SD‐WLB: An SDN‐aided mechanism for web load balancing based on server statistics

Software‐defined networking (SDN) is a modern approach for current computer and data networks. The increase in the number of business websites has resulted in an exponential growth in web traffic. To cope with the increased demands, multiple web servers with a front‐end load balancer are widely used by organizations and businesses as a viable solution to improve the performance. In this paper, we propose a load‐balancing mechanism for SDN. Our approach allocates web requests to each server according to its response time and the traffic volume of the corresponding switch port. The centralized SDN controller periodically collects this information to maintain an up‐to‐date view of the load distribution among the servers, and incoming user requests are redirected to the most appropriate server. The simulation results confirm the superiority of our approach compared to several other techniques. Compared to LBBSRT, round robin, and random selection methods, our mechanism improves the average response time by 19.58%, 33.94%, and 57.41%, respectively. Furthermore, the average improvement of throughput in comparison with these algorithms is 16.52%, 29.72%, and 58.27%, respectively.     

An adaptive load balancing scheme for web servers

This paper describes an overload control scheme for web servers which integrates admission control and load balancing. The admission control mechanism adaptively determines the client request acceptance rate to meet the web servers' performance requirements while the load balancing or client request distribution mechanism determines the fraction of requests to be assigned to each web server. The scheme requires no prior knowledge of the relative speeds of the web servers, nor the work required to process each incoming request. Copyright © 2002 John Wiley & Sons, Ltd.     

DServ‐LB: Dynamic server load balancing algorithm

In recent years, web services have been largely accessed by the customer, and it increases the network traffic on the internet. To provide the services for the large number of customer, dynamic clustering concept has been implemented that provides the ability to add or remove the servers on demand. But managing and processing the large set of traffic are very complicated. Load balancing technic helps to resolve the problems of network traffic and give efficient network management. In this paper, we proposed a dynamic server load balancing algorithm (DServ‐LB) using OpenFlow switches in software‐defined networking. The OpenFlow switches support the dynamic programmability. Also, we used the sFlow protocol, which is used to monitor the servers resource information periodically and the controller. Based on the server resource availability, the controller installs forwarding rules in the OpenFlow switches. For implementation, we used Mininet for network emulation, POX controller, and Docker container as Mininet hosts. The result shows that the proposed DServ‐LB improves the overall network performance and efficiently utilizes the server resources if compared with existing load balancing algorithms.     

网络负载均衡的控制理论及实践战略

网络负载均衡技术NLB（Network Load Balancing）采用完全分配算法来为集群中的服务器分配进入的访问流量,当集群中的某台服务器失效时,NLB会自动转发数据到其他可用的服务器上。负载均衡由多台服务器以对称的方式组成一个服务器集合,每台服务器都具有等价的地位,都可以单独对外提供服务而无须其他服务器的辅助。通过某种负载分担技术,将外部发送来的请求均匀分配到对称结构中的某一台服务器上,而接收到请求的服务器独立地回应客户的请求。均衡负载能够平均分配客户请求到服务器列阵,籍此提供快速获取重要数据,解决大量并发访问服务问题。     

一种改进的Linux集群系统负载均衡算法

提出一种基于改进的Linux集群系统负载均衡算法.首先通过修改负载权值计算指标,然后通过动态反馈机制收集各个各服务器的实时负载,负载均衡器根据收集的负载信息动态调整服务器权值,最后根据权值选择最优服务器去处理新的任务.仿真测试结果表明,改进负载均衡算法提高了整个系统的响应能力和吞吐量,较大幅度地提高系统的综合性能.     

