Admission Control Policy Research Articles

Connection Admission Control for Multiservice Integrated Cellular/WLAN System

The complementary characteristics of wireless cellular networks and wireless local area networks (WLANs) make them suitable to jointly offer seamless wireless access services to mobile users. In an integrated cellular/WLAN system, the quality-of-service (QoS) requirements for different services (e.g., voice, real-time video) require admission control to limit the number of connections in each access network. In this paper, we first develop an analytical model to facilitate the evaluation of different admission control policies in a multiservice integrated cellular/WLAN system. We then formulate two different revenue-maximization problems. Each problem takes different QoS requirements into account. By solving the equivalent cost-minimization problems, we evaluate the system performance when different combinations of cutoff priority and fractional guard channel admission control policies are being used. Results show that using a cutoff priority policy in both wireless access networks can achieve the optimal solution for the two optimization problems under a wide range of network conditions.

Optimal admission control in multimedia mobile networks with handover prediction

Admission control is one of the key traffic management mechanisms that must be deployed in order to meet the strict requirements for dependability imposed on the services provided by modern wireless networks. We study the problem of optimizing admission control policies in mobile multimedia cellular networks when predictive information regarding the movement of mobile terminals is available. For the optimization process we deploy a novel reinforcement learning approach based on the concept of after states. The results obtained define theoretical limits for the gain that can be expected when using handover prediction, which cannot be established by deploying heuristic approaches. Numerical results show that the performance gain is a function of the anticipation time with which the admission controller knows the occurrence of handovers, and an optimal anticipation time exists. We also compare an optimal policy obtained deploying our approach with a previously proposed heuristic prediction scheme, showing that there is still room for technological innovation.

Integration of Explicit Effective-Bandwidth-Based QoS Routing With Best-Effort Routing

This paper presents a methodology for protecting low-priority best-effort (BE) traffic in a network domain that provides both virtual-circuit routing with bandwidth reservation for QoS traffic and datagram routing for BE traffic. When a QoS virtual circuit is established, bandwidths amounting to the traffic's effective bandwidths are reserved along the links. We formulate a new QoS-virtual-circuit admission control and routing policy that sustains a minimum level of BE performance. In response to a QoS connection request, the policy executes a two-stage optimization. The first stage seeks a minimum-net-effective-bandwidth reservation path that satisfies a BE protecting constraint; the second stage is a tie-breaking rule, selecting from tied paths one that least disturbs BE traffic. Our novel policy implementation efficiently executes both optimization stages simultaneously by a single run of Dijkstra's algorithm. According to simulation results, within a practical operating range, the consideration that our proposed policy gives to the BE service does not increase the blocking probability of a QoS connection request.

An Empirical Study on the Capacity and Performance of 3G Networks

This paper presents the findings of an extensive measurement study on multiple commercial 3G networks. We have investigated the performance of those 3G networks in terms of their data throughput, latency, video and voice calls handling capacities, and their ability to provide service guarantees to different traffic classes under saturated and lightly-loaded network conditions. Our findings point to the diverse nature of the network resources allocation mechanisms and the call admission control policies adopted by different operators. It is also found that the 3G network operators seem to have extensively customized their network configurations in a cell-by-cell manner according to the individual site's local demographics, projected traffic demand and the target coverage area of the cell. As such, the cell capacity varies widely not only across different operators but also across different measurement sites of the same operator. The results also show that it is practically impossible to predict the actual capacity of a cell based on known theoretical models and standard parameters, even when supplemented by key field measurements such as the received signal-to-noise ratio (Ec/N0)

A Guard Code Scheme for Handover Traffic Management in WCDMA Systems

A key performance indicator of mobile wireless networks is failure probability of handover calls. In this paper, we propose a Call Admission Control policy which prioritizes handover calls over new calls in WCDMA systems. The OVSF code occupancy of the system is modeled by a Markov chain and the differentiation between handover and new calls is performed at the code level by introducing a “guard code” scheme. The scheme belongs to the well-known family of guard channel schemes and reserves some code capacity to favor the continuation of handover calls over the new calls. As the management of the general case is intractable, we solve certain numerical instances of the problem and manage to calculate several performance metrics like new call blocking and handover failure probabilities and code utilization. We complete our study with simulation results in the case of higher OVSF code tree capacity.

