异构无线网络中基于SINR和层次分析法的SAW垂直切换算法研究

B3G或者4G无线网络体系致力于集成各种异构无线接入网络,其中一个主要的设计课题是支持垂直切换的研究。该文将多属性QoS考虑在内,针对各业务特点,提出一种基于SINR(信干噪比)和层次分析法(AHP)的SAW(简单加权法)垂直切换算法(SASAW)。它综合考虑SINR的影响以及要获得同等数据速率情况下,目标网络需要的等效SINR数值、用户通信代价、网络可用带宽等来构造属性矩阵做切换判决。为了评估性能,考虑3GPP定义的4类业务,利用层次分析法中的特征向量法来决定各个QoS属性之间的权重关系,构造比较判决矩阵并检验其一致性;根据判决矩阵,利用特征根法获得权重向量;最后根据属性矩阵和权重向量,利用SAW垂直切换算法进行判决。通过对算法的通过率、丢话率、垂直切换次数、平均用户代价等的性能比较,结果表明该文提出的算法能够根据各业务特点综合考虑各属性间关系,获得优良的系统性能。     

Performance analysis of path rerouting algorithms for handoffcontrol in mobile ATM networks

This paper studies the effects of user mobility and handoff path rerouting on the traffic distributions in a mobile network environment. In mobile ATM networks, extra traffic load may be added to network links due to user mobility and handoff path rerouting. This requires higher network link capacity and possible topology reengineering in order to support the same quality of service (QoS) for mobile services. To capture the dynamic variations in mobile ATM networks, we propose to use a flow model. The model represents the mobile-generated traffic as a set of stochastic flows over a set of origin-destination (OD) pairs. The user mobility is defined by transfer probabilities of the flows and the handoff path rerouting algorithm is modeled by a transformation between the routing functions for traffic flows. The analysis shows that user mobility may cause temporal variations as well as smoothing effects on the network traffic. Using the flow network model, typical handoff path rerouting algorithms are evaluated through both analytical and experimental approaches. The evaluation methodology can be used for either redesigning the network topology for a given path rerouting algorithm or selecting a path rerouting algorithm for a given network topology under a specific mobile service scenario     

Artificial Neural Network Based Vertical Handoff Algorithm for Reducing Handoff Latency

One of the most challenging topics for next generation wireless networks is vertical handoff concept since several wireless technologies are assumed to cooperate. Plenty of parameters related to user preferences, application requirements, and network conditions, such as; data rate, service cost, network latency, speed of mobile, battery level, interference ratio and etc. must be considered in vertical handoff process along with traditional RSSI information. In this study, a new artificial neural network based handoff decision algorithm is proposed in order to reduce the handoff latency of smart terminal deployed in aforementioned wireless heterogeneous infrastructures. The prominent parameters data rate, monetary cost and RSSI information are taken as inputs of the developed vertical handoff decision system. Performance results of the proposed system are also compared with those of classical Multiple Attribute Decision Making method Simple Additive Weighting, and of some other artificial intelligence based algorithms. According to the results obtained, the proposed neural network based vertical handoff decision algorithm is able to determine whether a handoff is necessary or not properly, and selects the best candidate access network considering the abovementioned parameters. The results also show that, the neural network based algorithm developed significantly reduces the handoff latency while the number of handoffs, which is another vital performance metric, is still reasonable.     

Reducing signaling traffic in wireless ATM networks through handoff scheme improvement

We propose a new handoff call management scheme which reduces signaling traffic in wireless ATM networks and improves the efficiency of the virtual channel. Chaining followed by a make‐break algorithm is a suitable handoff scheme for various situations. In the chaining part of the scheme, a chain routing algorithm is studied and compared with the hop‐limiting scheme. When the algorithm is implemented in our scheme, it improves the performance of the existing scheme in call drop rates so as to reduce the signaling traffic in wireless ATM networks. Copyright © 2002 John Wiley & Sons, Ltd.     

分层多跳无线网中结合负载均衡的切换管理

该文主要研究分层多跳无线网络中的切换管理,提出一种新的用户切换管理算法和移动基站路由切换策略.在网络动态变化时,用户切换管理算法可以减少用户的切换次数,使用户负载分布均匀.移动基站路由切换策略则尽可能地从基站本地找出替代路由,可以在较小的开销下达到快速和无缝切换的目的.     