An efficient clustering and load balancing of distributed cloud data centers using graph theory

The prime focus of the Cloud Service Providers is enhancing the service delivery performance of the distributed cloud data centers. The clustering and load balancing of distributed cloud data centers have significant impact on its service delivery performance. Hence, this paper models distributed cloud data center environment as a network graph and proposes a two‐phase cluster‐based load balancing (CLB) algorithm based on a graph model. The first phase proposes a Cloud Data Center Clustering algorithm to cluster the distributed cloud data centers based on their proximity. The second phase proposes a Client‐Cluster Assignment algorithm to perform uniform distribution of the client requests across the clusters to enable load balancing. To assess the performance, the proposed algorithms are compared with other K‐constrained graph‐based clustering algorithms namely, graph‐based K‐means and K‐spanning tree algorithms on a simulated distributed cloud data center environment. The experimental results reveal that the proposed CLB algorithm outperforms the compared algorithms in terms of the average clustering time, load distribution, and fairness index and hence improves the service delivery performance of the distributed cloud data centers.     

基于软件定义网络的服务器集群负载均衡技术研究

在当前的网络体系结构下,采用硬件系统实现服务器集群负载均衡存在着获取负载节点状态困难、流量导向方式复杂等制约因素,不利于提升服务器集群的伸缩性和服务性能。针对此问题,该文提出一种基于软件定义网络(SDN)的负载均衡机制(SDNLB)。该机制借助SDN具有的集中式控制和流量灵活调度优势,利用SNMP协议和OpenFlow协议对服务器的运行状态和全局网络负载信息进行实时监测,并通过权值计算的方式选择出权重最高的服务器作为流处理的目标服务器,在此基础上,采用最优转发路径算法进行流量调度,从而达到提高服务器集群的利用率与处理性能的目的。搭建了实验平台对SDNLB的性能进行仿真测试,实验结果表明:在相同的网络负载条件下,SDNLB与其他负载均衡算法相比,能够有效地降低服务器集群的负载,并能够显著提高网络吞吐量和带宽利用率,缩短流的完成时间和平均时延。     

An Efficient Gaming User Oriented Load Balancing Scheme for MMORPGs

Massively multi-player online role-playing games (MMORPGs) follows a client-server model that has the numerous gaming users with many interactions at the same virtual world, massive loading that result in delays, resource shortages, and other such problems occur. Also, faced with high resource demand variability and with misfit resource renting policies, the current practices is to overprovision for each game tens of owned data. Existing load balancing schemes for distributed virtual environments and multiplayer games try to balance the workload among servers by transferring some workload of an overloaded server to other servers. While load balancing algorithms can minimize the average response time of the system, they may also result in frequent client migrations, which may damage the interactivity of an online games. To solve this, many developers devote research to load-balancing servers, yet due to steady and dynamic map divisions, such research is unreliable. Many developers propose algorithms to distribute the load on the server nodes, but the load is usually defined as the number of players on each server, what is not an ideal results. So, we propose a gaming user-oriented load balancing scheme for the load balancing of MMORPGs servers in this paper. This scheme shows effectiveness at dealing with hot-spots and other gatherings of gaming users at specific servers compared to previous methods.     

Self‐organising cluster‐based cooperative load balancing in OFDMA cellular networks

Mobility load balancing (MLB) redistributes the traffic load across the networks to improve the spectrum utilisation. This paper proposes a self‐organising cluster‐based cooperative load balancing scheme to overcome the problems faced by MLB. The proposed scheme is composed of a cell clustering stage and a cooperative traffic shifting stage. In the cell clustering stage, a user‐vote model is proposed to address the virtual partner problem. In the cooperative traffic shifting stage, both inter‐cluster and intra‐cluster cooperations are developed. A relative load response model is designed as the inter‐cluster cooperation mechanism to mitigate the aggravating load problem. Within each cluster, a traffic offloading optimisation algorithm is designed to reduce the hot‐spot cell's load and also to minimise its partners’ average call blocking probability. Simulation results show that the user‐vote‐assisted clustering algorithm can select two suitable partners to effectively reduce call blocking probability and decrease the number of handover offset adjustments. The relative load response model can address public partner being heavily loaded through cooperation between clusters. The effectiveness of the traffic offloading optimisation algorithm is both mathematically proven and validated by simulation. Results show that the performance of the proposed cluster‐based cooperative load balancing scheme outperforms the conventional MLB. Copyright © 2013 John Wiley & Sons, Ltd.     

