A dynamic channel assignment policy through Q-learning

One of the fundamental issues in the operation of a mobile communication system is the assignment of channels to cells and to calls. This paper presents a novel approach to solving the dynamic channel assignment (DCA) problem by using a form of real-time reinforcement learning known as Q-learning in conjunction with neural network representation. Instead of relying on a known teacher the system is designed to learn an optimal channel assignment policy by directly interacting with the mobile communication environment. The performance of the Q-learning based DCA was examined by extensive simulation studies on a 49-cell mobile communication system under various conditions. Comparative studies with the fixed channel assignment (FCA) scheme and one of the best dynamic channel assignment strategies, MAXAVAIL, have revealed that the proposed approach is able to perform better than the FCA in various situations and capable of achieving a performance similar to that achieved by the MAXAVAIL, but with a significantly reduced computational complexity.     

Using Cellular Probabilistic Self-Organizing Map in Borrowing Channel Assignment for Patterned Traffic Load

The fast growing cellular mobile systems demand more efficient and faster channel allocation techniques. Borrowing channel assignment (BCA) is a compromising technique between fixed channel allocation (FCA) and dynamic channel allocation (DCA). However, in the case of patterned traffic load, BCA is not efficient to further enhance the performance because some heavy-traffic cells are unable to borrow channels from neighboring cells that do not have unused nominal channels. The performance of the whole system can be raised if the short-term traffic load can be predicted and the nominal channels can be re-assigned for all cells. This paper describes an improved BCA scheme using traffic load prediction. The prediction is obtained by using the short-term forecasting ability of cellular probabilistic self-organizing map (CPSOM). This paper shows that the proposed CPSOM-based BCA method is able to enhance the performance of patterned traffic load compared with the traditional BCA methods. Simulation results corroborate that the proposed method delivers significantly better performance than BCA for patterned traffic load situations, and is virtually as good as BCA in the other situations analyzed.     

An efficient evolutionary algorithm for channel resource managementin cellular mobile systems

Modern cellular mobile communications systems are characterized by a high degree of capacity. Consequently, they have to serve the maximum possible number of calls while the number of channels per cell is limited. The objective of channel allocation is to assign a required number of channels to each cell such that both efficient frequency spectrum utilization is provided and interference effects are minimized. Channel assignment is therefore an important operation of resource management and its efficient implementation increases the fidelity, capacity, and quality of service of cellular systems. Most channel allocation strategies are based on deterministic methods, however, which result in implementation complexity that is prohibitive for the traffic demand envisaged for the next generation of mobile systems. An efficient heuristic technique capable of handling channel allocation problems is introduced as an alternative. The method is called a combinatorial evolution strategy (CES) and belongs to the general heuristic optimization techniques known as evolutionary algorithms (EAs). Three alternative allocation schemes operating deterministically, namely the dynamic channel assignment (DCA), the hybrid channel assignment (HCA), and the borrowing channel assignment (BCA), are formulated as combinatorial optimization problems for which CES is applicable. Simulations for representative cellular models show the ability of this heuristic to yield sufficient solutions. These results will encourage the use of this method for the development of a heuristic channel allocation controller capable of coping with the traffic and spectrum management demands for the proper operation of the next generation of cellular systems     

一种基于改进神经网络的动态信道分配算法

提出了一种基于改进神经网络的整体优化的动态信道分配方案(GODCA),该算法尽量保证最大程度的紧致分配,网络优化采用Hopfield神经网络,克服了传统动态信道分配方案实现方式繁杂,且往往不能达到紧致分配方式的不足,同时针对神经网络算法随机性强的弱点,提出一种优化的收敛算法。分析和仿真表明,该算法不论在业务量较大,还是较小都有较小的呼阻率和较高的频谱利用率。     

