses show that the CAC thresholds change adaptively with the average call arrival rate. The performance comparison shows that the proposed scheme outperforms the Mobile IP Reservation scheme.

An Adaptive CAC Scheme for Wideband Cellular Networks

An adaptive tri-threshold dynamic call admission control scheme for wideband mobile cellular networks is proposed. The relationship between the Channel Utilization and the Weighted Handover Dropping Probability versus traffic loadings are investigated. This scheme supports voice, data and multimedia services with differentiated QoS.

Robust dynamic Call Admission Control framework for prioritised multimedia traffic in wireless cellular networks

Next generation wireless cellular networks aim at supporting Wireless Multimedia Services (WMSs) with different classes of traffic characterised by diverse Quality of Service (QoS) and bandwidth requirements. They will use micro/pico cellular architectures in order to provide higher capacity. However, small-size cells increase the handoff rate drastically. As a result, it is a challenge to provide stable QoS in these networks. This paper introduces a novel QoS Adaptive Call Admission Control (QoS-AdCAC) framework for next generation broadband wireless cellular networks supporting WMSs with different classes of traffic and diverse bandwidth requirements. In this work, each base station locally, independently of other Base Stations (BSs) in the network, differentiates between new and handoff calls for each class of traffic by assigning a threshold to each class according to its QoS requirements. The threshold values change dynamically in order to respond to the varying traffic conditions. The main feature of the proposed framework is its ability to simultaneously achieve several design goals, which makes it suitable for real time execution. Simulation results show the strength of our proposed framework.

Dynamic Call Admission Control for Centralized CDMA Systems

Spectral efficiency of WCDMA based spread spectrum 3G/4G air interface technology is highly influenced by the common channel interference, hence the applied Call Admission Control method has great importance because it determines the number of active users admitted to the network. In this paper we present a dynamic air interface CAC algorithm which provides efficient usage of radio resources and allows real-time adaptation to the always changing network parameters. Required CAC parameters are derived for generalized multiplicative fading and generalized memory-less traffic sources. In order to validate its capabilities our proposed CAC method was investigated with ON/OFF traffic sources and lognormal fading channels.