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Web performance is a hot topic, as many studies have shown a strong correlation between slow webpages and loss of revenue due to user dissatisfaction. Front and center in Page Load Time (PLT) optimization is the order in which resources are downloaded and processed. The new HTTP/2 specification includes dedicated resource prioritization provisions, to be used in tandem with resource multiplexing over a single, well-filled TCP connection. However, little is yet known about its application by browsers and its impact on page load performance. This article details an extensive survey of modern User Agent implementations, with the conclusion that the major vendors all approach HTTP/2 prioritization in widely different ways, from naive (Safari, IE, Edge) to complex (Chrome, Firefox). We investigate the performance effect of these discrepancies with a full-factorial experimental evaluation involving eight prioritization algorithms, two off-the-shelf User Agents, 40 realistic webpages, and five heterogeneous (emulated) network conditions. We find that in general the complex approaches yield the best results, while naive schemes can lead to over 25% slower median visual load times. Also, prioritization is found to matter most for heavy-weight pages. Finally, it is ascertained that achieving PLT optimizations via generic server-side HTTP/2 re-prioritization schemes is a non-trivial task and that their performance is influenced by the implementation intricacies of individual browsers. Part of this work was funded by the imec ICON Pro-Flow project. Industrial partners involved in the Pro-Flow project include ANDROME, Nokia and Barco. Robin Marx is a SB PhD fellow at FWO, Research Foundation - Flanders, project number 1S02717N.

The HTTP/1.1 protocol has long been a staple on the web, for both pages and apps. However, it has started to show its age, especially with regard to page load performance and the overhead it entails due to its use of multiple underlying connections. Its successor, the newly standardized HTTP/2, aims to improve the protocol’s performance and reduce its overhead by (1) multiplexing multiple resources over a single TCP connection, (2) by using advanced prioritization strategies and by introducing new features such as (3) Server Push and (4) HPACK header compression. This work provides an in-depth overview of these four HTTP/2 performance aspects, discussing both synthetic and realistic experiments, to determine the gains HTTP/2 can provide in comparison to HTTP/1.1 in various settings. We find that the single multiplexed connection can actually become a significant performance bottleneck in poor network conditions with high packet loss and that HTTP/2 rarely improves much on HTTP/1.1, except in terms of reduced overhead. Prioritization strategies, Server Push and HPACK compression are found to have a relatively limited impact on web performance, but together with other observed HTTP/2 performance problems this could also be due to faulty current implementations, of which we have discovered various examples. This work is part of the imec ICON PRO-FLOW project. Robin Marx is a SB PhD fellow at FWO, Research Foundation - Flanders, project number 1S02717N.

Understanding the quality of Experience (QoE) of web browsing is key to optimize services and keep users' loyalty. This is crucial for both Content Providers and Internet Service Providers (ISPs). Quality is subjective, and the complexity of today's pages challenges its measurement. OnLoad time and SpeedIndex are notable attempts to quantify web performance with objective metrics. However, these metrics can only be computed by instrumenting the browser and, thus, are not available to ISPs. We designed PAIN: PAssive INdicator for ISPs. It is an automatic system to monitor the performance of web pages from passive measurements. It is open source and available for download. It leverages only flow-level and DNS measurements which are still possible in the network despite the deployment of HTTPS. With unsupervised learning, PAIN automatically creates a machine learning model from the timeline of requests issued by browsers to render web pages, and uses it to measure web performance in realtime. We compared PAIN to indicators based on in-browser instrumentation and found strong correlations between the approaches. PAIN correctly highlights worsening network conditions and provides visibility into web performance. We let PAIN run on a real ISP network, and found that it is able to pinpoint performance variations across time and groups of users. Based on work published at Martino Trevisan, Idilio Drago, and Marco Mellia. 2017. PAIN: A Passive Web Speed Indicator for ISPs. In Proceedings of the Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet QoE '17). ACM, New York, NY, USA, 7--12. DOI: https://doi.org/10.1145/3098603.3098605