Predictive-adaptive algorithm for a cluster-based network web servers

The use of Web Clusters that implement Quality of Service has gained much attention in recent years. In this paper we propose an adaptive algorithm for a Web Switch that estimates the best configuration of the Web cluster attending to the throughput of servers. The slotted time used by the system is adaptive to the burstiness factor of client requests arriving to the Web Cluster. The web switch model is based on the estimation of the throughput that servers would have in the next future to dynamically balance the workload. In order to reduce the checking time, estimations are computed in a variable slot scheduling. Simulation results are confronted with other algorithms and show that the algorithm proposed performs significantly better in terms of latency time for priority users.     

SOA中一种带有预测功能的自适应负载均衡算法

在面向服务架构（SOA）中,针对目前负载均衡算法对于延时期间的负载波动情况自适应性及预测性较差的问题,提出一种改进的带有预测功能的自适应负载均衡算法．当工作负载到达率和服务特征发生变化时自动调整负载参数,并对后续请求的负载权重及分配情况进行预测．实验结果表明,该算法适用于高频率分布式的服务集群环境,能够有效的缩短服务器的平均响应时间,提高服务器的性能．     

Performance of Hybrid Load Balancing Algorithm in Distributed Web Server System

The challenges that load balancing (LB) faces are that there may not always be enough physical servers to be able to handle the demand requested at any one time. If a huge influx of players comes online at the same time, there may just not be enough room for them all. In this case, the server would usually initiate a queue system where players are held before they are allowed to attempt to connect to the world server. If too many requests are made however, the load balancer itself may stop working and deny players access completely. These challenges are specific to the Client/Server model of game content distribution. The proposed hybrid Grid model has a slightly different set of challenges. The load balancer in this model has to constantly check the network for player disconnections so that any outstanding events can be cleaned up by the dedicated hosts. It also has to balance load like normal to these hosts as they will appear as one entity on the network but can be scaled to as many machines as are needed. The popularity of decentralization over recent years has led to issues with the demand on server hardware and the need for LB which generates increased costs for companies and affects the quality of service. The aim of this work was to design and construct a Hybrid load balancing solution for Grid and compare it to the other load balancing algorithms. Grid with a load balancer was written in Java using a modular construction which allowed code reuse between different network models. Four common algorithms, one of which was redeveloped to improve its performance, were compared to determine load balancing efficiency for selecting servers from a pool.     

一种基于分布式服务器集群的可扩展负载均衡策略技术

提出了一种基于软件定义网络的分布式数据库负载均衡算法,将数据、控制、应用分离的同时计算服务器集群中单个服务器的实际负载.通过查询流量采样记录来决策最少连接的服务器路径,减少了访问请求的响应时间,提高了系统吞吐量和容错能力,实现了充分利用服务器资源的目的.内网中的分布式数据库实验对通用负载均衡技术和基于软件定义网络的负载均衡技术进行了比较,在不同服务器集群的负载状态下,后者的平均响应时间小于前者,并得到了更好的负载均衡效果.     

Clustering‐based scheduling: A new class of scheduling algorithms for single‐hop lightwave networks

In wavelength division multiplexing (WDM) star networks, the construction of the transmission schedule is a key issue, which essentially affects the network performance. Up to now, classic scheduling techniques consider the nodes' requests in a sequential service order. However, these approaches are static and do not take into account the individual traffic pattern of each node. Owing to this major drawback, they suffer from low performance, especially when operating under asymmetric traffic. In this paper, a new class of scheduling algorithms for WDM star networks, which is based on the use of clustering techniques, is introduced. According to the proposed Clustering‐Based Scheduling Algorithm (CBSA), the network's nodes are organized into clusters, based on the number of their requests per channel. Then, their transmission priority is defined beginning from the nodes belonging to clusters with higher demands and ending to the nodes of clusters with fewer requests. The main objective of the proposed scheme is to minimize the length of the schedule by rearranging the nodes' service order. Furthermore, the proposed CBSA scheme adopts a prediction mechanism to minimize the computational complexity of the scheduling algorithm. Extensive simulation results are presented, which clearly indicate that the proposed approach leads to a significantly higher throughput‐delay performance when compared with conventional scheduling algorithms. We believe that the proposed clustering‐based approach can be the base of a new generation of high‐performance scheduling algorithms for WDM star networks. Copyright © 2008 John Wiley & Sons, Ltd.     