Heterogeneous Wireless Networks: Configuration and Vertical Handoff Management

Vertical handoff is one of the most important issues for the next generation heterogeneous wireless networks. However, in many situations, unbeneficial vertical handoffs occur across intersystem heterogeneous networks cause network performance degradation. Therefore, we propose a novel configuration architecture that can be deployed in the next generation of wireless networks. Second, we propose a predictive and adaptive Vertical Handoff Decision Scheme that optimizes the handoff initiation time as well as selection of the most optimal network. The proposed vertical handoff decision algorithm considers the technology type as well as the Signal to Interference Ratio (SIR), the Mobile Station (MS) velocity, the user preferences, the applications requirements and the terminal capabilities as the most important factors to make vertical handoff decision. In order to minimize handoff costs, the proposed decision algorithm uses the dwell timer concept. The handoff costs are analyzed in terms of unnecessary and unbeneficial handoffs rate.The simulation results show that the reduction of unnecessary handoffs proposed in our vertical handoff decision scheme reduces the handoff blocking probability, the packets loss rate and the handoff overhead     

改善用户体验的垂直切换算法

针对由超密集异构无线网络的超高动态性而引起掉话率不断增长的问题,并考虑到以往基于模糊逻辑相关垂直切换算法的较大时间开销,该文提出一种改善用户体验的垂直切换算法。首先利用5G核心访问和移动管理功能发现终端附近的所有候选网络,同时,利用自组织网络技术的环境感知能力,随时监测网络的运行状况,主动维护网络之间的邻居关系表。然后,引入动态模糊神经网络(DFNN)算法来执行切换判决,将获取到的网络参数数据作为该系统的输入,动态生成对垂直切换有效的规则库,经学习之后,计算得到输出判决值,从而为终端选择最佳接入网络。最后,仿真结果表明,该算法能够明显改善垂直切换过程中的掉话情况,降低切换失败概率。同时,与其他同类算法的时间消耗相比,该算法能够维持在一个较低的水平。     

A constrained MDP-based vertical handoff decision algorithm for 4G heterogeneous wireless networks

The 4th generation wireless communication systems aim to provide users with the convenience of seamless roaming among heterogeneous wireless access networks. To achieve this goal, the support of vertical handoff is important in mobility management. This paper focuses on the vertical handoff decision algorithm, which determines the criteria under which vertical handoff should be performed. The problem is formulated as a constrained Markov decision process. The objective is to maximize the expected total reward of a connection subject to the expected total access cost constraint. In our model, a benefit function is used to assess the quality of the connection, and a penalty function is used to model the signaling incurred and call dropping. The user’s velocity and location information are also considered when making handoff decisions. The policy iteration and Q-learning algorithms are employed to determine the optimal policy. Structural results on the optimal vertical handoff policy are derived by using the concept of supermodularity. We show that the optimal policy is a threshold policy in bandwidth, delay, and velocity. Numerical results show that our proposed vertical handoff decision algorithm outperforms other decision schemes in a wide range of conditions such as variations on connection duration, user’s velocity, user’s budget, traffic type, signaling cost, and monetary access cost.     

考虑负载均衡和用户体验的垂直切换算法

在超密集异构无线网络中,针对城区交通高峰期,大规模车载终端短时间聚集性移动引起的网络拥塞问题,该文提出一种考虑负载均衡和用户体验(LBUE)的垂直切换算法。首先,引入网络环境感知模型预测网络未来的拥塞程度,并提出一个融合自组织网络的网络架构,缓解网络拥塞。其次,定义业务适应度和负收益因子,并提出一种基于秩和比(RSR)的自适应切换判决算法,为用户筛选出当前环境下满意度最高的目标网络。实验结果表明,该算法能够有效降低终端接入网络的阻塞率和掉话率,实现网络间负载均衡并提升用户体验。     

Learning with handoff cost constraint for network selection in heterogeneous wireless networks

In heterogeneous wireless networks, network selection algorithms provide the user with the optimum network access choice. The optimal network is evaluated according to network parameters. Considering that the network parameters are dynamic and unavailable for the user in realistic heterogeneous wireless network environments, most existing network selection algorithms cannot work effectively. Learning‐based algorithms can address the problem of uncertain network parameters, while they commonly need considerable network handoff, resulting in unbearable handoff cost. In order to tackle the uncertainty of network parameters, we formulate the network selection problem as a multi‐armed bandit problem. Moreover, two online learning‐based network selection algorithms with a special consideration on reducing network handoff cost are proposed. By updating in a block manner, both algorithms achieve optimal logarithmic‐order regret and limited network handoff cost. The simulation indicates that the two algorithms can significantly reduce the network handoff cost and improve the transmission performance compared with existing algorithms, simultaneously. Copyright © 2014 John Wiley & Sons, Ltd.     