基于免疫策略的信道资源分配算法

根据信道分配的限制条件和特点应用免疫策略算法（ISA）,提出了基于 ISA的一种整体优化的动态信道资源分配方案,其特点是保证最大程度的紧致分配。同时针对遗传算法的退化现象引入免疫策略算法,较好解决了遗传算法的退化问题。实验仿真表明,该方案与现有的固定信道分配（FCA）、动态信道分配（DCA）方案和改进遗传算法信道分配方案（IGADCA）相比,有较小的呼阻率。     

An Adaptive Distributed Channel Allocation Strategy for Mobile Cellular Networks

A channel allocation algorithm includes a channel acquisition algorithm and a channel selection algorithm. Most of the previous work concentrates on the channel selection algorithm since early channel allocation algorithms simply use a centralized channel acquisition algorithm, which depends on a mobile switching center (MSC) to accomplish channel acquisition. Recently, distributed channel acquisition algorithms have received considerable attention due to their high reliability and scalability. There are two approaches to designing distributed channel acquisition algorithms: search and update. The update approach has shorter acquisition delay and lower call blocking rate, but higher message complexity. On the other hand, the search approach has lower message complexity, but longer acquisition delay and higher call blocking rate. In this paper, we propose a novel distributed channel acquisition algorithm, which is a significant improvement over both approaches. Also, we identify two guiding principles in designing channel selection algorithms and propose an algorithm which has low call blocking rate and low intrahandoff overhead. By integrating the channel selection algorithm into our channel acquisition algorithm, we get a complete distributed channel allocation algorithm. By keeping the borrowed channels, the channel allocation algorithm makes use of the temporal locality and adapts to the network traffic; i.e., free channels are transferred to hot cells to achieve load balance. Simulation results show that our channel allocation algorithm significantly outperforms the search approach and the update approach in terms of call blocking rate, message complexity, and acquisition delay.     

A hybrid channel allocation algorithm with priority to handoff calls in mobile cellular networks

This paper proposes and investigates a novel analytical model of a hybrid channel allocation algorithm within wireless cellular networks. Each cell of the network consists of a predesigned fixed number of channels and the network may approve the request for extra channels for both new and handoff calls if all predesigned channels are occupied. This approval depends on the types of new and handoff calls, as well as the number of approved additional channels in the cell. If a request is denied for the arriving new call, this call will be blocked and cleared from the system. However, if a request is denied for an arriving handoff call, this call will not be blocked immediately but rather put on hold in a buffer with finite space. The implication behind this is to give priority to handoff calls. For this proposed hybrid channel allocation scheme, we first obtain the stationary distribution of each cell when there are i calls connecting to the system and j calls holding on in the buffer. We then derive new and handoff call blocking probabilities, the average number of borrowed channels, and the average delay period of handoff calls. The numerical results show that the proposed hybrid algorithm is more efficient than other approaches, specifically, in comparison with methods without a borrowing capability for new calls and those without a reserved buffer priority for handoff calls. The idea and results presented in this paper are expected to provide guidelines for field data processing within current wireless and mobile network design and performance evaluation.     

Performance analysis of a threshold based distributed channel allocation algorithm for cellular networks

Rapid advances of the handheld devices and the emergence of the demanding wireless applications require the cellular networks to support the demanding user needs more effectively. The cellular networks are expected to provide these services under a limited bandwidth. Efficient management of the wireless channels by effective channel allocation algorithms is crucial for the performance of any cellular system. To provide a better channel usage performance, dynamic channel allocation schemes have been proposed. Among these schemes, distributed dynamic channel allocation approaches showed good performance results. The two important issues that must be carefully addressed in such algorithms are the efficient co-channel interference avoidance and messaging overhead reduction. In this paper, we focus on our new distributed channel allocation algorithm and evaluate its performance through extensive simulation studies. The performance evaluation results obtained under different traffic load and user mobility conditions, show that the proposed algorithm outperforms other algorithms recently proposed in the literature.     