Analysis of Admission and Inventory Control Policies for Production Networks

Problems of inventory control and customer admission control are considered for a manufacturing system that produces one product to meet random demand. Four admission policies are investigated: lost sales, complete backordering, randomized admission, and partial backordering. These policies are combined with an integral inventory control policy, which releases raw items only when an incoming order is accepted and keeps the inventory position (total inventory minus outstanding orders) constant. The objective is to determine the inventory level and the maximum number of backorders, as well as the admission probability that maximize the mean profit rate of the system. The system is modeled as a closed queueing network and its performance is computed analytically. The optimal parameters for each policy are found using exhaustive search and convex analysis. Numerical results show that managing inventory levels and sales jointly through partial backordering achieves higher profit than other control policies.

Asymptotically Optimal Admission Control of a Queue with Impatient Customers

We consider a GI/GI/1 queue with impatient customers in heavy traffic. We use the solution of an approximating singular diffusion control problem to construct an admission control policy for the queue. The approximating control problem does not admit a so-called pathwise solution. Hence, the resulting admission control policy depends on second-moment data. We prove asymptotic optimality of the constructed policy using weak-convergence methods.rh

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.

Editorial for the Special Issue of ACM/Springer Mobile Networks and Applications - Selected Papers from Fourth International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QShine 2007)

1. Interworking Architectures for IP Multimedia Subsystems Arslan Munir and Vincent W.S. Wong 2. Optimal Admission Control Policies for Heterogeneous Wireless Networks Amin Farbod and Ben Liang 3. Comparison of Multimedia Delivery Scenarios Using Parallel Wireless Links and Path Diversity Ki-Dong Lee, Byung K. Yi, and Victor C.M. Leung 4. Towards an FBM Model Based Network Calculus Framework with Service Differentiation Yu Cheng, Weihua Zhuang and Xinhua Ling. This paper was selected for QShine’2007 Best Paper Award. 5. On Throughput Efficiency of Geographic Opportunistic Routing in Wireless Ad Hoc Networks Kai Zeng, Wenjing Lou, Jie Yang, and Donald R. Brown III. This paper was selected for QShine’2007 Best Paper Award Runner-Up.

Cross-Layer Admission Control Policy for CDMA Beamforming Systems

A novel admission control (AC) policy is proposed for the uplink of a cellular CDMA beamforming system. An approximated power control feasibility condition (PCFC), required by a cross-layer AC policy, is derived. This approximation, however, increases outage probability in the physical layer. A truncated automatic retransmission request (ARQ) scheme is then employed to mitigate the outage problem. In this paper, we investigate the joint design of an AC policy and an ARQ-based outage mitigation algorithm in a cross-layer context. This paper provides a framework for joint AC design among physical, data-link, and network layers. This enables multiple quality-of-service (QoS) requirements to be more flexibly used to optimize system performance. Numerical examples show that by appropriately choosing ARQ parameters, the proposed AC policy can achieve a significant performance gain in terms of reduced outage probability and increased system throughput, while simultaneously guaranteeing all the QoS requirements.

Resource-Aware Distributed Scheduling Strategies for Large-Scale Computational Cluster/Grid Systems

In this paper, we propose distributed algorithms referred to as resource-aware dynamic incremental scheduling (RADIS) strategies. Our strategies are specifically designed to handle large volumes of computationally intensive arbitrarily divisible loads submitted for processing at cluster/grid systems involving multiple sources and sinks (processing nodes). We consider a real-life scenario, wherein the buffer space (memory) available at the sinks (required for holding and processing the loads) varies over time, and the loads have deadlines and propose efficient "pull-based" scheduling strategies with an admission control policy that ensures that the admitted loads are processed, satisfying their deadline requirements. The design of our proposed strategies adopts the divisible load paradigm, referred to as the divisible load theory (DLT), which is shown to be efficient in handling large volume loads. We demonstrate detailed workings of the proposed algorithms via a simulation study by using real-life parameters obtained from a major physics experiment.

Admission control in data transfers over lightpaths

The availability of optical network infrastructure and appropriate user control software has recently made it possible for scientists to establish end-to-end circuits across multiple management domains in support of large data transfers. These high-performance data paths are typically provisioned over 10 Gigabit optical links, and accessed using ethernet encapsulation at Gigabit and 10 Gigabit rates. The resulting mixture of circuit sizes gives rise to resource conflicts whereby requests to allocate bandwidth partitions are blocked despite vast underutilization of the optical link. In an attempt to remedy this problem, we investigate intelligent admission control policies that consider the long-term effects of admission decisions. Using analytic techniques we show that the greedy policy, which accepts requests to allocate bandwidth partitions whenever sufficient bandwidth exists, is suboptimal in a pertinent scenario. We then consider dynamic online computation of the optimal admission control policy and show that the acceptance ratio of requests to establish end-to-end circuits can be improved by up to 19% on a fifteen-node network where the behaviour of each link is governed by a local optimization effort.

