车载异构网中基于最优停止算法的垂直切换

目前,传统的车载Ad Hoc网络正朝着车载异构网发展;这就迫切需要为车辆用户提供一个高效、智能的网络接口进行切换,以满足其QoS要求。在本文中,我们针对车载异构网络存在的切换问题提出了一个优化算法,该策略整合了多个指标,包括价格成本、可用带宽和数据传输延迟等。利用最优停止理论,能最大限度提高用户满意度。仿真结果表明,基于最优停止的策略是可行的。     

一种基于移动趋势量化的多属性垂直切换判决算法

由于对终端移动趋势的不明确,基站容易盲目发起切换,并导致较高的切换失败率。该文在LTE-WiMAX网络构成的异构无线网络环境下对现有的垂直切换算法进行了优化。该优化算法考虑了终端移动趋势,利用趋势量化参数来推断终端最终的目标区域,解决已有判决算法中存在的不必要切换过多的问题,提高切换成功率。在衰落信道下的计算机仿真结果表明,该优化算法可以减小切换中的切换失败率,从而提高网络的切换性能。     

基于SCTP的异构网垂直切换研究

本文首先对异构网中的移动性管理进行介绍,对本文采用的传输层协议SCTP协议进行详细分析,在现有的基于SCTP协议的垂直切换方案上进行考虑,提出了一种基于SCTP协议的软切换方案,通过ns2仿真可以知道:当切换到带宽大的网络时分组丢失将比切换到带宽小的网络分组丢失严重,同时由于传输层协议的慢启动,通信开始和切换过程的传输速率很低。     

异构无线网络垂直切换技术综述

垂直切换是多网融合的基础,是实现异构网络互通、支持不同接入方式无缝衔接的核心技术,目前正在受到业界的重点关注,并成为学术界研究的热点问题。随着无线移动通信技术向接入多元化、网络一体化和应用综合化的方向发展,各种蜂窝移动接入、宽带无线接入和固定接入将共同接入基于IP的统一核心网络,通过网络间的垂直切换,支持用户的移动性和移动过程中业务的连续性。首先给出了垂直切换的定义和基本概念,介绍了垂直切换的分类和基本流程,随后详细论述垂直切换的切换判决和切换执行2个环节。针对切换判决,总结了现有判决算法,重点评述各代表算法工作原理并剖析论其特点和存在的不足。针对切换执行,详述了现有垂直切换执行机制的工作原理和适用场景,并分析其优缺点。最后,对未来垂直切换技术的研究方向进行了展望。     

异构网络下一种切换判决算法

基于传统切换算法的不足,提出了GPS辅助条件下位置知晓切换判决算法,实现异构网的切换。该算法综合考虑了网间切换的时延和信令负荷等问题,并对此算法进行了仿真验证。仿真结果表明,该算法性能相对于传统纯粹基于接收功率的切换算法有显著提升。     

一种新的无线异构网络的自适应垂直切换算法

针对当前无线异构网络融合技术中的垂直切换机制,提出了一种以平均接收信号强度为评价指标,并由此指标判断可能的运动趋势的自适应垂直切换算法。仿真结果表明:相比于传统的固定门限的平均接收信号强度垂直切换算法,提出的方法能较好地预测并提前触发该发生的切换,改善切换性能。     

一种基于异构网络的自适应垂直切换算法

提出一种基于WSN与WLAN异构网络环境下无缝移动通信的垂直切换算法。该算法针对日益普及的传感器网络自身特点与室内应急通信应用的特殊性,提出网络选取优先级参数。针对传感器网络在应急通信等特殊场合的应用．制定了专门的切换判决策略。实验分析表明,该算法可以一定程度地提高通信网络对现场场景变化的适应程度,满足室内环境下异构网络通信的需求。     

