Optimal Call Admission Control Research Articles

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.

An Optimal Joint Call Admission Control Policy in Heterogeneous Wireless Networks

In heterogeneous wireless networks (HWNs), a scheme called Joint Call Admission Control (JCAC) is demanding for deciding whether or not an incoming service request will be accepted. In this paper, we propose an optimal JCAC policy for HWNs based on semi-Markov decision process (SMDP) to achieve the optimal resource management scheme in terms of minimal the network cost and acquire the required quality of service (QoS) of mobile user. Furthermore, an improved value iteration algorithm with multi-dimensional threshold structure is presented. Numerical results show that the proposed JCAC policy is the overall optimal policy. The proposed algorithm is effective for high QoS performance by reducing the probabilities of dropping and blocking calls. The optimal JCAC policy is ratified by the current trend in the design of next generation wireless networks (NGWNs).

Uniform Fractional Band CAC Scheme for QoS Provisioning in Wireless Networks

Generally, the wireless network provides priority to handover calls instead of new calls to maintain its quality of service (QoS). Because of this QoS provisioning, a call admission control (CAC) scheme is essential for the suitable management of limited radio resources of wireless networks to uphold different factors, such as new call blocking probability, handover call dropping probability, channel utilization, etc. Designing an optimal CAC scheme is still a challenging task due to having a number of considerable factors, such as new call blocking probability, handover call dropping probability, channel utilization, traffic rate, etc. Among existing CAC schemes such as, fixed guard band (FGB), fractional guard channel (FGC), limited fractional channel (LFC), and Uniform Fractional Channel (UFC), the LFC scheme is optimal considering the new call blocking and handover call dropping probability. However, this scheme does not consider channel utilization. In this paper, a CAC scheme, which is termed by a uniform fractional band (UFB) to overcome the limitations of existing schemes, is proposed. This scheme is oriented by priority and non-priority guard channels with a set of fractional channels instead of fractionizing the total channels like FGC and UFC schemes. These fractional channels in the UFB scheme accept new calls with a predefined uniform acceptance factor and assist the network in utilizing more channels. The mathematical models, operational benefits, and the limitations of existing CAC schemes are also discussed. Subsequently, we prepared a comparative study between the existing and proposed scheme in terms of the aforementioned QoS related factors. The numerical results we have obtained so far show that the proposed UFB scheme is an optimal CAC scheme in terms of QoS and resource utilization as compared to the existing schemes.

An Optimal Admission Control Protocol for Heterogeneous Multicast Streaming Services

We investigate optimal call admission control (CAC) policy for multicast streaming services (MSS) in 3rd generation (3G) and beyond wireless mobile networks. Several MSS sessions are supported simultaneously in a bandwidth-limited network. Active sessions are those that are currently serving some users, and inactive sessions are those that are currently not serving any users. An admission decision in MSS is required only when an inactive session is requested, unlike in unicasting. For this reason, if a user request for an inactive MSS session arrives, we should make an admission decision in anticipation of ( i ) the possible reward earned based on users served during a session active time generated by accepting it, and ( ii ) the influence of the session active time upon the future status of network bandwidth and admission decisions. Our objective is to determine when to admit or block a user asking an inactive MSS session to achieve the optimality in rewards. We formulate this problem as a semi-Markov decision process (SMDP), and a value iteration algorithm is used to obtain an optimal stationary deterministic policy. We also derive the user blocking probability of the optimal policy by analyzing an embedded Markov chain induced by it.

Dynamic spectrum access based on interruptible spectrum leasing

Dynamic spectrum access (DSA) based on interruptible spectrum leasing allows secondary users (SUs) to lease a licensed, but idle, spectrum that is owned by primary users (PUs) on condition that the PUs preempt the access to the leased spectrum. This paper considers a DSA scenario where the SUs opportunistically use the primary spectrum in addition to their own band and the PUs use their own band regardless of the opportunistic access. This operating scenario can contribute to leverage the spectrum utilization by exploiting underutilized spectrum resources, but involves a problem that the SUs may be forced to interrupt on-going services in response to the PUs' reclamation of the leased spectrum. In this paper, we address the optimal call admission control (CAC) problem in order to coordinate the DSA based on interruptible spectrum leasing by considering the tradeoff between the additional spectrum use and the penalty on the service interruption. To this end, we adopt the profit of the secondary wireless service provider as a cost function of the CAC policy in a market mechanism manner. The optimization problem is modeled as a profit maximization problem, and a linear programming (LP) formulation of the semi-Markov decision process approach is provided. Through the simulation results, we analyze the LP solution of the optimal CAC for the leasing based DSA and demonstrate that the proposed CAC policy judiciously uses the access opportunities of the SUs considering the service interruption.