User experience (UX) is one of the most popular subjects in the industry nowadays and plays a significant role in the business success. As the growth of a business depends on customers, it is essential to emphasize on the UX that can help to enhance customer satisfaction. There has been statements that the overall end-user experience is to a great extent influenced by page load time, and that UX is primarily associated with performance of applications. This paper analyzes the effectiveness of performance optimization techniques and their impact on user experience. Principally, the web performance optimization techniques used in this study were caching data, fewer HTTP requests, Web Workers and prioritizing content. A profiling method Manual Logging was utilized to measure performance improvements. A UX survey consists of User Experience Questionnaire (UEQ) and three qualitative questions, was conducted for UX testing before and after performance improvements. Quantitative and qualitative methods were used to analyze collected data. Implementations and experiments in this study are based on an existing tool, a web-based application. Evaluation results show an improvement of 45% on app load time, but no significant impact on the user experience after performance optimizations, which entails that web performance does not really matter for the user experience. Limitation of the performance techniques and other factors that influence the performance were found during the study. Användarupplevelse (UX) är idag en av de mest populära ämnena inom IT-branschen och spelar en viktig roll i affärsframgångar. Eftersom tillväxten av ett företag beror på kunder är det viktigt att betona på UX som kan bidra till att öka kundnöjdheten. Det har konstaterats att den övergripande slutanvändarupplevelsen i stor utsträckning påverkas av sidladdningstiden och att UX huvudsakligen är förknippad med applikationernas prestanda. I denna studie analyseras effektiviteten av optimeringstekniker och deras inverkan på användarupplevelse. Huvudsakligen, optimeringstekniker som användes i denna studie var cache-lösning, färre HTTP-förfrågningar, Web Workers och prioritering av innehåll. Profileringsmetoden "Manual Logging" användes för att mäta prestandaförbättringar. En enkätutvärdering som består av User Experience Questionnaire (UEQ) och tre kvalitativa frågor, genomfördes med fokus på användarupplevelsen före och efter prestandaförbättringar. Kvantitativa och kvalitativa metoder användes för att analysera insamlade data. Implementeringar och experiment i denna studie är baserade på ett befintligt verktyg, en webbaserad applikation. Utvärderingsresultatet visar en förbättring på 45% när det gäller sidladdningstid men ingen signifikant inverkan på användarupplevelsen efter prestandaförbättringar, vilket innebär att webbprestanda inte spelar någon roll för användarupplevelsen. Begränsning av optimeringstekniker och andra faktorer som påverkar prestationen hittades under studien.

Ad and tracking blocking extensions are popular tools for improving web performance, privacy and aesthetics. Content blocking extensions generally rely on filter lists to decide whether a web request is associated with tracking or advertising, and so should be blocked. Millions of web users rely on filter lists to protect their privacy and improve their browsing experience. Despite their importance, the growth and health of filter lists are poorly understood. Filter lists are maintained by a small number of contributors who use undocumented heuristics and intuitions to determine what rules should be included. Lists quickly accumulate rules, and rules are rarely removed. As a result, users' browsing experiences are degraded as the number of stale, dead or otherwise not useful rules increasingly dwarf the number of useful rules, with no attenuating benefit. An accumulation of "dead weight" rules also makes it difficult to apply filter lists on resource-limited mobile devices. This paper improves the understanding of crowdsourced filter lists by studying EasyList, the most popular filter list. We measure how EasyList affects web browsing by applying EasyList to a sam- ple of 10,000 websites. We find that 90.16% of the resource blocking rules in EasyList provide no benefit to users in common browsing scenarios. We use our measurements of rule application rates to taxonomies ways advertisers evade EasyList rules. Finally, we propose optimizations for popular ad-blocking tools that (i) allow EasyList to be applied on performance constrained mobile devices and (ii) improve desktop performance by 62.5%, while preserving over 99% of blocking coverage. We expect these optimizations to be most useful for users in non-English locals, who rely on supplemental filter lists for effective blocking and protections.

Despite its widespread adoption and popularity, the Hypertext Transfer Protocol (HTTP) suffers from fundamental performance limitations. SPDY, a recently proposed alternative to HTTP, tries to address many of the limitations of HTTP (e.g., multiple connections, setup latency). In this paper, we perform a detailed measurement study to understand the benefits of using SPDY over cellular networks. Through careful measurements conducted over 4 months, we provide a detailed analysis of the performance of HTTP and SPDY, how they interact with the various layers, and their implications on Web design. Our results show that unlike in wired and 802.11 networks, SPDY does not clearly outperform HTTP over cellular networks. We identify negative interactions between the protocols used for Web access (HTTP/SPDY over TCP) and cellular radio resource management as the underlying cause. Overall performance suffers when devices go through a cellular radio state promotion after an idle period, and the consequent increase in latency. This impacts SPDY more because of the use of a single TCP connection. We conclude that a viable solution has to account for these unique cross-layer dependencies to achieve improved Web performance over cellular networks.

