On optimal call admission control in resource-sharing system

In this paper, we consider call admission control of multiple classes without waiting room. We use event-based dynamic programming for our model. We show that sometimes the customer classes can be ordered: if it is optimal to accept a class, then to accept a more profitable class is optimal too. We demonstrate submodularity of the minimum cost for the 2-classes problem and establish some properties of optimal policies. Then we formulate a fluid model that allows us to study the optimal control for the large-capacity case. We show that in the case of same service time distributions, the control problem can be reduced to a model with a one-dimensional (1-D) state space, and a trunk reservation policy is optimal. We present numerical examples that validate our results     

Genetic algorithms applied to cellular call admission: localpolicies

It is well known that if a stochastic service system (such as a cellular network) is shared by users with different characteristics (such as differing handoff rates or call holding times), the overall system performance can be improved by denial of service requests even when the success capacity exists. Such selective denial of service based on the system state is defined as the call admission. A previous paper suggested the use of genetic algorithms (GAs) to find near-optimal call admission policies for cellular networks. In this paper, we define local call admission policies that make admission decisions based on partial state information. We search for the best local call admission policies for one-dimensional (1-D) cellular networks using genetic algorithms and show that the performance of the best local policies is comparable to optima for small systems. We test our algorithm on larger systems and show that the local policies found outperform the maximum packing and best handoff reservation policies for the systems we have considered. We find that the local policies suggested by the genetic algorithm search in these cases are double threshold policies. We then find the best double threshold policies by exhaustive search for both 1-D and Manhattan model cellular networks and show that they almost always outperform the best trunk reservation policies for these systems     

Fairness in network optimal flow control: optimality of productforms

Consideration is given to the problem of optimal flow control in a multiclass telecommunications environment where each user (or class) desires to optimize its performance while being fair to the other users (classes). The Nash (1950) arbitration scheme from game theory is shown to be a suitable candidate for a fair, optimal operation point in the sense that it satisfies certain axioms of fairness and is pareto optimal. This strategy can be realized by defining the product of individuals user performance objectives as the network optimization criterion. This provides the rationale for considering the product of user powers, as has been suggested in the literature. For delay constrained traffic, the constrained optimization problem of maximizing the product of user throughputs subject to the constraints leads to a Nash arbitration point. It is shown that these points are unique in throughput space, and the authors also obtain some convexity properties for power and delays with respect to throughputs in a Jackson network     

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     

A game theoretic framework for bandwidth allocation and pricing inbroadband networks

In this paper, we present a game theoretic framework for bandwidth allocation for elastic services in high-speed networks. The framework is based on the idea of the Nash bargaining solution from cooperative game theory, which not only provides the rate settings of users that are Pareto optimal from the point of view of the whole system, but are also consistent with the fairness axioms of game theory. We first consider the centralized problem and then show that this procedure can be decentralized so that greedy optimization by users yields the system optimal bandwidth allocations. We propose a distributed algorithm for implementing the optimal and fair bandwidth allocation and provide conditions for its convergence. The paper concludes with the pricing of elastic connections based on users' bandwidth requirements and users' budget. We show that the above bargaining framework can be used to characterize a rate allocation and a pricing policy which takes into account users' budget in a fair way and such that the total network revenue is maximized     

State-dependent control of call arrivals in layered cellular mobile networks

Layered cellular mobile networks have been widely proposed as a way of accommodating traffic growth in mobile communications. There is a need, however, to give some form of priority to handover attempts over fresh call attempts to ensure that handovers are fast and reliable. A class of call control policies with state-dependent control of fresh call arrivals is considered for this purpose. A modified version of the Value Iteration Algorithm is used to solve a Markov decision model for the optimal call control policy. The network blocking performance under optimal state-dependent control is compared with the performance under a much simpler channel reservation policy for a model of a cellular sub-network. The channel reservation policy is shown to perform nearly as well as the optimal policy at lower loads, where fresh call blocking is less than 5%, indicating that it is both an effective and an efficient method for ensuring good handover performance.     

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.     

A learning approach for prioritized handoff channel allocation in mobile multimedia networks

An efficient channel allocation policy that prioritizes handoffs is an indispensable ingredient in future cellular networks in order to support multimedia traffic while ensuring quality of service requirements (QoS). In this paper we study the application of a reinforcement-learning algorithm to develop an alternative channel allocation scheme in mobile cellular networks that supports multiple heterogeneous traffic classes. The proposed scheme prioritizes handoff call requests over new calls and provides differentiated services for different traffic classes with diverse characteristics and quality of service requirements. Furthermore, it is asymptotically optimal, computationally inexpensive, model-free, and can adapt to changing traffic conditions. Simulations are provided to compare the effectiveness of the proposed algorithm with other known resource-sharing policies such as complete sharing and reservation policies     

