A data distribution scheme for VANET based on fountain code

Data dissemination is one of the applications used to provide infotainment to the end-users in vehicular ad hoc networks (VANET). During this process, the vehicles receive the data broadcast by the RoadSide Unit (RSU). However, it is difficult for vehicles to collect the complete content within the communication range of one RSU when the vehicle moves at a high speed and the amount of broadcast data is large. To solve this problem, a multi-RSU cooperative data distribution scheme based on fountain code (MRFC) is proposed in this paper. The source data are encoded by fountain code and poured into the VANET by multiple cooperative RSUs, then the vehicles in the area share data packets through the V2V resource compensation method, so that all vehicles can obtain enough encoded packets to reconstruct the source data. To improve channel resource utilization and reduce delivery delays, the RSUs use fuzzy logic to determine the number of fountain code packets according to their locations, the speed and density of surrounding vehicles. The experimental results show that on the premise of ensuring the delivery rate, the proposed scheme can reduce the delivery delay by 30–50%, and achieve a significant improvement in performance.

     

RSU-based message authentication for vehicular ad-hoc networks

Message authentication that ensures a message is genuine and verifies the source of the sender is a key issue in vehicular ad hoc networks (VANETs). Because messages may provide life-critical traffic information or emergency messages transmitted by unfamiliar sources. Because the vehicle in a VANET transmits messages in real-time in a high-mobility environment, traditional PKI security schemes are not suitable for VANET. The use of roadside units (RSUs) makes message authentication in VANET easy, but it also causes two problems and needed to be solved: how to authenticate messages transmitted between two different RSU ranges, and how to hand off messages for the vehicles moving across different RSU communication ranges. This paper proposes a comprehensive message authentication scheme that enables the message authentication within intra and between inter RSU ranges and hand-off between different RSUs. The proposed scheme balances the overhead for computation and communication with security against attacks. Efficiency analysis and comparison with related works demonstrate that the proposed scheme is a superior message authentication method for VANET.     

面向VNDN的兴趣包洪泛攻击检测

在车载命名数据网络(VNDN)中,兴趣包洪泛攻击(IFA)通过发送大量恶意兴趣包占用甚至耗尽网络资源,导致合法用户的请求无法被满足,严重危害了车联网的运行安全.针对上述问题,本文提出了一种基于流量监测的IFA检测方法.首先构建基于RSU的分布式网络流量监测层,每个RSU监测其通讯范围内的网络流量, RSU之间通信互联形成RSU网络流量监测层.其次,设定固定时间窗口,对每个窗口内的网络流量通过信息熵、网络自相似性和奇异点3个维度进行分析.其中,为了利用信息熵反映兴趣包来源的分布,在兴趣包中添加了新的字段.最后,综合上述3个指标,判断兴趣包洪泛攻击的存在.仿真实验结果表明,本文提出的方法有效地提升了兴趣包洪泛攻击检测的准确率,降低了误判率.     

联合车速–队列感知的路边单元分组调度随机优化

路边单元(RSU)是车联网中为其无线覆盖范围内过往车辆提供信息服务的基础设施,路边单元间的分组传输可通过移动车辆"存储–载带–转发"的方式进行,其传输过程中分组的端到端时延由源RSU缓存中的排队时延与车辆载带过程的传播时延两部分组成.为使RSU间分组传输过程中平均端到端时延最小化,本文提出一种联合车速–队列感知的路边单元分组调度随机优化方法,该方法根据源RSU缓存队列长度和经过源RSU覆盖范围的车辆速度状态作分组调度决策.通过马尔科夫决策(MDP)框架对分组传输过程中的平均排队时延和平均传播时延进行分析,建立一个非线性平均端到端时延最小化问题并求解.仿真结果表明,所提出的RSU分组调度随机优化方法可以显著降低RSU间分组传输过程中的平均端到端时延,并提高系统中分组传输的吞吐量.     

