Cluster-based Web Servers Research Articles

Impact analysis of SYN flood DDOS attack on HAPROXY and NLB cluster-base web servers

<p>In recent, the high available internet service is main demand of the most people. However, online services occasionally become inaccessible due to various threats and attacks. Synchronization (SYN) flood Distributed Denial of Service (DDoS) is the most used and has a serious effect on the public network services. Hence, the outcome of this attack on the commonly utilized cluster-based web servers is systematically illustrated in this paper. Moreover, performance of Internet Information Service 10.0 (IIS 10.0) on Windows server 2016 and Apache 2 on Linux Ubuntu 16.04 server is evaluated efficiently. The performance measuring process is done on both Network Load Balancing (NLB) and High Available Proxy (HAProxy) in Windows and Linux environments respectively as methods for web server load balancing. Furthermore, stability, efficiency and responsiveness of the web servers are depended as the study evaluation metrics. Additionally, average CPU usage and throughput of the both mechanisms are measured in the proposed system. The results show that the IIS 10.0 cluster-based web servers are more responsiveness, efficiency and stable with and without SYN flood DDoS attack. Also, the performance of IIS 10.0 web server is better than of the Apache 2 in term of the average CPU usage and throughput.</p>

Some Aspects of Implementation of Web Services in Load Balancing Cluster-Based Web Server

We have designed, developed, and implemented SOAP-based web services in load balancing cluster-based web server and carried out load testing over the system. The roles of web services, such as client, broker, and service provider are segregated among different services. The system is monitored through a load testing tool, Mercury LoadRunner. The recorded system metrics are evaluated to study the overall performance and reliability aspects against different massive level of users. This article presents in detail the system architecture, testing methodology, and recorded system metrics. The statistical analysis is carried out to validate and correlate the overall assessment. This article also provides insights of some aspects of system metrics for deploying web services with segregated roles by using a cluster-based web server. It is observed that service with segregated roles is better than the service with merged roles. As a result, performance and reliability of the proposed system is observed to be better than other generic techniques for such deployment.

Investigation on Reliability Estimation of Loosely Coupled Software as a Service Execution Using Clustered and Non-Clustered Web Server

Evaluating the reliability of loosely coupled Software as a Service through the paradigm of a cluster-based and non-cluster-based web server is considered to be an important attribute for the service delivery and execution. We proposed a novel method for measuring the reliability of Software as a Service execution through load testing. The fault count of the model against the stresses of users is deployed. A prototype application using Simple Object Access Protocol-based web service is developed and the study is carried out over there. The experimental setup, architecture, load testing results followed by a comparative study is discussed in this work. It is observed that the reliability of the service by using clustered and non-clustered web server degrades after a specific limit of stress level execution point. The comparative assessment predicts that the reliability of service by using a cluster-based web server is better than the service with a non-cluster based web server. With an increase in the stress level of usage in a multi-tenant environment, the service with clustered web server delivers better reliability than the service without a clustered web server. The occurrences of HyperText Transfer Protocol request failure in the service with a clustered web server is comparatively less than its counterpart service without a clustered web server. The study helps in identifying the applicability of the method and shows the effectiveness of such deployment.

Pengujian Distribusi Beban Kerja Web Secara Statis pada Sistem Server Web Berbasis Cluster dengan Algoritma Never Queue

The increase in web traffic and the development of network bandwidth that is relatively faster than the development of microprocessor technology today causes the one point server platform to be no longer sufficient to meet the scalability requirements of web server systems. Multiple server platforms are the answer. One known solution is cluster-based web server systems. In this study, a cluster-based web server system would be designed with the Never Queue algorithm and continued with testing the distribution of web workload on this system. The tests were carried out by generating HTTP workloads statically (with fast HTTP requests per fixed second) and dynamically (rapid HTTP requests per second that change or rise regularly) from the client to the web server system pool. Followed by analyzing data package traffic. In this study, the results of static testing with rapid HTTP requests per second which still showed that the Never Queue algorithm distributed HTTP requests to the web server system pool properly and got HTTP replies that tend to be stable at the HTTP average of 1031.8 replies/s. As for the rapid parameters of TCP connections, response times and errors increased with the rapid increasing HTTP requests generated. The average output was at 2,983 Mbps.

A predictive framework for load balancing clustered web servers

Self-adaptation is the mechanism that is used automatically by some clustered web servers for resolving issues such as server bottleneck and overload. Such mechanisms are usually reactive meaning that they will be used when some issue occurs. However, taking an adaptation mechanism after arising a bottleneck or overload may be late and can cause some problems. Such problems could be resolved if we are able to predict future behavior of servers. To this end, based on our previous experiences, we presented a framework by which an adaptation strategy is selected based on a learning-based predictive method. Through the prediction, we are provided with a number of decision-making parameters for adaptation strategy selection. To show the effectiveness of our framework, we applied it for design and implementation of a differentiated cluster-based web server system and showed results. In such systems, each cluster is considered to serve a specific service. By comparison of simulation results between our predictive method and the reactive one, we found: (1) increase of the number of replied requests by servers, (2) decrease of average response time, and (3) increase of resource utilization of the system twofold to threefold.