Probabilistic channel reservation scheme for mobilepico/microcellular networks

Channel reservation based on the handoff probability of a call arriving in an adjacent cell is proposed as a more flexible and dynamic means of providing handoff priority in mobile pico/microcellular networks in which frequent handoff events are to be expected. A basic probabilistic channel reservation scheme is described and shown to yield improvements in performance, especially in terms of channel utilization by successfully completed call, over the well-known static trunk reservation policy     

Load balancing for cellular/WLAN integrated networks

The interworking between heterogeneous third-generation cellular networks and wireless local area networks is one promising evolution approach to fourth-generation wireless networks, which can exploit the complementary advantages of the cellular network and WLANs. Resource management for the 4G-oriented cellular/WLAN integrated network is an important open issue that deserves more research efforts. In this article we present a policy framework for resource management in a loosely coupled cellular/WLAN integrated network, where load balancing policies are designed to efficiently utilize the pooled resources of the network. A two-phase control strategy is adopted in the load balancing policies, in which call assignment is used to provide a statistical quality of service guarantee during the admission phase, and dynamic vertical handoff during the traffic service phase is used to minimize the performance variations. Numerical results are presented to demonstrate that the proposed load balancing solution achieves significant performance improvement over two other reference schemes     

Call admission control in cellular networks: A reinforcement learning solution

In this paper, we address the call admission control (CAC) problem in a cellular network that handles several classes of traffic with different resource requirements. The problem is formulated as a semi‐Markov decision process (SMDP) problem. We use a real‐time reinforcement learning (RL) [neuro‐dynamic programming (NDP)] algorithm to construct a dynamic call admission control policy. We show that the policies obtained using our TQ‐CAC and NQ‐CAC algorithms, which are two different implementations of the RL algorithm, provide a good solution and are able to earn significantly higher revenues than classical solutions such as guard channel. A large number of experiments illustrates the robustness of our policies and shows how they improve quality of service (QoS) and reduce call‐blocking probabilities of handoff calls even with variable traffic conditions. Copyright © 2004 John Wiley & Sons, Ltd.     

A Noncooperative Game-Theoretic Framework for Radio Resource Management in 4G Heterogeneous Wireless Access Networks

Fourth generation (4G) wireless networks will provide high-bandwidth connectivity with quality-of-service (QoS) support to mobile users in a seamless manner. In such a scenario, a mobile user will be able to connect to different wireless access networks such as a wireless metropolitan area network (WMAN), a cellular network, and a wireless local area network (WLAN) simultaneously. We present a game-theoretic framework for radio resource management (that is, bandwidth allocation and admission control) in such a heterogeneous wireless access environment. First, a noncooperative game is used to obtain the bandwidth allocations to a service area from the different access networks available in that service area (on a long-term basis). The Nash equilibrium for this game gives the optimal allocation which maximizes the utilities of all the connections in the network (that is, in all of the service areas). Second, based on the obtained bandwidth allocation, to prioritize vertical and horizontal handoff connections over new connections, a bargaining game is formulated to obtain the capacity reservation thresholds so that the connection-level QoS requirements can be satisfied for the different types of connections (on a long-term basis). Third, we formulate a noncooperative game to obtain the amount of bandwidth allocated to an arriving connection (in a service area) by the different access networks (on a short-term basis). Based on the allocated bandwidth and the capacity reservation thresholds, an admission control is used to limit the number of ongoing connections so that the QoS performances are maintained at the target level for the different types of connections.     

Performance analysis of stochastic fair sharing scheme for link sharing

We address the problem of the performance analysis of the stochastic fair sharing (SFS) algorithm for fair link sharing. The SFS scheme has been proposed to carry out a fair link sharing and fair sharing among virtual private networks. Depending upon the current utilization and provisioned capacities of the classes, the SFS admission control algorithm decides which sessions to accept and which to reject. In this letter, we undertake the performance evaluation of the SFS scheme analytically. We explore the tradeoff between fairness and the blocking probability by varying the trunk reservation parameter. The results show that the analytical performance measure agrees well with the simulation results.     

Non-Uniform Traffic Issues in DCA Wireless Multimedia Networks

Wireless networks that utilize dynamic channel allocation (DCA) are known to perform better than those with fixed channel allocation, in terms of the call level QoS measures such as the handoff dropping probability. On account of this, the DCA networks are usually designed without the call admission control (CAC). However, given the decrease of cell sizes, together with ever increasing mobile phone and terminal population, dynamic channel allocation policies (such as channel borrowing) may not be sufficient to cope with the hot-spot area size and its traffic intensity. This paper analyses the performance of the DCA networks, both with and without the call admission control, under the hot-spot traffic regime. In such cases, the pure DCA approach fails to ensure sufficiently low level of QoS in both the hot-spot area and the surrounding cells. We propose a CAC policy that can stabilize the QoS under non-uniform traffic, whilst being easy to integrate in the distributed DCA policies.     