Optimal Priority-based Call Admission Control Scheme For QoS Provisioning in Heterogeneous Wireless Networks

Next generation wireless networks will support a diverse set of access technologies. And the demanding breed of multimedia applications will even more considerably require Quality of Service (QoS) support. This paper proposes an optimal prority-based Call Admission Control (CAC) scheme in heterogeneous wireless networks, i.e., the generalized semi-Markov Decision Process based CAC (GCAC). Considering the limitations of the traditional Markov decision process for optimal CAC policy, we characterize the CAC problem through a GSMDP formulation that characterize s the network behaviors in the heterogeneous system more exactly. And the proposed scheme can guarantee the QoS constrains both in the physical and network layer. Numerical examples illustrate that the performance in the GCAC scheme is significantly better than that in the conventioinal GC scheme and an optimal CAC schme based on MDP.

A tabu search heuristic for bandwidth allocation in fixed WiMAX

In this paper, we propose a mathematical model with the aim to give guidelines for the dimensioning of fixed WiMAX bandwidth provisioning service to residential customers. Our proposal relies on the modeling of a CAC policy associated to a priority-based bandwidth sharing strategy. Both mechanisms aim to satisfy Quality of Service constraints while maximizing the gain of the system. But unlike in Khemiri et al. (Optimal call admission control for an IEEE 802.16 wireless metropolitan area network. In: International Conference on Network Control and Optimization, 2007, accepted), we do not necessarily seek here for an optimal CAC policy. We rather consider a coordinate convex CAC policy, whose mathematical modeling leads to a tractable analytical resolution. We chose the Guaranteed Minima (GM) policy, which consists in reserving a specified amount of bandwidth for each traffic class. The remaining bandwidth is shared between all traffic classes. The purpose of the paper is to determine, using an analytical model and a heuristic approach, the nearly-optimal sizes of the GM reservation thresholds associated to each type of connection. The main concern here is to propose simple and robust computational methods, which can be easily and efficiently used to dimension a realistic WiMAX network.

Determination of optimal call admission control policy in wireless networks

This paper investigates the optimal call admission control (CAC) policy for non-priority scheme (NPS) and reserved channel scheme (RCS) in wireless networks, respectively. Both new call and handoff call arrival processes are assumed to be Poisson processes, and the call holding times are exponentially distributed with different rate for new call and handoff calls. Admitting each call would bring a reward to the network provider but holding each call in the system would also incur some expenses (or cost) to the provider. We concentrate on the optimization problems of when to admit or reject a call in order to achieve the maximum total expected discounted reward. By establishing a discounted semi Markov decision process (SMDP) model, we verify that the optimal policies are state-related control limit policies for both NPS and RCS. Our numerical results explained in both tables and diagrams are consistent with our theoretic results.

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.

Optimal Call Admission and Call Dropping Control in Links with Variable Capacity

This paper defines a theoretical framework based on Markov Decision Processes (MDPs) to deal with call control algorithms in links with variable capacity supporting multiple classes of service. The variable capacity problem, which arises in wireless network scenarios, is addressed by incorporating the link model into the MDP formulation and by introducing, besides the standard call admission policy, a call dropping policy. In this way, the proposed approach is capable of controlling class-level quality of service in terms of both blocking and dropping probabilities. Numerical simulations show the effectiveness of the approach.

Guard-Channel-Based Incremental and Dynamic Optimization on Call Admission Control for Next-Generation QoS-Aware Heterogeneous Systems

Next-generation communication systems are expected to be highly integrated heterogeneous networking environments. Supporting multimedia services with different quality-of-service (QoS) requirements over such highly heterogeneous environments is a very challenging task, and a unified call admission control (CAC) optimization mechanism is needed to allow resources to be efficiently utilized. In this paper, we propose an optimal CAC mechanism, i.e., the guard-channel-based incremental and dynamic optimization (GUIDO), which is a threshold-based CAC scheme that is designed based on the Markov decision process (MDP) and sensitivity analysis (SA) techniques. The MDP is used to derive the optimal CAC policy for predetermined goals, whereas the use of SA can greatly reduce the effort of unnecessary recomputation of the CAC policy when the traffic condition varies. Through the use of system capacity estimation and QoS mapping techniques, GUIDO allows the CAC operation to be performed in a general framework, even with various underlying communication systems and different access/core networks. GUIDO can be implemented dynamically (online optimization) and statically (lookup table). Homogeneous and heterogeneous systems with multiple service priority classes are studied in this paper. We have considered comprehensive objective functions, and each characterizes a different interest of the service provider. The performance is evaluated via an event-driven simulator, and the results are compared with those of the complete sharing scheme and conventional guard channel schemes under constant call-arrival rates as well as time-varying call-arrival-rate traffic scenarios.