This study explores how informative and entertaining features of destination marketing organization (DMO) websites affect a sense of telepresence, and how these features affect visitors’ evaluation of the utilitarian and hedonic performances of such websites. This study further examines how DMO websites affect visitors’ familiarity with, interest in, and knowledge about a destination and their consequent intention to visit the destination. A total of 433 responses from United States (US) Internet users were collected in an online survey. The study results suggest that informative and entertaining telepresence is crucial in DMO web performance, making a destination appear more familiar and interesting to prospective visitors. This increases the likelihood that potential tourists will plan a trip to the destination.

Content Delivery Networks (CDNs) deliver much of the world's web, video, and application content on the Internet today. A key component of a CDN is the mapping system that uses the DNS protocol to route each client's request to a ``proximal'' server that serves the requested content. While traditional mapping systems identify a client using the IP of its name server, we describe our experience in building and rolling-out a novel system called end-user mapping that identifies the client directly by using a prefix of the client's IP address. Using measurements from Akamai's production network during the roll-out, we show that end-user mapping provides significant performance benefits for clients who use public resolvers, including an eight-fold decrease in mapping distance, a two-fold decrease in RTT and content download time, and a 30% improvement in the time-to-first byte. We also quantify the scaling challenges in implementing end-user mapping such as the 8-fold increase in DNS queries. Finally, we show that a CDN with a larger number of deployment locations is likely to benefit more from end-user mapping than a CDN with a smaller number of deployments.

The Internet provides a convenient environment for data collection in psychology. Modern Web programming languages, such as JavaScript or Flash (ActionScript), facilitate complex experiments without the necessity of experimenter presence. Yet there is always a question of how much noise is added due to the differences between the setups used by participants and whether it is compensated for by increased ecological validity and larger sample sizes. This is especially a problem for experiments that measure response times (RTs), because they are more sensitive (and hence more susceptible to noise) than, for example, choices per se. We used a simple visual search task with different set sizes to compare laboratory performance with Web performance. The results suggest that although the locations (means) of RT distributions are different, other distribution parameters are not. Furthermore, the effect of experiment setting does not depend on set size, suggesting that task difficulty is not important in the choice of a data collection method. We also collected an additional online sample to investigate the effects of hardware and software diversity on the accuracy of RT data. We found that the high diversity of browsers, operating systems, and CPU performance may have a detrimental effect, though it can partly be compensated for by increased sample sizes and trial numbers. In sum, the findings show that Web-based experiments are an acceptable source of RT data, comparable to a common keyboard-based setup in the laboratory.

Now a day‘s the e-commerce websites are facing the biggest challenges of the massive growth of website data. There is a need to find behavior of user so that there is need to find next page in advance on cache. Further they do not have a good policy for finding user behavior in website. They need to use good approach for improving the quality and accuracy in today‘s scenario. Closed sequential pattern mining is an important technique among the different types of sequential pattern mining, since it preserves the details of the full pattern set and it is more compact than sequential pattern mining. In this paper the clustering task is used to improve performance of website navigation pattern in advance. The main goal of this research is to find the extract the knowledge that can enhance web performance of associate items in sequential manner with the quality.

In this paper we initially present the importance of search engine optimization (SEO) for tourism Websites. We present the most important metrics that affect SEO such as display speed, quality and quantity of content, mobile responsiveness, inbound links and the technologies that they use. All these metrics greatly affect search engine rankings and consequently online bookings. To assess how SEO is implemented on a tourism related domain we examine a sample of almost 400 Tourism business websites on the island of Kefalonia in Greece. We provide cumulative results for more than 20 important SEO metrics for these Websites. Our case study shows that SEO metrics have been optimized for about 25% of these Websites and need extensive optimization for the rest. Τhe basic idea in this paper is to study and evaluate the state of SEO on a specific tourism destination (Kefalonia) and provide insights for the next steps that need to be implemented in order to improve search engine rankings. We also correlate SEO optimization to search engine position. This has been done by introducing a general SEO grade as a combination of important SEO metrics for every Website, taking into account their relative significance. This correlation proves that more optimized websites rank better for generic queries in their category. SEO is very important in Tourism since it helps search engines figure out what each page is about, and how it may be useful to users. This paper proves that SEO plays a significant role for tourism website rankings and that there is a lot of room for improvement for a large number of tourism websites.

