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.     

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.     

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。     

QoS-aware dynamic MAP selection schemes in HMIPv6 networks

We consider a dynamic Mobile Anchor Point (MAP) selection problem when there are both real-time and non-real time sessions in a Hierarchical Mobile IPv6 (HMIPv6) network. We propose schemes in which Mobile Nodes (MNs) holding real-time sessions register with the root MAP in a hierarchy of MAPs to reduce the inter-domain handovers while those with non-real time sessions select one either to balance the load or to reduce handover frequencies.     

Load-balanced mesh router migration for wireless mesh networks

Load-balancing among domains in a wireless mesh network (WMN) is normally achieved by changing the Internet attachment of mesh routers (MRs) that carry the traffic from mobile stations (MSs). The greediness of load-balancing algorithms may force MRs to frequently change their Internet attachments, and thus degrade network performance due to inter-domain mobility of the associated MSs. In this paper, we discuss the negative impact on the performance of MSs’ mobility, due to inter-domain reassignment of MR. A MR migration scheme is proposed to achieve a tradeoff between load-balancing and inter-domain reassignment of MR. The proposed load-balancing scheme for WMNs includes: an initialization procedure to divide a WMN into domains, and a load adjustment procedure to rebalance the traffic load among the neighboring domains when required. We also provide a framework for handling inter-domain mobility in support of multi-hop communication using the Multi-hop cellular IP. Our simulation results show that the proposed protocol effectively controls MR’s change in connectivity as well as MS’s mobility.     

HMIPv6的LT-TMAP快速切换方案

分层移动IPv6(HMIPv6)作为移动IPv6的一种改进技术用于解决宏移动和微移动之间的切换管理问题。针对移动锚点(MAP)的选取不合理造成移动节点服务时延增加、MAP负载过于集中等问题,提出HMIPv6的授权给临时移动锚点(LT-TMAP)快速切换方案,在理论上描述该实现过程。仿真结果表明该方案能够更有效地利用网络的MAP资源,具有更好的实时性,提高了切换效率。     

基于流量模式和网络拓扑的网关部署算法

多并发流所引起的网络负载不均衡是无线网状网(wireless Mesh network,WMN)面临的一个挑战,部署网关是一种能缓解竞争节点负载的可行方案.针对这一问题,提出基于流量模式和网络拓扑的启发式网关部署算法.该算法利用节点在多种流量模式下所承载流量的平均值来估算节点的网络负载,并基于节点的网络负载和位置来选择网关,再根据特定的计算,分配节点给已知网关所管理的簇.实验结果表明,在不同流量模式和网络资源配置下,该算法均能有效地提高网络吞吐量、降低端到端延迟、减少路径长度.     

基于自相似网络流的多维QoS路由策略研究

提出了一种依据网络自相似的特征,在扩展的Bellman-Ford算法的基础上构造了一种基于自相似网络流的QoS路由算法,该算法具有根据历史路由信息来指导路由的特点,避免了由于以往确定性路由算法的路由聚集性的不足。实验结果表明,该算法具有较好的性能指标,能自适应网络,使其负载均衡,同时具有较少的处理与协议开销。     

基于应用层流量优化的中继路径选择方案

基于网络层路由协议的缺省单一路径难以满足高带宽应用的端到端传输需求,多径传输是一种有效方式。在基于应用层中继的多径传输系统的基础上,提出基于应用层流量优化的中继路径选择方案：借助于应用层流量优化机制,提出中继路径选择过程中遵循的规则,提出基于运营商定义域的最优中继路径生成算法,为数据传输分配优质的中继路径,同时在运营商定义域之间以及中继服务转发器之间保持负载均衡。仿真结果表明,提出的方案在选择优质中继路径方面具有较优性能,同时能够灵活地均衡运营商定义域之间的负载。     

Dynamic load balancing in IP-over-WDM optical burst switching networks

In this paper, we consider the problem of dynamic load balancing in wavelength division multiplexing (WDM)-based optical burst switching (OBS) networks. We propose a load balancing scheme based on adaptive alternate routing aimed at reducing burst loss. The key idea of adaptive alternate routing is to reduce network congestion by adaptively distributing the load between two pre-determined link-disjoint alternative paths based on the measurement of the impact of traffic load on each of them. We develop two alternative-path selection schemes to select link-disjoint alternative paths to be used by adaptive alternate routing. The path selection schemes differ in the way the cost of a path is defined and in the assumption made about the knowledge of the traffic demands. Through extensive simulation experiments for different traffic scenarios, we show that the proposed dynamic load balancing algorithm outperforms the shortest path routing and static alternate routing algorithms.     