解决高度分割的车载自组网络连通性问题的路侧单元最优化调度方案

车载自组网络VANET是一种拥有高度动态拓扑结构的移动自组网络。为了解决其频繁的网络分割问题,最新研究提出使用一种特殊的称为路侧单元RSU的基础设施部署于道路两侧来提高VANET连通性。本文主要研究RSU调度中的节能降耗问题:给定一组路侧单元,我们的目标是寻找指定时段内打开或关闭RSU的最优调度,以确保RSU系统所消耗的总能量最小化,同时维持VANET系统网络连通性。我们将这一问题分解为两个子问题,即网络瞬像调度问题和网络瞬像选取问题。网络瞬像调度问题用于决定某时刻VANET网络瞬像中所需的连通状态RSU的最小值,而网络瞬像选取问题则用于决定系统需要在哪些时刻更新网络瞬像。通过对这两个子问题的研究,我们最终给出关于RSU调度问题的完全解,并通过理论分析与实验结果证明本文的算法可以在保持VANET连通性的同时明显地节能降耗。     

基于预测机制的分级负载均衡算法

为解决服务器集群负载分配不均的问题,根据用户访问的请求类型,综合考虑用户历史请求引起的负载增量和服务器节点性能,提出了基于预测机制的分级负载均衡算法。负载均衡节点根据用户访问的请求类型建立一次指数平滑预测模型,对相应请求类型引起的负载进行预测,并将预测负载划分为低负载、正常负载、重负载等三个负载等级,根据负载等级对用户请求进行调度,从而实现负载均衡。使用OPNET仿真软件进行测试,结果表明该算法能有效提高负载均衡效率,有较好的负载均衡效果。     

基于模因优化和循环调度的多目标负载均衡技术

针对现有多目标调度方法所需时间较长以及处理突发情况时性能降低的问题,提出一种基于模因优化和循环调度的多目标负载均衡技术。使用突发检测器检测发送到云服务器的用户请求,确定负载状态。基于测器结果,应用不同的负载平衡算法来高效地调度用户任务。利用选定的负载平衡算法将用户请求任务调度到资源最佳的虚拟机上,保证在最低的时间消耗内达到负载均衡的状态。实验结果表明,与其他算法相比,该方法在多个性能指标上具有明显优势,可以提高调度效率的同时,最大限度地降低云中的能源使用。     

A testbed for performance evaluation of load‐balancing strategies for Web server systems

To improve response time of a Web site, one replicates the site on multiple servers. The effectiveness of a replicated server system will depend on how the incoming requests are distributed among replicas. A large number of load‐balancing strategies for Web server systems have been proposed. In this paper we describe a testbed that can be used to evaluate the performance of different load‐balancing strategies. The testbed uses a general architecture which allows different load‐balancing approaches to be supported easily. It emulates a typical World Wide Web scenario and allows variable load generation and performance measurement. We have performed some preliminary experiments to measure the performance of a few policies for load balancing using this testbed. Copyright © 2003 John Wiley & Sons, Ltd.     

基于区分Web QoS的负载均衡集群模型

随着电子商务的应用逐步深入,用户访问量的激增且服务请求多样．如何实现对所有请求的快速响应是当前解决的问题．针对此问题,本文提出采用基于区分WebQoS的负载均衡技术．建立了基于区分WebQoS的负载均衡的集群模型．根据请求类型和用户权限划分服务等级,高服务的请求具有高优先调度权,在集群当中通过动态反馈技术均衡调度到某个节点,从而达到区分WebQoS服务的目的,同时也保证集群服务器的负载均衡．该模型在网络环境及硬件环境相同的条件下,与常用的负载均衡技术进行了比较,实验结果证明本文提出的方法效果显著．     

A scalable multi-attribute hybrid overlay for range queries on the cloud

Cloud computing has become a promising paradigm as next generation computing model, by providing computation, software, data access, and storage services that do not need to know the location of physical resources interconnected across the globe providing such services. In such an environment, important issues as information sharing and resource/service discovery arise. In order to overcome critical limitations in centralized approaches for information sharing and resource/service discovery, this paper proposes a framework of a scalable multi-attribute hybrid overlay featured with decentralized information sharing, flexible resource/service discovery, fault tolerance and load balancing. Additionally, the proposed hybrid overlay integrates a structured P2P system with an unstructured one to support complex queries. Mechanisms such as load balancing and fault tolerance implemented in our proposed system to improve the overall system performance are also discussed. Experimental results show that the performance of the proposed approach is feasible and stable, as the proposed hybrid overlay improves system performance by reducing the number of routing hops and balancing the load by migrating requests.     