A Linear Programming Approach to Cross-Layer Optimization in Multiclass VSG-CDMA Over Rayleigh Fading

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper presents a new linear programming approach for throughput maximization on the uplink of a multiclass variable spreading gain code-division multiple-access (CDMA) multicellular system in Rayleigh fading for both binary phase-shift keying (BPSK) and quaternary phase-shift keying (QPSK) modulations. Based on the improved Gaussian approximation technique, we derive exact closed-form expressions of the outage probability, which are used as a physical (PHY) layer constraint of the maximization problem. We show that it is possible to transform the nonlinear constraint into a set of equivalent linear expressions. This facilitates the formulation of a new linear throughput maximization that noticeably requires less computational complexity than the known nonlinear approaches. Furthermore, due to the simplicity of the linear approach, we can include the constraints of such higher layers, i.e., media access control (MAC) and call admission control (CAC) layers, into the proposed formula. Accordingly, we introduce two linear programming optimization formulas. One is for MAC-PHY optimization, and another is for cross-layer optimal CAC policy. In the case of MAC-PHY optimization, the throughput is maximized, at low background noise level, when every user retains the same bit energy, particularly in the case where the difference in data rates is high. Nonetheless, at high levels of background noise, the throughput would be maximized when a larger amount of bit energy is allocated to the high-rate users. For the joint optimal policy, the throughput and the blocking probability are optimized and improved up to 50% in comparison to those of the conventional CAC policy, which is known as the <emphasis emphasistype="boldital">complete sharing</emphasis> policy. </para>

Dual-threshold admission control for non-real-time traffic in wireless data networks

Non-real-time services are an important category of network services in future wireless networks. When mobile users access non-real-time services, mobile users are usually concerned with the total time to complete their data transfer. In addition, system providers expect that channel utilization should be as high as possible because radio channels are limited. Therefore, it is crucial to design a system that satisfies the total completion time requirement of mobile users while maximizes channel utilization. In this paper, we design an optimal call admission control scheme that uses two thresholds; one threshold is used to determine whether or not to accept a new call arrival into a cell, and the other threshold is used to limit the total number of calls in a cell. An analysis is developed to evaluate the performance of the proposed call admission control scheme. Numerical results show that the proposed scheme not only satisfies mobile users’ quality-of-service requirements (in terms of the total completion time and hand-off dropping probability) but also maximizes channel utilization.

Computationally Efficient Dynamic Code Assignment Schemes With Call Admission Control (DCA-CAC) for OVSF-CDMA Systems

This paper investigates computationally efficient suboptimal dynamic code assignment (DCA) schemes with call admission control (CAC) for orthogonal variable spreading factor code-division multiple-access systems. We examine two different approaches. The first approach reduces the complexity of the DCA scheme by partitioning the total resource (either capacity or service class) into several mutually exclusive subsets and assigns each subset of resource to a group of users in proportion to the corresponding traffic load. The second approach reduces the complexity of the optimal CAC scheme with the Markov decision process over an infinite time horizon by a suboptimal CAC policy, which is designed by observing the behavior of system dynamics over only two consecutive stages upon the arrival of a call. It is demonstrated by numerical evaluation that the proposed schemes achieve an average data throughput close to that of the optimal DCA-CAC performance while demanding a much lower computational complexity in their design and implementation.

Efficient Structured Policies for Admission Control in Heterogeneous Wireless Networks

In the near future, demand for heterogeneous wireless networking (HWN) is expected to increase. QoS provisioning in these networks is a challenging issue considering the diversity in wireless networking technologies and the existence of mobile users with different communication requirements. In HWNs with their increased complexity, “the curse of dimensionality” problem makes it impractical to directly apply the decision theoretic optimal control methods that are previously used in homogeneous wireless networks to achieve desired QoS levels. In this paper, optimal call admission control policies for HWNs are considered. A decision theoretic framework for the problem is derived by a dynamic programming formulation. We prove that for a two-tier wireless network architecture, the optimal policy has a two-dimensional threshold structure. Further, this structural result is used to design two computationally efficient algorithms, Structured Value Iteration and Structured Update Value Iteration. These algorithms can be used to determine the optimal policy in terms of thresholds. Although the first one is closer in its operation to the conventional Value Iteration algorithm, the second one has a significantly lower complexity. Extensive numerical observations suggest that, for all practical parameter sets, the algorithms always converge to the overall optimal policy. Further, the numerical results show that the proposed algorithms are efficient in terms of time-complexity and in achieving the optimal performance.

