HMIPv6中的自适应MAP选择算法

HMIPv6是一种有效的微移动管理协议。当移动节点进入一个域时,它会选择一个MAP进行注册。针对HMIPv6的特点,提出了一种支持负载分担的MAP选择算法。该算法利用MAP的优先级值来表征其负载情况,并根据MAP负载的变化,动态调整其优先级值。此外,还将速度因素引入了MAP协议开销的计算。模拟结果表明,该算法实现简单,开销管理和负载分担效果好。     

一种基于MN移动特征的MAP选取算法

在分级移动IPv6(HMIPv6)中,MAP选取的不合理往往会造成移动节点(MN)通信服务延时增加和MAP负载过于集中。该文综合考虑了MN的移动速度、移动轨迹等因素,提出一种新的基于MN移动特征的MAP选择算法。仿真结果表明,该算法能够根据MN 的运动特征和网络当前拓扑结构特点来选取移动代理MAP,有效地降低了MN的服务延时,更合理地利用了HMIPv6网络中的MAP资源。     

基于移动性能计算的MAP分级选择算法

研究分级移动IPv6协议中移动节点的移动性能和数据通信情况对移动锚点（MAP）选择机制的影响,将MAP按覆盖范围分成不同等级,提出了一种通过计算移动节点的移动性能和数据通信量,使移动节点按照移动性能的升降和通信量的变化,动态选择不同MAP级别的机制,达到减少移动节点的切换次数和均衡MAP之间负载的目的。模拟实验证明动态选择MAP级别的机制,减少了绑定更新消息,并在MAP的负载均衡方面取得良好的效果,达到了减少移动节点的切换次数和均衡MAP之间负载的目的,优化了移动节点的移动切换过程,是一个适应性很强的分级选择MAP的机制。     

移动IPV6越区切换管理模型的研究

移动IPv6为IPv6节点提供了在Internet中使用固定的家乡地址在不同子网中进行漫游通信的能力,然而当节点在网络间越区切换的时候,容易引起通信质量的下降或中断。针对标准移动IPv6和HMIPv6（层次化移动IPv6管理模型）对节点切换管理的不足,提出了一种新的越区切换管理模型方案,通过非固定的移动锚节点（MAP,Mobility Anchor Point）管理域,以及动态的MAP切换时机的选择,来达到降低切换行为的发生频率、保持切换发生时通信的连续性、使MAP负载均衡等目的。     

基于MN的移动轨迹的MAP实时调整策略

本文在分析HMIPv6协议基础上,指出HMIPv6协议中移动节点选择移动锚点策略的缺陷,通过分析MN本身的因素和MAP的因素,提出以MN（移动节点）的移动轨迹为依据的MAP（移动锚点）实时调整策略,在MN移动之前预先调整MAP,以解决移动节点在移动过程中出现的移动时延过长和丢包率高等问题;并通过实验仿真验证了该策略的可行性和实用性。     

一种平衡负载的分布式动态型微移动管理方案

目前微移动管理方案大多是采用分层的原则,在子域外设置一个外地管理代理（FMA）作为区域代理。移动主机（MH）在域内进行移动时只需向FMA进行注册,而对家乡代理（HA）透明。为了弥补MH数量过多而导致的FMA负载过大的缺陷,提出了一种平衡负载的分布式动态型微移动管理方案。该方案在网络中放置多个区域移动代理来实现分布式的域内主机移动管理,并采用一种由网络根据自身的负载情况动态地选择区域移动代理的算法。该算法有效避免了传统方案中FMA在MH数量过多时负载过大的问题,且没有对网络拓扑结构和区域移动代理的位置做任何强制性要求。分析和仿真均表明,当主机数量快速递增时网络的负载平衡状况得到了改善。     

三层HMIPv6架构下的MAP选择算法

分析了HM IPv6协议现有MAP选择算法的不足,提出了一种改进的MAP选择算法。该算法能根据MN的移动速度快慢来选择不同层次的MAP,并通过动态配置MAP暂存器容量,有效地解决了因MN移动过快而造成的数据包丢失现象。仿真结果证明了该算法的优越性。     

分级移动IPv6中一种新的自适应MAP选择算法*

分级移动IPv6中存在单点故障和负荷集中问题。提出一种基于分布式MAP结构的自适应MAP选择算法,综合考虑移动节点的当前速度、会话到达率、MAP负荷及距离等因素,以MN注册后将产生的移动性管理信令开销最小为依据进行选择。仿真结果表明,自适应MAP选择算法能够根据移动节点和网络的当前特性优化地选择不同的MAP进行注册,使移动性管理信令开销最小,具有较好的负荷分担效果,并一定程度上增强了分级结构的鲁棒性。与最远/近MAP选择方案相比,自适应MAP选择算法能够提高网络的吞吐量及减少平均切换时延。     

基于F-HMIPv6的MAP自适应选择算法

移动IPv6提供了移动节点在不同子网中漫游通信的能力,同时为了缩短切换延迟和减少丢包率,层次化移动IPv6模型、快速切换机制及F-HMIPv6相继被提出.在层次化移动IPv6模型和F-HMIPv6中引入了MAP来缩短绑定更新延迟,但目前还没有较完善的MAP选择算法被提出.提出了一种自适应的MAP选择算法,该算法能根据移动节点的移动特点来选择合适的MAP.     