A Reinforcement Learning Approach for Admission Control in Mobile Multimedia Networks with Predictive Information

We study the problem of optimizing admission control policies in mobile multimedia cellular networks when predictive information regarding movement is available and we evaluate the gains that can be achieved by making such predictive information available to the admission controller. We consider a general class of prediction agents which forecast the number of future handovers and we evaluate the impact on performance of aspects like: whether the prediction refers to incoming and/or outgoing handovers, inaccurate predictions, the anticipation of the prediction and the way that predictions referred to different service classes are aggregated. For the optimization process we propose a novel Reinforcement Learning approach based on the concept of afterstates. The proposed approach, when compared with conventional Reinforcement Learning, yields better solutions and with higher precision. Besides it tackles more efficiently the curse of dimensionality inherent to multimedia scenarios. Numerical results show that the performance gains measured are higher when more specific information is provided about the handover time instants, i.e. when the anticipation time is deterministic instead of stochastic. It is also shown that the utilization of the network is maintained at very high values, even when the highest improvements are observed. We also compare an optimal policy obtained deploying our approach with a previously proposed heuristic prediction scheme, showing that plenty of room for technological innovation exists.

An HMM-based call admission control policy for supporting QoS in wireless cellular networks

The multimedia services are getting to become the major trend in next-generation cellular networks. Call admission control (CAC) plays the key role for guaranteeing the quality of service (QoS) in cellular networks. The goal which keeps both the call dropping probability (CDP) and call blocking probability (CBP) below a certain level is more difficult owing to user indeterminate mobility. In this paper, the Hidden Markov Models (HMMs) concept which is suitable for solving a dynamic situation is introduced and applied to the call admission control policy. The prediction of user mobility can be modeled and resolved as the decoding problem of the HMMs. According to the prediction result, the proposed CAC method can reserve appropriate bandwidths for a handoff call beforehand. Thus, the call dropping probability can be kept below a lower level. Moreover, the call blocking probability is not sacrificed too much since the proposed method can reserve the suitable bandwidths in the appropriate cells but not reserve stationary ones which are always adopted by traditional CAC methods. Therefore, the proposed method not only can satisfy both CDP and CBP issues, but also improve the system utilization.

Optimizing Admission Control for Multiservice Wireless Networks With Bandwidth Asymmetry Between Uplink and Downlink

Next-generation wireless networks need to support multiclass services with asymmetric bandwidth allocation between uplink and downlink to match the asymmetric traffic load brought by some data services. For the design of call admission control (CAC) policy in such networks, how to decrease the average system cost is a key issue. In this paper, we study the optimal admission policy for minimizing the system cost. We consider the CAC problem as a decision process. By modeling the admission control problem into a Markov decision process (MDP) and analyzing the corresponding value function, we obtain some monotonicity properties of the optimal policy. These properties suggest that the optimal admission control policy for the bandwidth asymmetry wireless networks should have a threshold structure and the threshold specified for a class of calls may change with the system state. Due to the prohibitively high complexity for computing the thresholds in a system with large state-space, we propose a heuristic CAC policy called call-rate-based dynamic threshold (CRDT) policy to approximate the theoretical optimal policy based on the insights we obtain from the modeling and the analytical study on the properties of the optimal policy. The CRDT policy is efficient and can be easily implemented. The numerical results show that the performance of average system cost of the proposed CRDT policy is close to that of the optimal policy from the MDP model and is better than that of some known existing CAC schemes, including those performing well in bandwidth asymmetry wireless networks

An efficient architecture for Bandwidth Brokers in DiffServ networks

AbstractIn this article we examine the architecture of an entity used for automatic management and provisioning of resources for DiffServ networks. We examine the existing literature and implementations in this area, focusing on the design choices made, and we propose an architecture for the design of Bandwidth Brokers that combines an adaptive admission control algorithm for increased utilization of network resources and a mechanism for reducing the complexity overhead that intends to be both simple and effective. Specifically, we present a novel architecture for the admission control module that aims at achieving a satisfactory balance between maximizing the resource utilization for the network provider and minimizing the overhead of the module. We complement our theoretical discussion with extensive experimental simulations for the proposed Bandwidth Broker components and analysis of the results. The simulations study the possible configurations of the proposed algorithm and also compare it with alternative admission control policies. Copyright © 2007 John Wiley & Sons, Ltd.