Loosely coordinated coscheduling in the context of other approaches for dynamic job scheduling: a survey

Loosely coordinated (implicit/dynamic) coscheduling is a time‐sharing approach that originates from network of workstations environments of mixed parallel/serial workloads and limitedsoftware support. It is meant to be an easy‐to‐implement and scalable approach. Considering that the percentage of clusters in parallel computing is increasing and easily portable software is needed, loosely coordinated coscheduling becomes an attractive approach for dedicated machines. Loose coordination offers attractive features as a dynamic approach. Static approaches for local job scheduling assign resources exclusively and non‐preemptively. Such approaches still remain beyond the desirable resource utilization and average response times. Conversely, approaches for dynamic scheduling of jobs can preempt resources and/or adapt their allocation. They typically provide better resource utilization and response times. Existing dynamic approaches are full preemption with checkpointing, dynamic adaptation of node/CPU allocation, and time sharing via gang or loosely coordinated coscheduling. This survey presents and compares the different approaches, while particularly focusing on the less well‐explored loosely coordinated time sharing. The discussion particularly focuses on the implementation problems, in terms of modification of standard operating systems, the runtime system and the communication libraries. Copyright © 2005 John Wiley & Sons, Ltd.     

多层蜂窝系统信道指配仿真与性能分析

对多级蜂窝系统信道指配策略的研究几乎抛弃了原有单层系统下的信道指配策略，而蜂窝信道指配策略性能的研究，一般都辅之以计算机仿真。给出了使用Object Pascal语言对信道指配策略在单机上进行网络仿真的技巧和算法，并将单层蜂窝系统中行之有效的信道借用和多层蜂窝系统中的溢出策略相结合进行了仿真和性能分析。结果表明，适用于单层系统的信道借用策略对于多层系统仍然非常有效，而双向溢出策略结合层内信道借用具有更好的系统性能。     

一种支持宽带无线多媒体网络QoS的动态呼叫接纳策略

在无线网络中,小区微型化的趋势使得呼叫切换发生的频率越来越高,迫切需要一种有效的呼叫接纳控制策略,对有限的无线带宽资源进行分配,以保证切换时的QoS,同时使带宽利用率最高。传统的预留带宽策略(GC,guard channel scheme)由于其固有的静态特征而不能适应流量模式的变化。最近,人们发现采用动态的随机控制策略能适应流量模式的变化,而且能使精度和稳定性大大提高。但将这种策略应用于多业务环境依然十分困难,挑战来自于多类呼叫的QoS要求、流量模式、切换率的多样性和宽带条件下的实时可计算性。在文[3]中,我们建立了一个随机控制模型,可以在宽带条件下实时地进行多业务接纳控制,但由于没有考虑复杂的边界条件,控制精度受到影响。本文,我们在考虑边界条件的情况下,求解该随机问题,并采用一种有效的数值方法,使计算复杂度大大降低,保证了计算的实时性。最后得到的多业务动态接纳控制策略具有较高的控制精度和良好的可计算性。仿真结果显示该策略能稳定地满足多业务QoS对呼叫中断概率的严格限制,同时又能保证信道的高利用率。     

一种自适应的扇型微蜂房式带宽预留通信模式

在目前的跨区域连接方式中,扇型微蜂房式的网络系统比传统的微蜂房式系统有更高的传输速度.文中介绍了一种自适应的带宽预留模式,这种模式使用了一种神经模糊带宽预留估计量的技术,经过证实,这种技术能够减少客户连接时被强行终止的概率.在这种带宽预留模式中,使用一种通道借用技术能够在实时通信时,减少新的呼叫受阻现象的发生.通过分析强行终止的客户连接和呼叫受阻的概率事件,仿真结果表明,采用扇型微蜂房式的网络系统比传统的固定带宽预留模式要有更好的性能.     