基于动态负载均衡的层次性移动IPv6路由优化方案

针对层次性移动IPv6网络负载过重时存在的MAP负载分配失衡的问题,提出一种动态的MAP负载调度方案。方案中,MAP通过提出的计算模型,以带宽使用情况作为参数计算当前的负载。当检测到网络负载分配失衡时,根据MN的移动趋向调度MAP之间的负载,使网络中的计算资源合理分配,优化网络性能。仿真结果表明,该方案能有效地改善网络的整体服务质量,降低通信时延和减少通信过程中的丢包率。     

On a moving direction pattern based MAP selection model for HMIPv6 networks

In a large-scale mobile IPv6 network, usually there are several coexisting mobility anchor points (MAPs) for networking robustness and traffic sharing. Therefore, it is a challenging issue for an arriving mobile node to choose the most appropriate MAP to bind. This task must be carried out by considering the issues of load balancing, binding update and packet delivery cost minimization. This paper proposes a novel MAP selection scheme for hierarchical mobile IPv6 networks to allow a mobile node to discover the most appropriate MAP when there are multiple coexisting MAPs. This scheme is an enhancement to the adaptive MAP selection scheme. The proposed scheme improve the overall performance due to the consideration of the movement (direction) pattern of mobile nodes. Simulation results show that this scheme outperforms the existing cost models in terms of total binding update and packet delivery costs, ensuring a level of load balance similar to adaptive MAP selection scheme.     

A performance comparison of mobility anchor point selection schemes in Hierarchical Mobile IPv6 networks

Hierarchical Mobile IPv6 (HMIPv6) introduces a mobility anchor point (MAP) that localizes the signaling traffic and hence reduces the handoff latency. In addition to processing binding update messages from mobile nodes (MNs) on behalf of MNs’ home agents (HAs), the MAP performs data traffic tunneling destined to or originated from MNs, both of which will burden the MAP substantially as the network size grows. To provide scalable and robust mobile Internet services to a large number of visiting MNs, multiple MAPs will be deployed. In such an environment, how to select an appropriate MAP has a vital effect on the overall network performance. In this paper, we choose four MAP selection schemes: the furthest MAP selection scheme, the nearest MAP selection scheme, the mobility-based MAP selection scheme, and the adaptive MAP selection scheme. Then, we compare their performances quantitatively in terms of signaling overhead and load balancing. It can be shown that the dynamic schemes (i.e., the mobility-based and the adaptive MAP selection schemes) are better than the static schemes (i.e., the furthest and the nearest MAP selection schemes), since the dynamic schemes can select the serving MAP depending on the MN’s characteristics, e.g., mobility and session activity. In addition, the adaptive MAP selection scheme achieves low implementation overhead and better load balancing compared with the mobility-based MAP selection scheme.     

一种新的基于分级移动IPv6的移动性管理方案*

提出了一种基于分级移动IPv6 的自适应移动性管理方案,该方案重点研究切换过程中的MN和MAP的操作。当MN进入一个新的子网内时,它可以利用这种自适应MAP选择算法来选择一个合适的MAP进行注册,同时,MAP可以综合考虑当时的业务情况和其他相关信息自适应地改变它在分级结构中的位置。这就使得MAP可以自适应地改变它的管理域,使得分级移动IP的体系结构是可伸缩的。     

Dynamic partitioning of IP-based wireless access networks

In HMIPv6-based network architecture, Mobile Nodes (MNs) generate excessive signalling overhead, where they move at borders of different Mobility Anchor Point (MAP) domains. Furthermore all the traffic originated or destined to MNs must traverse through the MAPs. Thus, MAPs are potential points of bottlenecks in the network, as the traffic load grows. To mitigate these drawbacks, division of the access network domain into overlapping partitions (MAP domains) is proposed in order to provide more scalable and robust mobile services. Partitioning problem is an NP-hard problem. In this paper, we propose three, heuristic, Kernighan–Lin based partitioning algorithms to minimise the total inter-area handover rate as well as bottleneck effect of MAPs. Our proposed algorithms adopt the proposed scheme of multiple MAP deployment per domain, where each AR can be assigned to more than one MAP in the same level of hierarchy. The proposed algorithms dynamically adapt to traffic and mobility changes. We devise a cost function for each algorithm and formulate optimisation problems, accordingly. Then we evaluate the performance of the algorithms in terms of dynamic adaptation to mobility and load changes, and also to the degree of load-balance, and mean amount of bandwidth blocking and dropping rates. A simulation evaluation and comparison study with Sanchis algorithm, demonstrates that the proposed overlapping scheme outperforms the conventional non-overlapping scheme. Furthermore, all proposed algorithms obtain improved performance implementation of Sanchis algorithm.     

Adaptive Decentralized Output-Constrained Control of Single-Bus DC Microgrids

A single-bus DC microgrid can represent a wide range of applications. Control objectives of such systems include high-performance bus voltage regulation and proper load sharing among multiple distributed generators (DGs) under various operating conditions. This paper presents a novel decentralized control algorithm that can guarantee both the transient voltage control performance and realize the predefined load sharing percentages. First, the output-constrained control problem is transformed into an equivalent unconstrained one. Second, a two-step backstepping control algorithm is designed based on the transformed model for bus-voltage regulation. Since the overall control effort can be split proportionally and calculated with locally-measurable signals, decentralized load sharing can be realized. The control design requires neither accurate parameters of the output filters nor load measurement. The stability of the transformed systems under the proposed control algorithm can indirectly guarantee the transient bus voltage performance of the original system. Additionally, the high-performance control design is robust, flexible, and reliable. Switch-level simulations under both normal and fault operating conditions demonstrate the effectiveness of the proposed algorithm.