Cluster-based Web Services using an Integrated Adaptive Management System

A cluster based web server is a web system architecture that consists of multiple server nodes distributed on a local area and is interconnected through a high speed network. The complexity of the cluster-based web service challenges the traditional approaches, which fail to guarantee the reliability and real-time performance required. In this paper, we present an Integrated Adaptive Management System (IAMS) for such service. The issues we discuss address to efficiently allocate resources and provide more effective QoS support under a wide range of load conditions. For the global resource level, we introduce spare instance and corresponding management strategy as a supplemental adaptive mechanism. The spare instances hosted on shared node afford better resource utilization and more effective QoS support in the case of overload or workload fluctuation. Further, it can relax the influence of the fault recovery from the hardware and software failure. For the local level, we apply a multipurpose linear-quadratic regulator (LQR) as basic adaptive element. The control scheme using reject time ratio as control input is able to provide guarantees for overload protection, resource control, Qos control, performance isolation, and effective management for spare instances. Although cluster-based web services have been widely deployed we have seen limited research in the literature on comprehensive adaptive mechanism for resource management with QoS support. For lack of detailed knowledge about the inner workings of the web service, we adopt system identification approach to establish the models. The open-loop service is modeled as a difference equation with unknown parameters. Then we stimulate the web service with pseudo-random signal as inputs and sample output data. After collecting the data, the least square estimation of model parameters can be solved via MATLAB. In this paper, we present an integrated adaptive management system (IAMS) for cluster-based web services. The main adaptive mechanisms in our system are: The resource adaptation based on the SLA event-driven mechanism. A supplemental adaptive mechanism based on spare instances and the corresponding strategy. A multi-purpose control scheme incorporated in the local manager and/or application is used as the basic adaptive element to provide guarantees for overload protection, resource control, Qos control, performance isolation and management for spare instances. We have presented rich experiments including overload protection, resource utility and QoS performance control both on static and dynamic website. The results illustrate our multi-purpose control scheme can offer effective QoS differential service and satisfied performance. Now the controller as the adaptive element only provides throughput different-tiation. It discusses the spare instance and its management. The multi-purpose feedback control scheme and the implementation of QoS differentiated service. It presents the experiment results on Tomcat and a 3-tiered web site to illustrate the efficiency of our control scheme respectively. Last Section summarizes our work and discusses the future work. Results of experiments on both static and dynamic web sites illustrate the efficiency and robustness of the multi-purpose LQR. The full text of the article is not available in the cache. Kindly refer the IJCA digital library at www.ijcaonline.org for the complete article. In case, you face problems while downloading the full-text, please send a mail to editor at editor@ijcaonline.org

A predictive and probabilistic load-balancing algorithm for cluster-based web servers

The exponential demands for high performance web servers led to use of cluster-based web servers. This increasing trend continues as dynamic contents are changing traditional web environments. Increasing utilization of cluster web servers through effective and fair load balancing is a crucial task specifically when it comes to advent of dynamic contents and database-driven applications on the internet. The proposed load-balancing algorithm classifies requests into different classes. The algorithm dynamically selects a request from a class and assigns the request to a server. For both the scheduling and dispatching, new probabilistic algorithms are proposed. To avoid using unreliable measured utilization in the face of fluctuating loads the proposed load-balancing algorithm benefits from a queuing model to predict the utilization of each server. We also used a control loop feedback to adjust the predicted values periodically based on soft computing techniques. The implementation results, using standard benchmarks confirms the effectiveness of proposed load-balancing algorithm. The algorithm significantly improves both the throughput and mean response time in contrast to two existing load-balancing algorithms.

An approximation-based load-balancing algorithm with admission control for cluster web servers with dynamic workloads

The growth of web-based applications in business and e-commerce is building up demands for high performance web servers for better throughputs and lower user-perceived latency. These demands are leading to a widespread substitution of powerful single servers by robust newcomers, cluster web servers, in many enterprise companies. In this respect the load-balancing algorithms play an important role in boosting the performance of cluster servers. The previous load-balancing algorithms which were designed for the handling of static contents in web services suffer from significant performance degradation under dynamic and database-driven workloads. Regarding this, we propose an approximation-based load-balancing algorithm with admission control for cluster-based web servers in this study. Since it is difficult to accurately determine the loads of web servers through feedbacks from distributed agents in web servers, we propose an analytical model of a web server to estimate the web servers' loads. To achieve this, the algorithm classifies requests based on their service times and track numbers of outstanding requests for each class of each web server node and also based on their resource demands to dynamically estimate the loads of each node. For the error handling of the model a proportional integral (PI) controller from control theory is used. Then the estimated available capacity of each web server is used for load balancing and admission control decisions. The implementation results with a standard benchmark confirm the effectiveness of the proposed scheme, which improves both the mean response time and the throughput of the cluster compared to rival load-balancing algorithms, and also avoids situations in which the cluster is overloaded, even when the request rates are beyond the cluster capacity.