Sensor-based architecture for QoS provisioning and fast handoff management in WLANs

As wireless local area networks gain popularity from network access providers and customers, supporting multimedia applications becomes a crucial yet unresolved challenge. The need to maintain quality-of-service in the presence of bandwidth limitations, increasing traffic volume and user mobility entails radical rethinking in resource management design in WLANs. The unique capabilities of wireless sensor networks constitute a promising research direction to tackle these issues. In this paper, we present a new sensor-based resource management architecture for enhanced QoS provisioning and handoff management in WLANs. Through theoretical analysis and simulations, we show that the framework can maximize bandwidth utilization while satisfying applications’ QoS requirements and significantly reduce handoff latency.     

A seamless context-aware architecture for fourth generation wireless networks

The integration of a multitude of wireless networks is expected to lead to the emergence of the fourth generation (4G) of wireless technologies. Under the motivation of increasing the levels of user satisfaction while maintaining seamless connectivity and a satisfactory level of QoS, we design a novel cross-layer architecture that provides context-awareness, smart handoff and mobility control in heterogeneous wireless IP networks. We develop a Transport and Application Layer Architecture for vertical Mobility with Context-awareness (Tramcar). Tramcar presents a new approach to vertical handoff decisions, which is not exclusively based on network characteristics but also on higher level parameters which fall in the application and transport layers. Tramcar is tailored for a variety of different network technologies with different characteristics and has the ability of adapting to changing environment conditions and unpredictable background traffic. Furthermore, Tramcar allows users to identify and prioritize their preferences. Tramcar is a smart and practical system, which is more capable of dealing with 4G challenges. Simulation results demonstrate that Tramcar increases user satisfaction levels and network throughput under rough network conditions and reduces overall handoff latencies.     

Efficient call admission control for heterogeneous services inwireless mobile ATM networks

An efficient call admission control scheme for handling heterogeneous services in wireless ATM networks is proposed. Quality-of-service provisioning of jitter bounds for constant bit rate traffic and delay bounds for variable bit rate traffic is used in the CAC scheme to guarantee predefined QoS levels for all traffic classes. To reduce the forced handoff call dropping rate, the CAC scheme gives handoff calls a higher priority than new calls by reserving an appropriate amount of resources for potential handoff calls. Resource reservation in the CAC scheme makes use of user mobility information to ensure efficient resource utilization. Simulation results show that the proposed CAC scheme can achieve both low handoff call dropping rate and high resource utilization     

Aggregate History of User Mobility Pattern for QoS Provisioning in Multimedia Wireless Networks

Multimedia traffic is expected to be included in the next generation of wireless networks. As in wireline networks, the wireless network must also be capable of providing guaranteed quality-of-service (QoS) over the lifetime of mobile connections. In this paper, a bandwidth reservation scheme incorporating a user mobility prediction is proposed to manage the QoS of the networks. The mobility prediction scheme is developed based on the aggregate history of mobile users. Based on the mobility prediction, bandwidth is reserved to guarantee the uninterrupted handoff process. Simulation results demonstrate that the proposed scheme can guarantee the required QoS requirements in terms of handoff call dropping probability and new call blocking probability while maintaining efficient bandwidth utilization.     

A context‐aware handover decision based on user perceived quality of service trigger

Growing demands for pervasive and ubiquitous services over wireless mobile networks and evolution of such networks towards heterogeneous solutions have emphasized the necessity of more intelligent handoff decisions. The existing handoff management methods in the literature are mostly using signal strength measurements and other link quality evaluations not addressing the knowledge about context of mobile devices, users and networks. Recently, context‐aware handoff management has been considered as a novel candidate for fourth generation (4G) wireless technology. In this paper, user perceived quality of service has been considered in addition to traditional contexts such as user preferences, application requirements, network parameters and link quality for decision making. User perceived quality (UPQ) has been employed as a trigger source, in addition to link layer triggers which are emerged using media independent handover (MIH) event service. This paper presents a policy based mechanism for handoff decision making where fuzzy petri nets (FPNs) have been utilized as its evaluation algorithm. A case study has been provided by simulations to show the usability and user level satisfaction. Simulation results show superior performance in terms of UPQ, jitter and packet delivery measures. Copyright © 2009 John Wiley & Sons, Ltd.     