A network flow based approach for network selection in dynamic spectrum access networks

In this paper, we present a network flow based approach for dynamic network and channel selection for secondary users in dynamic spectrum access networks. Most approaches in the current literature on dynamic spectrum access networks do not consider dynamic network and channel selection. We present a network flow framework for network selection. We show that our approach can enable re-assignment of networks to secondary users and also re-assignment of channels to secondary users within the same network. The assignments and re-assignments take into account, the interference caused to primary users, the price each secondary user is willing to pay and the quality of service (QoS) obtained by each secondary user. We obtain a bound for the maximum number of re-assignments.     

Performance prediction for OFDMA systems with dynamic power and subcarrier allocation

It is well known that channel-dependent OFDMA resource assignment algorithms provide a significant performance improvement compared to static (i.e., channel-unaware) approaches. Such dynamic algorithms constantly adapt resource assignments to current channel states according to some objective function. Due to these dynamics, it is difficult to predict the resulting performance for such schemes given a certain scenario (characterized by the number of terminals in the cell and their average channel gains). In this paper we provide a novel, analytical framework for performance prediction, which takes dynamic power and subcarrier allocation into account. The analysis is based on fundamental transformations of the channel gains caused by the dynamic subcarrier allocations. This insight allows for deriving probability functions of the achieved rate per subcarrier which ultimately yields expressions for the expected minimal rates as well as outage probabilities for certain rate demands. Hence, the methods presented in this paper for performance prediction can be employed for admission control in systems with dynamic resource allocation. We illustrate the applicability of our derivations with respect to the capacity of 802.16e systems for Voice-over-IP and video streams. The results demonstrate a significant improvement compared to state-of-the art approaches but also reveal room for improvement of this approach compared to the optimal system performance.     

Predicting intrusion goal using dynamic Bayesian network with transfer probability estimation

Predicting the intentions of an observed agent and taking corresponding countermeasures is the essential part for the future proactive intrusion detection systems (IDS) as well as intrusion prevention systems (IPS). In this paper, an approach of dynamic Bayesian network with transfer probability estimation was developed to predict whether the goal of system call sequences is normal or not, with early-warnings being launched, so as to ensure that some appropriate countermeasures could be taken in advance. Since complete set of system call state transfer can hardly be built in real environments, the empirical results show that the newly emerging system call transfer would have great impact on the prediction performance if we straightly use dynamic Bayesian network without transfer probability estimation. Therefore, we estimate the probability of new state transfer to predict the goals of system call sequences together with those in conditional probability table (CPT). It surmounts the difficulties of manually selecting compensating parameters with dynamic Bayesian network approach [Feng L, Guan X, Guo S, Gao Y, Liu P. Predicting the intrusion intentions by observing system call sequences. Computers & Security 2004; 23/3: 241–252] and obviously makes our prediction model more applicable. The University of New Mexico (UNM) and KLINNS data sets were analyzed and the experimental results show that it performs very well for predicting the goals of system call sequences with high accuracy and furthermore dispenses with much more manual work for selecting compensating parameters.     

A fair resource allocation protocol for multimedia wireless networks

Wireless networks are expected to support real-time interactive multimedia traffic and must be able, therefore, to provide their users with quality-of-service (QoS) guarantees. Although the QoS provisioning problem arises in wireline networks as well, mobility of hosts and scarcity of bandwidth makes QoS provisioning a challenging task in wireless networks. It has been noticed that multimedia applications can tolerate and gracefully adapt to transient fluctuations in the QoS that they receive from the network. The additional flexibility afforded by the ability of multimedia applications to tolerate and adapt to transient changes in QoS can be exploited by protocol designers to significantly improve the overall performance of wireless systems. This paper presents a fair resource allocation protocol for multimedia wireless networks that uses a combination of bandwidth reservation and bandwidth borrowing to provide network users with QoS in terms of guaranteed bandwidth, call blocking, and call dropping probabilities. Our view of fairness was inspired by the well-known max-min fairness allocation protocol for wireline networks. Simulation results are presented that compare our protocol to similar schemes.     