基于系统最优的航空信息网络流量均衡方案

随着未来空战的需求,当前的航空信息网络逐渐暴露出种种不足,如针对不同作战任务网络应具备较强的差异化服务能力、网络中各平台节点间的信息不能得到及时共享、网络规模的增加导致网络中流量发生拥塞和网络架构更加臃肿等问题,而SDN的出现较好地解决了这一问题,通过将SDN与航空信息网络相结合,创新性地提出了一种软件定义航空信息网络。文中面向航空信息网络中的流量传输问题,针对网络中流量分布不均衡的情况,提出了一种基于系统最优(System Optiminzation,SO)的流量负载均衡方案。文中通过构建混合SDN/IP航空信息网络模型,在网络中利用SDN控制器的集中控制特性使SDN节点对业务流量进行多路径转发,进而实现对其调度优化,并定义链路拥塞系数和SDN数据流,以链路利用率最小为目标,利用Wardrop均衡理论分析求解,参照系统最优原则,并提出一种基于SO的流量均衡分配算法。为体现所提算法的优越性,仿真中同时设置了SMR算法和MSR算法,结果表明SOA算法在业务完成率与业务吞吐量方面均有显著提升,如在大规模网络中,MSR和SMR算法的业务完成率分别为58.4%和52.2%,而SOA算法的业务完成率大约为70.5%,性能分别提升了20.7%和35.1%,因此所提算法对网络中流量的转发实现了较好的处理,为解决未来航空信息网络下的流量传输问题提供了一种新思路。     

考虑约束参数切换的小蜂窝LTE移动负载自适应均衡

针对因用户设备移动性和小区覆盖率造成的网络负载周期性不平衡问题,引入小蜂窝网络以支持高数据率服务和密集部署,提出一种自适应网络负载状态并考虑负载估计的小蜂窝网络移动性负载平衡算法。该算法根据过载单元和相邻单元调整进行参数切换,其资源利用取决于信号质量和所连接用户设备在长期演进网络(LTE)中的流量需求,并定义资源块利用率作为单元负载的度量,根据网络负载情况使用自适应阈值来确定过载单元。为避免性能振荡,考虑移动负载对网络的影响,进行负载均衡过程设计。最后通过系统级仿真评价了该算法在不同环境下的性能,仿真结果表明,该算法在网络间提供了更均衡的负载(即小区间的标准差较小),比以前的算法具有更高的网络吞吐量。     

基于负载均衡的VEC服务器联合计算任务卸载方案

在车载边缘计算(Vehicular Edge Computing,VEC)网络中,车辆计算资源受限导致无法处理海量的计算任务,需要将车载应用产生的计算任务卸载到VEC服务器上进行处理。但车辆的移动性和区域部署的差异性易导致VEC服务器负载不均衡,造成了计算卸载效率和资源利用率降低。为解决该问题,提出一种计算卸载和资源分配方案,以使用户效用最大化。将用户效用最大化问题转化成服务器选择决策和卸载比例与计算资源分配联合优化两个子问题,在此基础上设计基于匹配的服务器选择决策算法和基于Adam梯度优化法的计算任务卸载比例与资源分配联合优化算法,并对上述两种算法进行联合迭代,直至收敛,从而得到近似最优解以达到负载均衡。仿真结果表明,相比最近卸载方案和预测卸载方案,该方案能有效降低计算任务处理时延和车辆能耗,增大车辆效用,促进负载均衡。     

基于区域的无线传感器网络密钥管理

要密钥分配是无线传感器网络中极具挑战性的安全问题之一．目前提出的解决方法是采用密钥预分配策略，给每个节点分配多个密钥，如Eschenauer和Gligor提出的随机密钥预分配方案（R—KPS）．随机密钥预分配方案没有利用节点的部署和位置信息，在许多应用场合中，部署和位置信息能被用于改善网络性能．在R—KPS中，每个节点有可能成为其它任何节点的邻居，所以节点必须从同一密钥池中选取密钥．如果能把网络划分为多个区域，则同一区域内和相邻区域间的节点更有可能成为邻居．文章提出一种利用已知区域信息的密钥预分配方案，相比随机密钥预分配方案，能提高网络的连通性，减小节点所需存储空间，并能增强网络抗攻击能力．最后利用上述区域信息提出一种不借助定位设备的节点定位算法，此算法实现简单，适用于定位精度要求不高的场合．     