Rate adaptive multimedia streams: optimization and admission control

This work investigates support of rate adaptive multimedia streams on communication networks. Optimal and practical mechanisms to maximize the customer average quality of service (QoS), defined in terms of a normalized time average received rate, are established. By scaling the arrival rate and link capacity, we obtain asymptotic expressions for customer average QoS in the case of networks with single bottleneck links. The optimal adaptation policy is identified as the solution to an integer program which has an intuitive "sort by volume" interpretation for the case of single bottleneck links, where stream volume is the total number of bits associated with a stream at its maximum resolution. Our asymptotic analysis shows the optimal adaptation policy may yield performance improvements of up to 42% over baseline policies. We demonstrate that a static multi-class admission control policy can achieve the same asymptotic QoS as that of the optimal adaptation policy. This implies that dynamic adaptation may be unnecessary for large capacity networks with appropriate call admission.     

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.     

A separation principle between scheduling and admission control forbroadband switching

A framework for joint scheduling and admission control in broadband switching systems based on a principle of separation between these two levels of control is developed. It is shown that an admission control strategy can be tailored to a particular mix of traffic by using high-level information from the scheduler. This principle is presented in the context of asynchronous time-sharing (ATS) in which explicit guarantees of cell-level and call-level quality of service (QOS) are given to several traffic classes. The separation principle allows the formulation of an optimal admission control policy that maximizes the expected system utility and maintains all QOS guarantees. Several heuristic admission control policies are considered and compared with the optimal policy. The admissible load region is introduced as a means of quantifying the capacity of a switch under the QOS constraints at the cell and call levels. Numerical calculations for a single MAGNET II switching node carrying two classes of real-time traffic are used to illustrate the effects of different scheduling and admission control policies on both the expected utility and the admissable load region     

A Prioritized Real-Time Wireless Call Degradation Framework for Optimal Call Mix Selection

This paper describes a framework for selecting the optimal call mix to be admitted while employing a bandwidth degradation policy in a wireless cellular network. The optimal property is achieved by maximizing the revenue generated by different calls in a cell for the service provider. By degradation, we mean that: (1) some channels can be taken away from ongoing calls that are assigned multiple channels, and/or (2) newly admitted calls that require multiple channels get fewer than what they requested. To avoid removing more channels from calls than they could tolerate, we incorporate a new call attribute: the degradation tolerance, i.e., the number of channels a call can be degraded without sacrificing the acceptable level of quality. We also consider priorities over calls to influence the admission and/or degradation decision. Our analytical framework includes both static and dynamic scenarios. The dynamic case is enhanced with the ability to select the optimal call mix using incoming and departing handoffs, new calls, and call terminations in a recursive way, thus, resulting in a call admission policy. We also discuss how to accommodate non-real-time calls into our system. To evaluate the performance of the proposed scheme, a discrete event simulation tool has been developed that models our dynamic framework built on a customized simulated annealing optimization function. Simulation results demonstrate that not only does the proposed degradation framework maximize the total revenue generated by the admitted calls in the cells, but also reduce the handoff and new call blocking probabilities.     

Optimal Resource Allocation and Fairness Control in All-Optical WDM Networks

This paper investigates the problem of optimal wavelength allocation and fairness control in all-optical wavelength-division-multiplexing networks. A fundamental network topology, consisting of a two-hop path network, is studied for three classes of traffic. Each class corresponds to a source-destination pair. For each class, call interarrival and holding times are exponentially distributed. The objective is to determine a wavelength allocation policy in order to maximize the weighted sum of users of all classes (i.e., class-based utilization). This method is able to provide differentiated services and fairness management in the network. The problem can be formulated as a Markov decision process (MDP) to compute the optimal allocation policy. The policy iteration algorithm is employed to numerically compute the optimal allocation policy. It has been analytically and numerically shown that the optimal policy has the form of a monotonic nondecreasing switching curve for each class. Since the implementation of an MDP-based allocation scheme is practically infeasible for realistic networks, we develop approximations and derive a heuristic algorithm for ring networks. Simulation results compare the performance of the optimal policy and the heuristic algorithm, with those of complete sharing and complete partitioning policies.     

A comprehensive resource management framework for next generation wireless networks

We propose an integrated resource management approach that can be implemented in next generation wireless networks that support multimedia services (data, voice, video, etc.). Specifically, we combine the use of position-assisted and mobility predictive advanced bandwidth reservation with a call admission control and bandwidth reconfiguration strategy to support flexible QoS management. We also introduce a mobile agent based framework that can be used to carry out the functions of geolocation and of the proposed resource management in wireless networks. A model is also developed to obtain the optimal location information update interval in order to minimize the total cost of the system operation. The comparison of the achievable performance results of our proposed scheme with the corresponding results of a conventional system that supports advanced bandwidth reservation only, as means of supporting the QoS requirements, demonstrate that our integrated scheme can alleviate the problem of overreservation, support seamless operation throughout the wireless network, and increase significantly the system capacity.