Borrowing channel assignment strategies based on heuristictechniques for cellular systems

The demand for more efficient and fast channel allocation techniques in cellular systems increases day by day. Borrowing channel assignment (BCA) was introduced in the literature as a compromise between the classic fixed and dynamic channel allocation schemes. This paper examines the behavior of three heuristic BCA techniques based alternatively on a Hopfield neural network, an efficient evolutionary algorithm named combinatorial evolution strategy (CES) and a third heuristic which combines the basic advantages of the two above computational intelligence methods. By considering some specific assumptions that follows an ideal cellular mobile model, BCA is formulated as a combinatorial optimization problem. The above heuristics have been extensively applied to solve efficiently such problems in the past. Simulation results, derived for uniform and nonuniform traffic load conditions, are used to compare these BCA schemes each other as also with other well-established allocation techniques.     

An opportunistic resource allocation approach for mixed QoS and non-QoS connections in OFDMA wireless networks

An opportunistic resource allocation approach is proposed to guarantee both fair resource allocation and high system throughput under combinations of QoS and non-QoS connections in OFDMA networks. This approach features dynamic connection classification and packet prioritization based on real-time network conditions and QoS constraints. A classifier is first employed to prioritize QoS connections by observing the channel state of each subscriber station and the utilization of network resources. It performs a finite-horizon Markov decision process with dynamic rules affected by system load. The transmission order of packets is then determined by an opportunistic multiservice scheduler according to the QoS requirements of connections and the output of the classifier. Having the scheduling result, an allocator assigns slots to the scheduled packets, and its output is linked back to the connection classifier through a resource usage observer for all subscriber stations. The sub-channel allocation problem is also solved by cooperation between the slot allocator and the packet scheduler. Results of numerical analysis and NS2 simulation confirm the advantages claimed above. The same conclusion can also be drawn from the comparison with several existing approaches in terms of system throughput, service successful ratio, average spectral efficiency, and system revenue.     

异构蜂窝系统中动态联合呼叫接纳控制算法

针对异构蜂窝系统的接纳控制问题,设计了一种动态联合呼叫接纳控制算法。该算法采取TOPSIS法选择最优接入网,根据系统负载分布情况动态调整网络资费,对用户的接入选择决策施加影响,以均衡网络间负载;针对不同的呼叫优先级,采取多级接入阈值及动态带宽分配策略,在接入控制环节进一步改善系统性能及用户体验。仿真结果表明,该算法在重视用户偏好的同时实现了负载均衡,降低了呼叫阻塞率和掉线率。     

Extended EDCA for delay guarantees in wireless local area networks

Despite their very broad diffusion, IEEE 802.11 Wireless Local Area Networks (WLANs) are not able to provide service differentiation and to support real-time multimedia applications, due to their channel access methods. To overcome these limitations, the 802.11e working group has proposed the Enhanced Distributed Coordination Access (EDCA) scheme, which achieves service differentiation on a statistical basis by properly mapping user Quality of Service (QoS) requirements to channel contention parameters. Such a scheme will be included in the emerging 802.11n standard and in the revision of the 802.11 standard. However, it has been widely demonstrated that, especially at high network loads, EDCA does not provide an effective usage of the channel capacity. In particular, it is unable to provide a bounded delay service to all kinds of multimedia flow because flows with lower channel access priorities are starved to advantage only those with the highest priority. To fix this undesired behavior and improve wireless LAN performance, this paper proposes a new Extended EDCA (E²DCA) scheme, that is compliant with 802.11e specifications. By exploiting a closed-loop control algorithm, E²DCA performs a distributed dynamic bandwidth allocation, providing guarantees on average/absolute delays to real-time media flows, regardless of their priorities. Moreover, an innovative Call Admission Control (CAC) procedure has been developed. Using the ns-2 simulator, the effectiveness of the algorithm has been investigated in realistic network scenarios, involving a mix of audio, video, and FTP flows, at several network loads and with random losses. Results have shown that the proposed scheme is able to provide a bounded delay service to multimedia flows in a wide range of network loads and frame loss ratios.