Design and performance analysis of an inductive QoS routing algorithm

Routing mechanism is key to the success of large-scale, distributed communication and heterogeneous networks. Consequently, computing constrained shortest paths is fundamental to some important network functions such as QoS routing and traffic engineering. The problem of QoS routing with multiple additive constraints is known to be NP-complete but researchers have been designing heuristics and approximation algorithms for multi-constrained paths algorithms to propose pseudo-polynomial time algorithms. This paper introduces a polynomial time approximation quality of service (QoS) routing algorithm and constructs dynamic state-dependent routing policies. The proposed algorithm uses an inductive approach based on trial/error paradigm combined with swarm adaptive approaches to optimize lexicographically various QoS criteria. The originality of our approach is based on the fact that our system is capable to take into account the dynamics of the network where no model of the network dynamics is assumed initially. Our approach samples, estimates, and builds the model of pertinent aspects of the environment which is very important in heterogeneous networks. The algorithm uses a model that combines both a stochastic planned pre-navigation for the exploration phase and a deterministic approach for the backward phase. Multiple paths are searched in parallel to find the K best qualified ones. To improve the overall network performance, a load adaptive balancing policy is defined and depends on a dynamic traffic path probability distribution function. We conducted a performance analysis of the proposed QoS routing algorithm using OPNET based on a platform simulated network. The obtained results demonstrate substantial performance improvements as well as the benefits of learning approaches over networks with dynamically changing traffic.     

Learning non-cooperative game for load balancing under self-interested distributed environment

Resources in large-scale distributed systems are distributed among several autonomous domains. These domains collaborate to produce significantly higher processing capacity through load balancing. However, resources in the same domain tend to be cooperative, whereas those in different domains are self-interested. Fairness is the key to collaboration under a self-interested environment. Accordingly, a fairness-aware load balancing algorithm is proposed. The load balancing problem is defined as a game. The Nash equilibrium solution for this problem minimizes the expected response time, while maintaining fairness. Furthermore, reinforcement learning is used to search for the Nash equilibrium. Compared with static approaches, this algorithm does not require a prior knowledge of job arrival and execution, and can adapt dynamically to these processes. The synthesized tests indicate that our algorithm is close to the optimal scheme in terms of overall expected response time under different system utilization, heterogeneity, and system size; it also ensures fairness similar to the proportional scheme. Trace simulation is conducted using the job workload log of the Scalable POWERpallel2 system in the San Diego Supercomputer Center. Our algorithm increases the expected response time by a maximum of 14%. But it improves fairness by 12–27% in contrast to Opportunistic Load Balancing, Minimum Execution Time, Minimum Completion Time, Switching Algorithm, and k-Percent Best.     

Termite-hill: Performance optimized swarm intelligence based routing algorithm for wireless sensor networks

A wireless sensor network (WSN) is a large collection of sensor nodes with limited power supply, constrained memory capacity, processing capability, and available bandwidth. The main problem in event gathering in wireless sensor networks is the formation of energy-holes or hot spots near the sink. Due to the restricted communication range and high network density, events forwarding in sensor networks is very challenging, and require multi-hop data forwarding. Improving network lifetime and network reliability are the main factors to consider in the research associated with WSN. In static wireless sensor networks, sensors nodes close to the sink node run out of energy much faster than nodes in other parts of the monitored area. The nodes near the sink are more likely to use up their energy because they have to forward all the traffic generated by the nodes farther away to the sink. The uneven energy consumption results in network partitioning and limit the network lifetime. To this end, we propose an on-demand and multipath routing algorithm that utilizes the behavior of real termites on hill building termed Termite-hill which support sink mobility. The main objective of our proposed algorithm is to efficiently relay all the traffic destined for the sink, and also balance the network energy. The performance of our proposed algorithm was tested on static, dynamic and mobile sink scenarios with varying speed, and compared with other state-of-the-art routing algorithms in WSN. The results of our extensive experiments on Routing Modeling Application Simulation Environment (RMASE) demonstrated that our proposed routing algorithm was able to balance the network traffic load, and prolong the network lifetime.     

多蚁群算法的网络负载动态均衡方法

针对网络资源管理中的负载均衡与优化问题,提出一种多蚁群网络负载动态均衡方法,采用网络流量工程理论中拥塞控制机制实现信息素随网络流量动态释放与更新。算法通过蚁群间信息素的动态相互作用（蚁群内信息素相互增强,蚁群间信息素相互削弱）,将代表网络负载的蚂蚁合理分配到可用路径,避免蚂蚁集中到特定路径而造成网络拥塞。实验结果表明,通过路径信息素控制能够实现网络负载均衡,有效提高网络在路径延时、平均带宽利用率和平均丢包率方面的性能。     

WMN中的干扰避免部分重叠信道分配算法

针对无线mesh网络(wireless mesh networks,WMN)中存在的信道干扰问题,提出一种基于部分重叠信道(partially overlapping channels,POC)的负载平衡且干扰避免的信道分配算法。通过基于Huffman树的通信接口分配方法连接邻居节点的接口;根据网络干扰情况,对链路进行迭代信道分配,使用静态链路调度保证网络连接;利用启发式算法优先为重要程度较高的链路分配无干扰时隙,对链路调度进行优化。仿真结果表明,在具有混合流量的WMN中,所提算法可以显著提升网络吞吐量,降低网络干扰与平均丢包率,改善网络性能。