MDDR: a solution for improving the scalability of dispatcher-based web server cluster

Native Web communication protocols are the pivotal components of Web services, applications and systems. In particular, HTTP is a de facto protocol standard used in almost all Web services and systems. Consequently, it is one of the crucial protocols responsible for the performance of Web services and systems. HTTP/1.1 has been successfully deployed in Web services and systems for the last two decades. However, one of the most significant issues with HTTP/1.1 is the Round Trip Time and Web latency. To resolve this issue, two successor protocols SPDY and HTTP/2 have been developed recently, with some studies suggesting that SPDY improved the performance of Web services and systems, whilst some did not find significant improvements in the performance. HTTP/2 is a relatively new protocol and has yet to be tested with any rigour. Therefore, it is important to investigate the effects of these two enhanced protocols SPDY and HTTP/2 on the performance of Web services and systems. This paper conducts a number of practical investigations to evaluate the performance of Web services and systems with and without the support of SPDY and HTTP/2 protocols at the client and server. This study investigates the impact of SPDY and HTTP/2 on the overall performance of Web services and systems from the end-user's perspective.

High-performance Web servers are essential to meet the growing demands of the Internet and large-scale intranets. Satisfying these demands requires a thorough understanding of key factors affecting Web server performance. This paper presents empirical analysis illustrating how dynamic and static adaptivity can enhance Web server performance. Two research contributions support this conclusion. First, the paper presents results from a comprehensive empirical study of Web servers (such as Apache, Netscape Enterprise, PHTTPD, Zeus, and JAWS) over high-speed ATM networks. This study illustrates their relative performance and precisely pinpoints the server design choices that cause performance bottlenecks. Once network and disk I/O overheads are reduced to negligible constant factors, the main determinants of Web server performance are its protocol processing path and concurrency strategy. Moreover no single strategy performs optimally for all load conditions and traffic types. Second, we describe the design techniques and optimizations used to develop JAWS, our high-performance adaptive Web server. JAWS is an object-oriented Web server that was explicitly designed to alleviate the performance bottlenecks we identified in existing Web servers. The performance optimizations used in JAWS include adaptive prespawned threading, fixed headers, cached date processing, and file caching. In addition, JAWS uses a novel software architecture that substantially improves its portability and flexibility, relative to other Web servers.

The advent of Web technology has made Web servers core elements of future communication networks. Although the amount of traffic that Web servers must handle has grown explosively during the last decade, the performance limitations and the proper tuning of Web servers are still not well understood. In this paper we present an end-to-end queueing model for the performance of Web servers, encompassing the impacts of client workload characteristics, server harware/software configuration, communication protocols, and interconnect topologies. The model has been implemented in a simulation tool, and performance predictions based on the model are shown to match very well with the performance of a Web server in a test lab environment. The simulation tool forms an excellent basis for development of a Decision Support System for the configuration tuning and sizing of Web servers.

During their navigation, Web users leave many records of their activity. This huge amount of data can be a useful source of knowledge. Sophisticated data mining processes are needed for this knowledge to be extracted, understood and used. In this paper, we propose a Web usage mining (WUM) system, called SUGGEST, which dynamically generates suggested links to Web pages of potential interest for a user. SUGGEST is designed to efficiently integrate the WUM process with the ordinary Web server functionalities. It can provide useful information to make the user's Web navigation easier and to optimize the Web server's performance. Two quantities are introduced in order to give a measure of the quality of our WUM system.

Towards a context-based multi-type policy approach for Web services composition

Simple SummaryThe OSov web server incorporates gene expression profiles with clinical risk factors to estimate the ovarian cancers patients’ survival, and provides a tool for multiple analysis, such as forest-plot, uni/multi-variate survival analysis, Kaplan-Meier plot and nomogram construction.Ovarian cancer is one of the most aggressive and highly lethal gynecological cancers. The purpose of our study is to build a free prognostic web server to help researchers discover potential prognostic biomarkers by integrating gene expression profiling data and clinical follow-up information of ovarian cancer. We construct a prognostic web server OSov (Online consensus Survival analysis for Ovarian cancer) based on RNA expression profiles. OSov is a user-friendly web server which could present a Kaplan–Meier plot, forest plot, nomogram and survival summary table of queried genes in each individual cohort to evaluate the prognostic potency of each queried gene. To assess the performance of OSov web server, 163 previously published prognostic biomarkers of ovarian cancer were tested and 72% of them had their prognostic values confirmed in OSov. It is a free and valuable prognostic web server to screen and assess survival-associated biomarkers for ovarian cancer.

Background/Objectives: The primary objective of the study is to evaluate the performance of Composite Web Service based on the parameters relating to Quality of Service by using statistical methodologies. Methods/Statistical Analysis: By using Web Service Crawler Engine we have collected data on eleven parameters of interest from a more number of Web Services. Among the eleven parameters we have selected six parameters of importance using the sampling of thirty Web Services. We have constructed the weight matrix for the parameters. By using Web Services Relevancy Function ranking has been done for three different scenarios. Using Spearman's Rank Correlation Coefficient we have compared the scenarios. Findings: The graphical representation of the three scenarios shows varying pattern. The Spearman's Rank Correlation coefficient of the Web Services Relevancy Function varied widely among the sampled Web Services. F-Test revealed that there are no significant differences in respect of weights of Quality of Web Services for three different scenarios. We concluded that weight assigned for Quality of Service parameters in Scenario I is preferred than the scenarios II and III through the evaluations. Application/Improvements: The technique developed in this research paper can be applied for the comparison of Web Services during discovery to enhance the performance of the Composite Web Service.