Optimal and Structured Call Admission Control Policies for Resource-Sharing Systems

Many communication and networking systems can be modeled as resource-sharing systems with multiple classes of calls. Call admission control (CAC) is an essential component of such systems. Markov decision process (MDP) tools can be applied to analyze and compute the optimal CAC policy that optimizes certain performance metrics of the system. But for most practical systems, it is prohibitively difficult to compute the optimal CAC policy using any MDP algorithm because of the "curse of dimensionality". We are, therefore, motivated to consider two families of structured CAC policies: reservation and threshold policies. These policies are easy to implement and have good performance in practice. However, since the number of structured policies grows exponentially with the number of call classes and the capacity of the system, finding the optimal structured policy is a complex unsolved problem. In this paper, we develop fast and efficient search algorithms to determine the parameters of the structured policies. We prove the convergence of the algorithms. Through extensive numerical experiments, we show that the search algorithms converge quickly and work for systems with large capacity and many call classes. In addition, the returned structured policies have optimal or near-optimal performance, and outperform those structured policies with parameters chosen based on simple heuristics

Optimal call admission control with QoS guarantee in a voice/data integrated cellular network

This paper addresses the issue of call admission control with the necessary quality-of-service (QoS) guarantee for an integrated service mobile cellular network. Specifically, we extend the limited fractional guarded channel (LFGC) scheme to incorporate the multiple traffic types, and derive the set of parameters that leads to the optimal call admission control. The key challenges are the state-dependent nature of the admission control, and the increasing complexity of the state space in a multi-services environment. We propose a novel control mechanism that only uses a few parameters (2-5) to characterize the optimal control planes, and use the simulated annealing technique to obtain the optimal control parameters.

Optimal Resource Allocation and Adaptive Call Admission Control for Voice/Data Integrated Cellular Networks

Resource allocation and call admission control (CAC) are key management functions in future cellular networks, in order to provide multimedia applications to mobiles users with quality of service (QoS) guarantees and efficient resource utilization. In this paper, we propose and analyze a priority based resource sharing scheme for voice/data integrated cellular networks. The unique features of the proposed scheme are that 1) the maximum resource utilization can be achieved, since all the leftover capacity after serving the high priority voice traffic can be utilized by the data traffic; 2) a Markovian model for the proposed scheme is established, which takes account of the complex interaction of voice and data traffic sharing the total resources; 3) optimal CAC parameters for both voice and data calls are determined, from the perspective of minimizing resource requirement and maximizing new call admission rate, respectively; 4) load adaption and bandwidth allocation adjustment policies are proposed for adaptive CAC to cope with traffic load variations in a wireless mobile environment. Numerical results demonstrate that the proposed CAC scheme is able to simultaneously provide satisfactory QoS to both voice and data users and maintain a relatively high resource utilization in a dynamic traffic load environment. The recent measurement-based modeling shows that the Internet data file size follows a lognormal distribution, instead of the exponential distribution used in our analysis. We use computer simulations to demonstrate that the impact of the lognormal distribution can be compensated for by conservatively applying the Markovian analysis results.

A connection-level call admission control using genetic algorithm for multi-class multimedia services in wireless networks

Semi-Markov Decision Process (SMDP) can be used to optimise channel utilisation with upper bounds on handoff blocking probabilities as Quality of Service constraints for call admission control in a wireless cell in a Personal Communication System (PCS). However, this method is too time consuming and therefore it fails when state space and action space are large. In this paper, we apply a genetic algorithm approach to address the situation when the SMDP approach fails. We code call admission control decisions as binary strings. The coded binary strings are fed into the genetic algorithm, and the resulting binary strings are founded to be near optimal call admission control decisions. Simulation results from the genetic algorithm are compared with the optimal solutions obtained from linear programming for the SMDP approach. The results reveal that the genetic algorithm approximates the optimal approach very well with less complexity.

A call admission control for service differentiation and fairness management in WDM grooming networks

We investigate a call admission control (CAC) mechanism for providing fairness control and service differentiation in a WDM network with grooming capabilities. A WDM grooming network can handle different classes of traffic streams which differ in their bandwidth requirements. We assume that for each class, call interarrival and holding times are exponentially distributed. Using a Markov Decision Process approach, an optimal CAC policy is derived for providing fairness in the network. The Policy Iteration algorithm is used to numerically compute the optimal policy. Furthermore, we propose a heuristic decomposition algorithm with lower computational complexity and good performance. Simulation results compare the performance of our proposed policy with those of Complete Sharing and Complete Partitioning policies. Comparisons show that our proposed policy provides the best performance in most cases. Although this approach is motivated by WDM networks, it may be deployed to determine the optimal resource allocation in many problems in wireless and wired telecommunications systems.