Estimation-Based Load-Balancing with Admission Control for Cluster Web Servers

The growth of the World Wide Web and web-based applications is creating demand for high performance web servers to offer better throughput and shorter user-perceived latency. This demand leads to widely used cluster-based web servers in the Internet infrastructure. Load balancing algorithms play an important role in boosting the performance of cluster web servers. Previous load balancing algorithms suffer a significant performance drop under dynamic and database-driven workloads. We propose an estimation-based load balancing algorithm with admission control for cluster-based web servers. Because it is difficult to accurately determine the load of web servers, we propose an approximate policy. The algorithm classifies requests based on their service times and tracks the number of outstanding requests from each class in each web server node to dynamically estimate each web server load state. The available capacity of each web server is then computed and used for the load balancing and admission control decisions. The implementation results confirm that the proposed scheme improves both the mean response time and the throughput of clusters compared to rival load balancing algorithms and prevents clusters being overloaded even when request rates are beyond the cluster capacity.

A Performance Isolation Mechanism Based on Fuzzy Technique for Web Server Load Balancing

In this study, a performance isolation mechanism based on a fuzzy control technique is developed in such a way that ambiguous situations caused when estimating the workload of cluster-based web servers, client request rates, and dynamic request rates can be represented effectively. The proposed mechanism involving a fuzzy-based technique is compared with a non-fuzzy technique in terms of the response time in the 95th percentile. Experiments showed that the proposed technique improves the performance of web servers that provide differentiated services.

Coscheduled distributed-Web servers on system area network

As cluster-based Web servers are increasingly adopted to host a variety of network-based services, improving the performance of such servers has become critical to satisfy the customers’ demands. Especially, the user response time is an important factor so that clients feel satisfied with the Web services. In this paper, we investigate the feasibility of minimizing the response time of a server by exploiting the advantages of both user-level communication and coscheduling. We, thus, propose a coscheduled server model based on the recently proposed distributed PRESS Web server, where the remote cache accesses can be coscheduled on different nodes to reduce the response time. We experiment this concept using two known coscheduling techniques, called dynamic coscheduling (DCS) and DCS with immediate blocking. We have developed a comprehensive simulation testbed that captures the underlying communication layer in a cluster, the characteristics of various coscheduling algorithms, and the characteristics of the distributed server model to estimate the average delay and throughput with different system configurations. The accuracy of the VIA communication layer and the DCS mechanism is verified using measurements on a 16-node Linux cluster. Extensive simulation of four server models (PRESS over VIA, coscheduled PRESS model with DCS, with DCS and blocking, and Adaptive) using 32-node cluster configurations indicates that the average response time of a distributed server can be minimized significantly by coscheduling the communicating processes. The use of the DCS scheme reduced the average latency up to four times to the PRESS over VIA model that uses only user-level communication.

Modeling and simulation of performance analysis for a cluster-based Web server

Higher scalability and availability of Web servers are required as the traffic on the Internet has been increasing dramatically over the last few years. This paper focuses on modeling and simulation of the performance analysis for the test system of a cluster-based Web server consisting of five real servers. Three ways of load balancing are introduced, namely, network address translation, IP tunneling and direct routing. Calculation of packet delay is discussed for each part of the running system according to the transferred data in the system. The input model and the system model to measure and simulate the system performance are derived, and the probability distributions of the delay data are specified for using random inputs in the model according to the Q– Q plot and the cumulative distribution function. After the solution of performance tuning problems is evaluated, the maximum process capability of the system is found and a possible performance bottleneck is analyzed.

Weblins: A scalable WWW cluster-based server

With the ever-growing web traffic, cluster-based web servers have become very important to the Internet infrastructure. Thus, making the best use of all available resources in the cluster to achieve high performance is a significant research issue. In this paper, we present Weblins, a cluster-based web server that can achieve good throughput. Weblins has Gobelins operating system as platform. Gobelins is an efficient single system image operating system that transparently makes use of the resources available in the cluster. The architecture of Weblins is fully distributed. Weblins implements a content-aware request distribution policy via a new interface on top of Gobelins. Popular web files are dynamically replicated on all nodes via a cooperative caching mechanism. For the non-popular files, the requests are handed-off to the corresponding nodes via the TCP Handoff protocol. Simulation results show that the strategy used by Weblins is more suitable for cluster-based Web severs in comparison with pure content-aware strategy and pure cooperative caching strategy.