Adaptive Resource Management in Mobile Wireless Networks Using Feedback Control Theory

Emerging mobile wireless networks are characterized by significant uncertainties in mobile user population and system resource state. Such networks require adaptive resource management that continuously monitor the system and dynamically adjust resource allocations for adherence to the desired system performance requirements. We propose adaptive resource management technique based on control theory. The controller dynamically solves resource allocation problem using feedback control laws. In the base algorithm, the number of guard channels is dynamically adjusted by feeding back the current handoff call dropping probability. The base algorithm is then enhanced in two ways: feeding back the instantaneous number of handoff calls and by probabilistically implementing a fractional number of guard channels. We study the effects of parameter choices on the performance of the proposed algorithms using discrete event simulation. Simulation results indicate that the feedback controllers can guarantee the predetermined call dropping probability under a variety of traffic conditions, and so can utilize the scarce wireless resource efficiently by accepting more new calls.     

Call Level QoS Performance under Variable User Mobilities in Wireless Networks

The concept of adaptive admission control in cellular wireless networks ensures quality of service by reserving bandwidth for handoff calls. It is equally important in current second generation wireless systems as well as in the future IMT-2000 and UMTS systems. In order to ensure bounded call level QoS we propose to track the changes of the handoff call arrival rate and integrate this information in the admission algorithm. However, the handoff call arrival rate can vary when the new call arrival rate and/or user mobility vary. In our previous work we have analysed bandwidth reservation techniques needed to maintain a stable call level QoS when new call arrival rate is changing in a group, or groups, of wireless cells. This paper analyses bandwidth reservation techniques that are adaptive to the user mobility as well as to the changing new call arrival rate, and which can ensure stable call level QoS over a range of user mobilities. We also propose the technique to derive bandwidth reservation policy when the QoS characteristics over a range of user mobilities are given.     

Implied Costs for Multirate Wireless Networks

Implied costs for multirate wireless networks are calculated and their use is demonstrated for quantifying mobility, traffic load, call pricing, network optimization and for evaluating trade-offs between calls of different rates. User mobility is modeled by assigning call termination and call handoff probabilities. Fixed Channel Assignment (FCA) is used with priority for handoffs over new call arrivals by reserving a number of channels in all the cells. The performance measures used are new call blocking and handoff drop probabilities. The implied cost is calculated for the network net revenue, which considers the revenue generated by accepting a new call arrival into the network as well as the cost of a handoff drop in any cell. Simulation and numerical results are presented to show the accuracy of the model. The implied costs are used to suggest pricing techniques for different calls based on mobilities and bandwidth. Finally, a nonlinear constrained optimization problem is formulated to calculate the sum revenue for a given network by maximizing the net revenue using implied costs in a gradient descent algorithm. The implied cost analysis also shows that matching capacity distribution to not only exogenous traffic, but also to mobility can significantly increase revenue.     

Research on vertical handoff decision based on service history information and SINR for heterogeneous wireless networks

In this letter, we propose a SH (Service History) and SINR (Signal to Interference plus Noise Ratio) based PROMETHEE (SHS-PROMETHEE) vertical handoff (VHO) decision algorithm. An attribute matrix is constructed considering the SH information and the SINR in the source network and the equivalent SINR in the target network and so on. Handoff decision meeting multi-attribute QoS requirement is made according to the traffic features. The weight relation of decision elements is determined with LS method. Finally decision is made using PROMETHEE algorithm based on the attribute matrix and weight vector. The simulation results have shown that the SHS-PROMETHEE algorithm can reduce unnecessary handoffs and provide satisfactory vertical handoff performance.     

An Optimum Vertical Handoff Decision Algorithm Based on Adaptive Fuzzy Logic and Genetic Algorithm

Handoff decision making is one of the most important topics in wireless heterogeneous networks architecture as there are many parameters which have to be considered when triggering handoff and selecting suitable access point. More intelligent approaches which reckon user profiles, application requirements, and network conditions must be improved so that desired performance results for both user and network could be provided. In this paper we introduce a new adaptive vertical handoff decision making algorithm in which fuzzy membership functions are optimized by means of genetic algorithm. Genetic algorithm is an adaptive search technique based on natural selection and genetic rules. In addition to that, it takes places in various scientific applications and can be used to adjust the membership functions in fuzzy systems. The purpose of the study is to adjust the shape of fuzzy membership functions, properly, using genetic algorithm in order to achieve optimum handoff performance. The results show that, compared to the several different algorithms performance of the proposed approach with genetic algorithm is significantly improved for both user and network in terms of number of handoff while the other requirements are still satisfied.