End-users in emerging markets experience poor web performance due to a combination of three factors: high server response time, limited edge bandwidth and the complexity of web pages. The absence of cloud infrastructure in developing regions and the limited bandwidth experienced by edge nodes constrain the effectiveness of conventional caching solutions for these contexts. This paper describes the design, implementation and deployment of xCache, a cloud-managed Internet caching architecture that aims to proactively profile popular web pages and maintain the liveness of popular content at software defined edge caches to enhance the cache hit rate with minimal bandwidth overhead. xCache uses a Cloud Controller that continuously analyzes active cloud-managed web pages and derives an object-group representation of web pages based on the objects of a page. Using this object-group representation, xCache computes a bandwidth-aware utility measure to derive the most valuable configuration for each edge cache. Our preliminary real-world deployment across university campuses in three developing regions demonstrates its potential compared to conventional caching by improving cache hit rates by about 15%. Our evaluations of xCache have also shown that it can be applied in conjunction with other web optimizations solutions like Shandian, and can improve page load times by more than 50%.

Software with high quality is in demand in this competitive software industry. Software validation, verification and quality maintenance are significant principles of testing. Performance testing is the process of determining the speed and the effectiveness of a system. It basically focuses on determining whether the user of the system will be satisfied with the performance characteristics of the application. Performance optimization is the process to make and manage the quality demands of a product. In this paper, we propose a novel approach named web performance analyzer (WebN) which analyses the website, retrieves all performance-dependent factors and gives appropriate suggestions. These suggestions are framed based on the analysis of approximately 10 million websites’ performance data. These suggestions are distinct from other web analyzer tools. After web page optimization, the status visualization for performance improvement is given by WebN. Our research work will help the developers to construct systematic and qualitative software throughout the software development life cycle.

Improving web performance is fueling the debate of sizing TCP's initial congestion window (IW), which is a critical performance parameter especially for short-lived flows. This debate yielded several RFC updates to recommended IW sizes, e.g., an increase to IW10 in 2010. The current adoption of IW recommendations is, however, unknown. In this paper, we therefore conduct large-scale measurements covering the entire IPv4 space inferring the IW distribution size by probing HTTP and HTTPS servers. We present an HTTP and TLS scanning method implemented in ZMap, enabling quick estimations of IW sizes at Internet scale. For the first time since the standardization and implementation of IW 10, we shed light on the rugged landscape of IW configurations on the Internet.

Through analyses on performances of Web frontend, we can learn about the bottlenecks of Web performance, the load limit and connection limit of browser. In this paper, the optimization strategies were carried out to accommodate the bottlenecks and a new request scheduling algorithm with AQSM was proposed to resolve the two connection restrictions. Some optimization strategies were used to settle the frontend performance problems of some webpages, and the results were in good performances.

Many methods are used to reduce the time required to download web page completely. Most of them based on different techniques such as media elements and scripts compression, parallel resource download or caching. One of such techniques based on resource sharing and CDN usage. Resource sharing is an effective design for web pages with a considerable amount of media elements. In this paper, the author introduces his own software to determine, if selected web page uses CDN or external resources. In addition, questions about the correlation between web-page size, category and CDN usage are taken into account.

Clearly, no one likes webpages with poor quality of experience (QoE). Being perceived as slow or fast is a key element in the overall perceived QoE of web applications. While extensive effort has been put into optimizing web applications (both in industry and academia), not a lot of work exists in characterizing what aspects of webpage loading process truly influence human end-user's perception of the Speed of a page. In this paper we present SpeedPerception1, a large-scale web performance crowdsourcing framework focused on understanding the perceived loading performance of above-the-fold (ATF) webpage content. Our end goal is to create free open-source benchmarking datasets to advance the systematic analysis of how humans perceive webpage loading process.In Phase-1 of our SpeedPerception study using Internet Retailer Top 500 (IR 500) websites [3], we found that commonly used navigation metrics such as onLoad and Time To First Byte (TTFB) fail (less than 60% match) to represent majority human perception when comparing the speed of two webpages. We present a simple 3-variable-based machine learning model that explains the majority end-user choices better (with 87 ± 2% accuracy). In addition, our results suggest that the time needed by end-users to evaluate relative perceived speed of webpage is far less than the time of its visualComplete event.