Cyclone: A High-Performance Cluster-Based Web Server with Socket Cloning

With the ever-growing web traffic, cluster-based web server is becoming more and more important to the Internet's infrastructure. Making the best use of all the available resources in the cluster to achieve high performance is thus a significant research issue. In this paper, we introduce Cyclone, a cluster-based web server that can achieve nearly optimal throughput. Cyclone makes use of a novel network support mechanism called Socket Cloning (SC), together with the method of hot object replication, to obtain high performance. SC allows an opened socket to be moved efficiently between cluster nodes. With SC, the processing of HTTP requests can be migrated to the node that has a cached copy of the requested document, thus obviating the need for any cache transfer between cluster nodes. To achieve better load balancing, frequently accessed documents (hot objects) are replicated to other cluster nodes. Trace-driven benchmark tests using http_load show that Cyclone outperforms existing approaches and can achieve a throughput of 14575 requests/s (89.5 MBytes/s), which is 98% efficiency of the available network bandwidth, with eight web server nodes.

Content-aware cooperative caching for cluster-based web servers

Most traditional cooperative caching schemes were developed for network file systems but were not designed for cluster-based web servers with content-based request distribution. Hence, although the schemes are applied to the web servers, their performance is not good due to high disk accesses and large block access latency. This paper proposes and evaluates a new cooperative caching scheme suitable to file systems in web servers. It uses a cache replacement policy, called duplicate first copy replacement, to avoid caching unnecessary data produced during serving requests and to minimize disk accesses. In addition it reduces block access latency required to fetch a file-block in the cooperative cache. A simulation shows that our cooperating caching decreases the disk access ratio by 29%, and reduces block access latency by about 26% when compared to the existing cooperative algorithms.

Content-Aware Dispatching Algorithms for Cluster-Based Web Servers

Cluster-based Web servers are leading architectures for highly accessed Web sites. The most common Web cluster architecture consists of replicated server nodes and a Web switch that routes client requests among the nodes. In this paper, we consider content-aware Web switches that can use application level information to assign client requests. We evaluate the performance of some representative state-of-the-art dispatching algorithms for Web switches operating at layer 7 of the OSI protocol stack. Specifically, we consider dispatching algorithms that use only client information as well as the combination of client and server information for load sharing, reference locality or service partitioning. We demonstrate through a wide set of simulation experiments that dispatching policies aiming to improve locality in server caches give best results for traditional Web publishing sites providing static information and some simple database searches. On the other hand, when we consider more recent Web sites providing dynamic and secure services, dispatching policies that aim to share the load are the most effective.

Comparison of Load Balancing Strategies on Cluster-based Web Servers

This paper focuses on an experimental analysis of the perfor mance and scalability of cluster-based web servers. We carry out the comparative studies using two experimental platforms, namely, a hardware testbed consisting of sixteen PCs, and a trace-driven discrete-event simulator. Dispatcher and web server service times used in the simulator are determined by carrying out a set of experiments on the testbed. The simulator is validated against stochastic queuing models and the testbed. Experiments on the testbed are limited by the hardware configu ration, but our complementary approach allows us to carry out scalability studies on the validated simulator. The three dis patcher-based scheduling algorithms analyzed are: round robin scheduling, least connected based scheduling, and least loaded based scheduling. The least loaded algorithm is used as the baseline (upper performance bound) in our analysis and the performance metrics include average waiting time, average re sponse time, and average web server utilization. A synthetic trace generated by the workload generator called SURGE, and a public-domain France Football World Cup 1998 trace are used. We observe that the round robin algorithm performs much worse in comparison with the other two algorithms for low to medium workload. However, as the request arrival rate increases, the performance of the three algorithms converge with the least con nected algorithm approaching the baseline algorithm at a much faster rate than the round robin. The least connected algorithm performs well for medium to high workload. At very low load, the average waiting time is two to six times higher than the baseline algorithm but the absolute value between these two waiting times is very small.

LSMAC vs. LSNAT: Scalable cluster-based Web servers

Server scalability is more important than ever in today's client/server dominated network environments. Recently, researchers have begun to consider cluster-based computers using commodity hardware as an alternative to expensive specialized hardware for building scalable Web servers. In this paper, we present performance results comparing two cluster-based Web servers based on different server architectures: OSI layer two dispatching (LSMAC) and OSI layer three dispatching (LSNAT). Both cluster-based server systems were implemented as application-space programs running on commodity hardware in contrast to other, similar, solutions which require specialized hardware/software. We point out the advantages and disadvantages of both systems. We also identify when servers should be clustered and when clustering will not improve performance.