一种基于负载反馈的分布式数字集群动态负载均衡算法

针对传统负载均衡算法不能满足公网数字集群系统高并发用户请求和快速呼叫建立等需求,提出一种基于负载反馈的分布式数字集群动态负载均衡算法,实现公网数字集群系统负载均衡,提高用户容量。首先建立参与MCPTT服务器的静态负载和动态负载监控机制和指标;然后利用加权轮询算法为用户分配参与MCPTT服务器,并通过用户请求的处理获得复合负载参数;根据负载指标的反馈更新参与MCPTT服务器权值以动态调整服务器负载。仿真结果表明,该算法的负载均衡效果优于传统算法和其他动态反馈算法,负载均衡度更小、用户请求响应延迟更低。     

Enhanced GridSim architecture with load balancing

Grid is a network of computational resources that may potentially span many continents. Maximization of the resource utilization hinges on the implementation of an efficient load balancing scheme, which provides (i) minimization of idle time, (ii) minimization of overloading, and (iii) minimization of control overhead. In this paper, we propose a dynamic and distributed load balancing scheme for grid networks. The distributed nature of the proposed scheme not only reduces the communication overhead of grid resources but also cuts down the idle time of the resources during the process of load balancing. We apply the proposed load balancing approach on Enhanced GridSim in order to gauge the effectiveness in terms of communication overhead and response time reduction. We show that significant savings are delivered by the proposed technique compared to other approaches such as centralized load balancing and no load balancing.     

LBBSRT: An efficient SDN load balancing scheme based on server response time

The response time is the most important factor determining user experiences in the service provision model involving server clusters. However, traditional server cluster load balancing scheme are limited by the hardware conditions, and cannot completely exploit the server response times for load balancing. In order to effectively resolve the traditional load balancing schemes, we propose a load balancing scheme based on server response times by using the advantage of SDN flexibility, named LBBSRT. Using the real-time response time of each server measured by the controller for load balancing, we process user requests by obtaining an evenly balanced server loads. Simulation experiments show that our scheme exhibits a better load balancing effect and process requests with a minimum average server response times. In addition, our scheme is easy to implement, and exhibits good scalability and low cost characteristics.     

Decentralized service discovery and selection in Internet of Things applications based on artificial potential fields

The Internet of Things (IoT) vision involves a future Internet integrated with real-world objects that can commonly offer their functionality trough services. In such pervasive environments of IoT networks, locating and invoking suitable services is quite challenging and traditional service discovery and selection approaches have been proven inadequate. In this paper, taking inspiration from natural metaphors, a decentralized service discovery and selection model is proposed. The model is based on artificial potential fields (APFs) which are formed upon each user service request and become active at points where services can be provided. Such points are termed as service provision nodes (SPNs). The strength of each APF depends on the percentage of requested services that can be provided by the respective SPN, as well as on SPN service load and availability with the aim to balance service load among SPNs. Service discovery and selection is then driven by artificial forces applied among user service requests and SPNs. Simulation results indicate that the proposed approach maintains satisfactory performance and scalability as the number of SPNs in an IoT network increase and efficient load balancing of the requested services among the SPNs in comparison with other approaches.     

Agent scheduling model for adaptive dynamic load balancing in agent-based distributed simulations

Agent-based distributed simulations are confronted with load imbalance problem, which significantly affects simulation performance. Dynamic load balancing can be effective in decreasing simulation execution time and improving simulation performance. The characteristics of multi-agent systems and time synchronization mechanisms make the traditional dynamic load balancing approaches not suitable for dynamic load balancing in agent-based distributed simulations. In this paper, an adaptive dynamic load balancing model in agent-based distributed simulations is proposed. Due to the complexity and huge time consuming for solving the model, a distributed approximate optimized scheduling algorithm with partial information (DAOSAPI) is proposed. It integrates the distributed mode, approximate optimization and agent set scheduling approach. Finally, experiments are conducted to verify the efficiency of the proposed algorithm and the simulation performance under dynamic agent scheduling. The experiments indicate that DAOSPI has the advantage of short execution time in large-scale agent scheduling, and the distributed simulation performance under this dynamic agent scheduling outperforms that under static random agent distribution.     