The dispatcher-based web server load balancing architecture can improve the performance of popular web servers. When the backend servers have different computational power, the system must use the real-time loading information as the decision making criteria. In this paper, we proposed a dispatcher architecture that uses the remaining capacity of each backend servers to decide the most appropriate server. In addition to improve the performance, the system can also use the remaining capacity algorithm to reduce the cost when the web side does not have frequent burst request. For example, the course registration ticket reservation systems have burst requests only several times a year. The proposed architecture can use the remaining capacity of other servers such DNS or MAIL server to share the load in the burst request period. The simulation results show that using the remaining capacity of both DNS and MAIL server can achieve similar performance compared to using another dedicated web server.

This paper presents an analysis of web service performance using queueing theory models. We explore the significance of aligning key web service attributes with queueing theory parameters to enable comprehensive performance evaluation. Through both theoretical modeling and analysis of empirical data, we examine the impact of various factors on system performance, such as response time, throughput, and resource utilization. The results emphasize the importance of understanding web service characteristics for performance optimization, highlighting the need to balance arrival and service rates for maximum efficiency. While this study offers valuable insights into web service performance assessment, future research should focus on exploring additional factors and applying advanced queueing theory techniques to enhance optimization in distributed systems.

Many Web sites today dynamically generate responses when user requests are received. Dynamic content creation enables features that might otherwise not be possible. One disadvantage of dynamically generating Web content is the impact on Web server performance. In this paper, we experimentally evaluate the impact of three different dynamic content technologies on Web server performance. The results show that the overheads of dynamic content generation reduce the peak response rate of a Web server by a factor of 2 to 8, depending on the workload characteristics and the specific Web technologies used.

Web cluster systems consist of a load balancer for distributing web requests and loads to several servers, and real servers for processing web requests. Previous load distribution scheduling algorithms of web cluster systems to distribute web requests to real servers are Round-Robin, Weighted Round-Robin, Least-Connection and Weighted Least-Connection(WLC) algorithm. The WLC scheduling algorithm, in which a throughput weight is assigned to real servers and the least connected real server is selected for processing web requests, is generally used for web cluster systems. When a new real server is added to a web cluster system with many simultaneous users, previous WLC scheduling algorithm assigns web requests to only the new real server, and makes load imbalance among real servers. In this paper, we propose a improved WLC scheduling algorithm which maintains load balance among real servers by avoiding web requests being assigned to only a new real server. When web requests are continuously assigned to only a new real server more than the maximum continuous allocation number(L), the proposed algorithm excepts the new real server from activated real server scheduling list and deactivates the new real server. And after L-1 allocation round times, the new real server is included into real server scheduling list by activating it. When a new real server is added to web cluster systems, the proposed algorithm maintains load balance among real servers by avoiding overloads of the new real server.

This paper introduces a novel honeypot for web application. Recently, web applications have been the target of numerous cyber attacks. In order to catch up new vulnerabilities in the applications, using a honeypot system is a feasible solution. However, there remains difficulty for developing a lure-able, protect-able, and deception-able honeypot for web applications. In this paper, we present an approach in which attackers will be automatically isolated from the real web server to the honey web server. The key features are employing migration techniques to create a virtual machine as a honey web server, making the honeypot to equip the same memory and storage devices of the real systems, and controlling network traffic with OpenFlow in order to isolate honeypots from the real server. This paper also shows our design and implementation of INTERCEPT+, a component of honeypot systems for web applications.

PurposeWeb services promise a step change in business‐to‐business application models and practices. But how do we measure web services' performance? Because web services are so new, and implementations so few, the purpose of this paper is to take internet performance as a proxy for web services performance.Design/methodology/approachThe authors surveyed 106 e‐business SMEs to identify key drivers for internet performance, and then predicted web services performance.FindingsSurprisingly, it was found that while business resources and IT resources positively impact internet performance, dynamic capabilities do not. Also, there appear to be significant firm size effects.Originality/valueThe implications of these findings for the strategic management of web services are discussed, and in particular, managers' need to balance resources and capabilities in volatile business environments.

The exponential growth of Web service makes building high-quality service-oriented systems an urgent and crucial research problem. Performance of the service-oriented systems highly depends on the remote Web services as well as the unpredictability of the Internet. Performance prediction of service-oriented systems is critical for automatically selecting the optimal Web service composition. Since the performance of Web services is highly related to the service status and network environments which are variable over time, it is an important task to predict the performance of service-oriented systems at runtime. To address this critical challenge, this chapter proposes an online performance prediction framework, called OPred, to provide personalized service-oriented system performance prediction efficiently. Based on the past usage experience from different users, OPred builds feature models and employs time series analysis techniques on feature trends to make performance prediction. The results of large-scale real-world experiments show the effectiveness and efficiency of OPred.

On the performance of web services, google cloud messaging and firebase cloud messaging