The existing slowness of the web on mobile devices frustrates users and hurts the revenue of website providers. Prior studies have attributed high page load times to dependencies within the page load process: network latency in fetching a resource delays its processing, which in turn delays when dependent resources can be discovered and fetched.To securely address the impact that these dependencies have on page load times, we present Vroom, a rethink of how clients and servers interact to facilitate web page loads. Unlike existing solutions, which require clients to either trust proxy servers or discover all the resources on any page themselves, Vroom's key characteristics are that clients fetch every resource directly from the domain that hosts it but web servers aid clients in discovering resources. Input from web servers decouples a client's processing of resources from its fetching of resources, thereby enabling independent use of both the CPU and the network. As a result, Vroom reduces the median page load time by more than 5 seconds across popular News and Sports sites. To enable these benefits, our contributions lie in making web servers capable of accurately aiding clients in resource discovery and judiciously scheduling a client's receipt of resources.

Web performance has long proved to be one of the most sought after and difficult to achieve components for the web. Since the inception of the modern web infrastructure, the situation has been growing in complexity, adding remote hosts and objects, providing everything from computation infrastructure, content distribution capability, and targeted advertising. While many of these components provide improvements for some users, the complexity of the Internet often leaves other users suffering from poor performance. We propose Oak, a system which addresses client performance on the individual level, hence addressing challenges which may be unique to the user. Oak measures a user's performance for objects loading on a page, and determines which components are under-performing. Oak further provides an automated mechanism by which sites are able to replace resources with those provided by a better performing alternative service for a particular user. In this work, we demonstrate the prevalence of under-performing services on the web, finding that over 60% of the Alexa Top 500 have at least one under-preforming server. We further evaluate Oak on experimental and popular existing webpages, and demonstrate its effectiveness in making decisions in existing environments and with a distributed user base.

In HTTP/1.1, it is necessary for the client to request an object (e.g. an image in a page) in order for the server to send it, even if the server knows in advance what the client will need. Server Push is a feature introduced in HTTP/2 that promises to improve page load times (PLT) by having the server push content to the browser in advance. In this paper, we investigate the benefits and challenges of using Server Push on mobile devices. We first examine whether pushing all content or just the CSS and Javascript files performs better, and find the former leads to much better web performance. Also, we find that sites making use of domain sharding or which otherwise have content divided across many servers do not benefit much from Server Push, a major challenge for Server Push going forward. Network performance characteristics also play a major role. Server Push is especially effective at improving performance at high loss rates (16% median PLT reduction with a 2% loss rate) and high latencies (14% PLT reduction with 100 ms latency), and has little benefit for high-speed Ethernet connections. This motivates its use on mobile devices, although we also find the limited processing power of these devices limits the benefits of Server Push. Server Push also offers modest energy benefits, with energy savings of 9% on LTE for one device. Overall, Server Push is a promising approach for improving web performance in mobile networks, but there are a number of challenges in achieving the full benefits of Server Push.

Web developers use base64 formats to include images, fonts, sounds and other resources directly inside HTML, JavaScript, JSON and XML files. We estimate that billions of base64 messages are decoded every day. We are motivated to improve the efficiency of base64 encoding and decoding. Compared to state-of-the-art implementations, we multiply the speeds of both the encoding (~10x) and the decoding (~7x). We achieve these good results by using the single-instruction-multiple-data (SIMD) instructions available on recent Intel processors (AVX2). Our accelerated software abides by the specification and reports errors when encountering characters outside of the base64 set. It is available online as free software under a liberal license., software at https://github.com/lemire/fastbase64

In this paper, we present WePR, a web performance measurement tool for evaluating the download and the rendering time of a website at large scale. The first component of the tool, WebPerf, measures the technical metrics of a website such as DNS lookup time, TCP connection establishment time, page download time from different vantage points. The second component renders the website based on the metrics recorded by the WebPerf and measures the rendering time of the website in a browser window. The user experience on a website is then inferred from the measured rendering time. Along with describing WePR's architectural design and the metrics it measures, we present initial measurement results recorded March to August 2015. The results show that transmission latency, DNS lookup time, the number of HTTP elements affect the rendering time of the website and therefore the end user experience.