A LIMITED RESOURCE VECTOR LOAD-BALANCING ALGORITHM FOR SOFTSWITCH-BASED HETEROGENEOUS CLUSTERED MEDIA SERVER

I. Introduction NGN (Next Generation Network) that can sup- port multimedia services has become a research hotspot in telecom and computer field in recent years. In the NGN architecture, multimedia service platform includes many kinds of devices[1]. As the device to provide media resource data and multime- dia operation environment under the control of softswitch device, media server is a key device on multimedia service platform. The media server un- der the control of softswitch device i…     

基于排队论综合指标评估的动态负载均衡算法

互联网通信、计算机集群和云环境均具有一定的复杂性和动态性,极易发生负载失衡,从而降低服务效率、增加能耗。因此,负载均衡技术成为重点研究课题。现有的负载均衡策略均是以 CPU、内存、进程等参数的占用率来评估服务器当前的负载情况,但服务器负载情况的复杂性往往使其难以得到准确评估。针对该问题,提出了一种基于排队论综合指标评估的动态负载均衡算法,首先引入排队论模型评估各服务器的实时负载情况,然后根据各服务器的负载综合指标,将输入队列中的任务逐一分配给各服务器。实验结果表明,该方法可有效平衡各服务器的负载且减少任务请求的平均等待时间。     

多核Web服务器中基于分配矩阵的动态请求调度算法

为了构建高性能的Web服务器,充分利用Web服务器中多核处理器的性能成为关键。传统的先到先服务策略没有考虑多核处理器的特点,不能充分利用多核处理器的性能。为解决此问题,该文提出一种基于分配矩阵的动态请求调度算法。该算法充分考虑了多核处理器的特点,可将同类动态请求动态分配至同一个处理器核心,提高了Web服务器处理动态请求的速度。仿真实验结果表明,采用该算法的Web服务器在自相似性、平均响应时间、丢包率等方面均优于传统的先到先服务算法。     

Apache集群在多媒体内容播控管理平台上的应用

随着终端用户的增加,多媒体内容播控管理平台对高访问量、高并发的需求越来越高。本文首先介绍了Apache集群的原理,然后将其应用于多媒体内容播控管理平台中,通过均衡负载,减轻了服务器的负担,提高了响应速度。     

代理集群的负载均衡系统的设计与实现

为了提高代理集群系统的整体性能,提高代理集群的效率,基于分布式计算领域已经较为成熟的负载均衡算法的研究成果,以及目前流行的服务器流量均衡策略,设计了一种针对代理集群这一应用背景的负载均衡策略系统,完成了系统结构和负载均衡策略的实现,并进行了性能测试。     

A self‐adaptive load‐dispatching control framework for device data accessing in IoT‐based systems

The Internet of things (IoT) information system plays important roles in disposing of huge volumes of real‐time service requests from heterogeneous devices, targeting for different complex application requirements. Load‐dispatching control (LDC) is a key problem to be solved for devices accessing concurrently in cluster systems. Self‐adaptive LDC optimizes the resource allocation to ensure no overloading node, thus, improving the performance of IoT systems. This paper focuses on adaptive dispatching control problem in IoT information system. First, a device data access platform is proposed for reducing the load imbalance and improving the efficiency of data processing. Then, we propose a processing capability prediction model to evaluate the system performance. On the basis of the model, we present a practical self‐adaptive LDC framework with a self‐adaptive control strategy and a load dispatching method. Finally, a case study is given to verify the framework and the control strategy. Experimental results show that the proposed strategy can meet the requirements of dynamic load balancing with the ability to avoid the load imbalance problem, and the LDC‐based device access platform can process data accessing effectively and ubiquitously.