基于模糊逻辑技术的中间件负载平衡机制

针对当前基于中间件负载平衡机制中负载定位不够准确、监测粒度过大等问题,基于模糊逻辑技术提出一种更精确、更细粒度的负载平衡系统及其负载平衡机制。负载平衡系统的节点负载信息记录表记录系统中所有节点从模糊推理得出的负载状态信息,负载转发表记录服务节点与相应服务请求者之间的关系。实验结果表明,该负载平衡机制能有效地定位过载节点,较好地实现集群中的负载平衡服务。     

车联网RSU单元下行流量的性能研究

基于802.11p/WAVE的车联网是一项涉及道路交通、无线通信、自组织系统等多学科综合性的技术领域,车联网中,RSU单元可作为AP,让在行驶的汽车中的人们可以随时随地接入Internet,其中,如何建立RSU单元的下行流量模型是一个关键问题.通过引入车辆密度概率质量函数,分析车联网MAC层车辆通过RSU设备访问Internet的信道竞争情形,提出了适用于高速公路交通场景的RSU单元网络吞吐量模型,并推导出RSU上行及下行流量的性能解析式.针对RSU单元通信范围有限、相邻RSU单元之间可能存在盲区的问题,提出了一种利用同向行驶的车辆协助数据下载的VCoDS方案,以达到提高某时间段RSU的下行流量的目标.仿真实验结果证实,VCoDS方案可有效提高RSU单元的下行流量.     

The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times.     

MaxCD: Efficient multi-flow scheduling and cooperative downloading for improved highway drive-thru Internet systems

The limitation of existing wireless wide area networks, coupled with the delay tolerant property of many non-realtime applications (e.g. email, file download) enables drive-thru networking, which depends on roadside units (RSUs) to provide vehicular users with intermittent Internet access service. Focusing on the downlink service, MaxCD – a joint multi-flow scheduling and cooperative downloading protocol is proposed in this paper with the goal of maximizing the amount of data packets that can be downloaded per drive-thru. Based on the macro-level opportunistic scheduling and node cooperation, the best wireless link(s) (with the highest data rate) between the RSU and vehicular users can always be utilized. On the other hand, the advantage of opportunistic overhearing due to the broadcast nature of wireless medium is also exploited to reduce packet retransmission times, so as to further increase the effective data rate. Since the store-carry-forward delivery manner is adopted for the cooperators to avoid introducing interference to the in-range data communication, a multi-channel collision-free relay mechanism is designed to address the reliable and fast data exchange issue when the vehicular users are outside the service area of the RSU. Our theoretical analysis vindicates the performance gain of the cooperation and extensive simulations demonstrate the efficiency of MaxCD.     

基于Nginx负载均衡的动态改进算法

随着过去几十年互联网服务的指数增长,各大网站的访问量急剧上升。海量的用户请求使得热门网站的网络请求率可能在几秒钟内大规模增加。一旦服务器承受不住这样的高并发请求,由此带来的网络拥塞和延迟会极大地影响用户体验。负载均衡是高可用网络基础架构的关键组件,通过在后端引入一个负载均衡器,将工作负载分布到多个服务器来缓解海量并发请求对服务器造成的巨大压力,提高后端服务器和数据库的性能以及可靠性。而Nginx作为一款高性能的HTTP和反向代理服务器,正越来越多地应用到实践中。文中将分析Nginx服务器负载均衡的体系架构,研究默认的加权轮询算法,并提出一种改进后的动态负载均衡算法,实时收集负载信息,重新计算并分配权值。通过实验测试,对比不同算法下的负载均衡性能,改进后的算法能有效提高服务器集群的性能。