Practical algorithms for scheduling video data in a local area network environment

Simultaneous transmission of multiple high quality video streams from a server to the clients is becoming an increasingly important class of traffic in a network of workstations or cluster environment. With a powerful symmetric multiprocessor (SMP) as the server and a high-speed network, such transmission is practicable from a hardware point of view. However, the actual construction of such a video data server system entails tackling a number of difficult problems related to the provision of strict quality of service (QoS) guarantees. Among others, the smoothing and scheduling of multiple video packet streams are two crucial issues. Smoothing is concerned with reducing the rate variability of video streams in view of the fact that video data are usually compressed in a variable bit rate fashion. Scheduling is important to guarantee the requested QoS levels while maximizing the utilization of the resources. Although much work on smoothing has been done, it is not clear which scheduling scheme is suitable for multiplexing smoothed video data to the network. In this paper we present an extensive performance study of the EDF and RM scheduling algorithms which are modified to provide QoS guarantees for smoothed video data. With a probabilistic definition of QoS, admission control conditions are incorporated into the two algorithms. Furthermore, a counter-based scheduling module is included as the core scheduling mechanism which adaptively adjusts the actual QoS levels assigned to requests. Our theoretical analysis of the two modified algorithms, called QEDF and QRM, shows that the QRM algorithm is more robust than the QEDF algorithm for different workload and utilization conditions. We also propose to use a new metric called meta-QoS to quantify the overall performance of a packet scheduler given a set of simultaneous requests. In our experiments based on an SMP-based Linux platform, we find that the QRM algorithm can sustain a rather stable level of meta-QoS even when the workload and utilization levels are increased. On the other hand, the QEDF algorithm, due to its conservative admission control policy, is found to be not suitable for a high level of utilization and a large number of requests. In view of the lower complexity of the QRM algorithm, it seems that the QRM approach is a more suitable candidate for packet scheduling in the client-server environment considered in our study.

Radio resource management games in wireless networks: an approach to bandwidth allocation and admission control for polling service in IEEE 802.16 [Radio Resource Management and Protocol Engineering for IEEE 802.16

Game theory is a mathematical tool developed to understand competitive situations in which rational decision makers interact to achieve their objectives. Game theory techniques have recently been applied to various engineering design problems in which the action of one component impacts (and perhaps conflicts with) that of any other component. In particular, game theory techniques have been successfully used for protocol design and optimization (e.g., radio resource management, power control) in wireless networks. In this article we present an overview of different game theory formulations. Then a survey on the game-theory-based resource management and admission control schemes in different wireless networks is presented, and several open research issues are outlined. To this end, we propose an adaptive bandwidth allocation and admission control scheme for polling service in an IEEE 802.16-based wireless metropolitan area network. A noncooperative game is formulated, and the solution of this game is determined by the Nash equilibrium for the amount of bandwidth offered to a new connection. The admission control policy ensures QoS for all connections in the system

Optimal Joint Session Admission Control in Integrated WLAN and CDMA Cellular Networks with Vertical Handoff

This paper considers optimizing the utilization of radio resources in a heterogeneous integrated system consisting of two different networks: a wireless local area network (WLAN) and a wideband code division multiple access (CDMA) network. We propose a joint session admission control scheme for multimedia traffic that maximizes overall network revenue with quality of service (QoS) constraints over both the WLAN and the CDMA cellular networks. The WLAN operates under the IEEE 802.11e medium access control (MAC) protocol, which supports QoS for multimedia traffic. A novel concept of effective bandwidth is used in the CDMA network to derive the unified radio resource usage, taking into account both physical layer linear minimum mean square error (LMMSE) receivers and characteristics of the packet traffic. Numerical examples illustrate that the network revenue earned in the proposed joint admission control scheme is significantly larger than that when the individual networks are optimized independently with no vertical handoff between them. The revenue gain is also significant over the scheme in which vertical handoff is supported, but admission control is not done jointly. Furthermore, we show that the optimal joint admission control policy is a randomized policy, i.e., sessions are admitted to the system with probabilities in some states.

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