无线异构网络的垂直切换

传统意义上的水平切换算法已经在同构网络中得到很好的研究和应用,而随着多种无线异构网络的出现,下一代网络必须支持垂直切换技术以保证用户从一种类型的网络切换到另一种类型的网络时仍然保持连接。由于切换算法所需考虑因素的多样性和算法本身的复杂性,有必要对现有文献中的网络切换类型、切换因素、切换算法进行了归纳总结,并对垂直切换算法进行比较,指出未来切换算法的研究方向。     

基于强化学习的异构网络垂直切换方法

网络切换技术不仅可以保证用户的网络连接,同时能够以较强的信号传输网络数据。网络切换技术的性能对网络服务质量(quality of service, QoS)的影响至关重要。然而,现有的切换算法多数存在严重的乒乓效应,这不仅造成网络资源的严重浪费,还会损害用户的QoS。为此,提出了一种基于强化学习的异构网络垂直切换方案,主要从触发切换、网络选择及判决切换等方面进行优化。在触发切换时将垂直切换考虑成必要切换和择优切换,通过Q-Learning（QL）算法在选择网络时优化垂直切换;然后以QoS为条件,在判决切换时加入驻留定时器,从多角度减少用户切换次数,降低乒乓效应对异构网络垂直切换的影响。仿真结果表明,基于强化学习的异构网络垂直切换方法可以在保证QoS的条件下有效减少用户切换网络的次数,短时间内频繁切换的情况也有所改善,降低了乒乓效应的影响。     

无线异构网络的垂直切换判决算法

传统上的水平切换处理方法已经应用在同一接入技术的网络中（如无线蜂窝网络）。随着多种异构无线网络的出现,下一代网络必须支持垂直切换技术以保证用户从一个网络切换到内一个网络时仍然保持连接,垂直切换作为多网融合的基础,受到了学术界和工业界的广泛关注。对使用层次分析法进行垂直切换技术的工作原理及应用环境进行了分析,提出同时使用多种切换技术以解决不同环境下的切换问题。     

异构网络中基于终端决策的通用垂直切换算法

垂直切换是异构网络中的关键技术,目前已有的垂直切换算法大多是针对特定的网络或切换过程的某个环节,提出一种与网络类型无关的通用垂直切换算法,仿真结果表明该算法在支持多任务,有效利用能量方面比传统方法有很大的改进.     

Group vertical handoff management in heterogeneous networks

Traditional vertical handover schemes postulate that vertical handovers (VHOs) of users come on an individual basis. This enables users to know previously the decision already made by other users, and then the choice will be accordingly made. However, in case of group mobility, almost all VHO decisions of all users, in a given group (e.g., passengers on board a bus or a train equipped with smart phones or laptops), will be made at the same time. This concept is called group vertical handover (GVHO). When all VHO decisions of a large number of users are made at the same time, the system performance may degrade and network congestion may occur. In this paper, we propose two fully decentralized algorithms for network access selection, and that is based on the concept of congestion game to resolve the problem of network congestion in group mobility scenarios. Two learning algorithms, dubbed Sastry Algorithm and Q‐Learning Algorithm, are envisioned. Each one of these algorithms helps mobile users in a group to reach the nash equilibrium in a stochastic environment. The nash equilibrium represents a fair and efficient solution according to which each mobile user is connected to a single network and has no intention to change his decision to improve his throughput. This shall help resolve the problem of network congestion caused by GVHO. Simulation results validate the proposed algorithms and show their efficiency in achieving convergence, even at a slower pace. To achieve fast convergence, we also propose a heuristic method inspired from simulated annealing and incorporated in a hybrid learning algorithm to speed up convergence time and maintain efficient solutions. The simulation results also show the adaptability of our hybrid algorithm with decreasing step size‐simulated annealing (DSS‐SA) for high mobility group scenario. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive vertical handoff algorithm in heterogeneous networks

The integration of cellular network (CN) and wireless local area network (WLAN) is the trend of the next generation mobile communication systems, and nodes will handoff between the two kinds of networks. The received signal strength (RSS) is the dominant factor considered when handoff occurs. In order to improve the handoff efficiency, this study proposes an adaptive decision algorithm for vertical handoff on the basis of fast Fourier transform (FFT). The algorithm makes handoff decision after analyzing the signal strength fluctuation which is caused by slow fading through FFT. Simulations show that the algorithm reduces the number of handoff by 35%, shortens the areas influenced by slow fading, and enables the nodes to make full use of WLAN in communication compared with traditional algorithms.     

An efficient vertical handoff scheme for microcellular and macrocellular interworking

The next generation wireless network environments increasingly become integrated to support anywhere, anytime connectivity for various applications like multimedia, full‐motion video and high data rates with appropriate quality of service (QoS). With these emerging needs, interworking of microcellular and macrocellular networks has been accompanied by service providers. However, these networks have different technologies, which make efficient vertical handoff a challenging issue. In this study, an efficient vertical handoff scheme (EVHS) for interworking between microcellular and macrocellular networks is proposed and analyzed. The handoff decision criteria of the proposed scheme include crucial features like user mobility, network conditions, pricing issues, and user preferences in addition to the received signal strength (RSS). EVHS ensures the selection of the most appropriate network in terms of cost and acceptable QoS according to users' preferences. The results show that EVHS scheme outperforms other proposed schemes in the literature in terms of incompletion probabilities, grade of service (GoS) and cost without causing degradation in system utilization. Besides, although EVHS scheme is mainly intended for user satisfaction, the results show that it does not cause a significant degradation in the revenue of the service provider. Copyright © 2009 John Wiley & Sons, Ltd.     

多网络共存下基于贝叶斯的垂直切换算法

针对目前的垂直切换技术普遍不能满足多网络下的切换问题,提出了一种改进的基于贝叶斯决策的垂直切换算法。首先根据接入终端网络的信号强度、网络负载、误码率和网络阻塞率以及用户业务对网络的实际需求偏好建立多条件相关的切换概率分布,计算出先验切换概率;然后通过贝叶斯决策算法计算出后验概率来进行判决比较,从而选取最优的接入网络。仿真结果表明,该算法不仅能有效地实现不同接入技术之间的垂直切换,从而减少不必要的切换,提高了切换成功的概率,而且还能在维持各网络平均负载达到30%~40%时减轻通信热点的阻塞情况,为用户提供更优的服务质量。     

An enhanced TCP for upward vertical handoff in integrated WLAN and cellular networks

The integration of wireless local area networks (WLANs) and third generation (3G) cellular networks has been recently a subject of great interest, mainly aimed at augmenting cellular networks with high‐rate data services by WLANs in hotspots. The complementary characteristics of 3G cellular networks and 802.11 WLANs are expected to offer the best of both technologies. On the other hand, the drastically different characteristics of both networks could be a serious obstacle to providing seamless mobility in the integrated WLAN and cellular networks. In particular, mobile users suffer from a drastic decrease in data rate after a vertical handoff from a WLAN to a 3G cellular network. However, current TCP congestion control cannot adapt to the change in the data rate after the vertical handoff, resulting in significant throughput degradation. Thus, we propose a novel TCP scheme to enhance the throughput when a vertical handoff occurs from a WLAN to a cellular network. For the proposed scheme, the throughput performance is investigated via analytic modeling and simulation. Copyright © 2008 John Wiley & Sons, Ltd.     

车联网中基于贝叶斯决策的垂直切换方法研究

车辆需要在车联网的异构无线网络环境下进行垂直切换,针对垂直切换技术普遍不能支持 WAVE, WiMAX和3G cellular间的垂直切换这一问题,提出了一种基于贝叶斯决策的垂直切换算法。首先,根据接入网络的信号强度、传输速率、误码率和网络阻塞率以及车辆终端的速度和运动趋势建立多条件相关的切换概率分布,计算出切换先验概率;然后通过贝叶斯决策算法计算后验概率并进行决策分类,从而选取最优网络接入。仿真实验结果表明,该算法不仅有效地实现WAVE,WiMAX和3G cellular无线接入技术之间的垂直切换,而且避免了乒乓效应,保证了网络及时更新。     

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.