Web page performance is becoming increasingly important for end users but also more difficult to provide by web developers, in part because of the limitations of the legacy HTTP/1 protocol. The new HTTP/2 protocol was designed with performance in mind, but existing work comparing its improvements to HTTP/1 often shows contradictory results. It is unclear for developers how to profit from HTTP/2 and whether current HTTP/1 best practices such as resource concatenation, resource embedding, and hostname sharding should still be used. In this work we introduce the Speeder framework, which uses established tools and software to easily and reproducibly test various setup permutations. We compare and discuss results over many parameters (e.g., network conditions, browsers, metrics), both from synthetic and realistic test cases. We find that in most non-extreme cases HTTP/2 is on a par with HTTP/1 and that most HTTP/1 best practices are applicable to HTTP/2. We show that situations in which HTTP/2 currently underperforms are mainly caused by inefficiencies in implementations, not due to shortcomings in the protocol itself. This work is part of the imec ICON PRO-FLOW project. Robin Marx is a SB PhD fellow at FWO, Research Foundation - Flanders, project number 1S02717N

Globalization has made a remarkable impact on the university education system, and the Internet has become the core resource for universities to make their facilities and opportunities available globally. University Web sites are increasingly used for a wide variety of purposes. The evaluation of universities based on their Web performance was introduced by Cybermetrics Lab as the "Webometric Ranking of World Universities" (WRWU), and this ranking system has become a popular way of measuring university excellence.

The number and size of resource constituting the web page has been increasing steadily, and this circumstance leads to rapidly falling quality of web service in mobile network that offer relatively higher delay. Moreover, Improving the quality of a web services protocol is difficult to provide network function because the current network architecture has closed structure. In this paper, we suggest schemes to enhance web performance in mobile network, which are Check Coded DOM scheme and Functional JavaScript Transmission scheme, and then try to seek idea which can be provided suggested schemes as a network function using NFV(Network Function Virtualization). For the performance evaluation and analysis about the suggested schemes, we perform network simulation using SMPL library. We confirm that suggested schemes offer better performance in term of page loading time, the number of message and the amount of traffic in the network than HTTP Protocol. 논문 14-39B-06-10 The Journal of Korea Information and Communications Society '14-06 Vol.39B No.06 http://dx.doi.org/10.7840/kics.2014.39B.6.414 414 ※ 이 논문은 0000년도 정부(미래창조과학부)의 재원으로 한국연구재단-차세대정보・컴퓨팅기술개발사업의 지원을 받아 수행된 연구임 (NRF-2010-0020727) First Author : Kyunghee University Department of Computer Engineering, kimgijeong@khu.ac.kr, 학생회원 ° Corresponding Author : Kyunghee University Department of Computer Engineering, drsungwon@khu.ac.kr, 정회원 논문번호:KICS2014-05-198, Received May 27, 2014; Revised June 19, 2014; Accepted June 19, 2014 논문 / 모바일 네트워크에서 SDN/NFV 기반의 웹 성능 향상을 위한 웹 캐시 일관성 제공과 JavaScript 전송 가속화 방안

To provide Qos in distributed web systems, it is necessary to perform predicting in web systems. Then provide prediction technique on time and space of web resource downloaded using turning bands geostatistical simulation method. Web resources are obtained from a group of web servers worldwide by multi agent measurement systems which continuously monitor the web servers located in different geographical localization. The outcome of high-quality of Web performance calculation completed by resources of the Turning bands method, particularly in the situation when we place the Web servers were monitored by a Multi-agent Measurement Systems (MWING) localized in Poland. By means of satellite navigation system real life data like accident cases, first aid rescuers can accurately locate the place within certain specified range with maximum error control, so that the injured people can be saved as soon as possible. This method will save time or the areas in the outer part of the main zone.

Recent development of Distributed computer systems (DCSs) in networked industrial and manufacturing applications on the World Wide Web (WWW) platform, including service-oriented architecture and Web of Things QoS-aware systems, it has become important to predict the Web performance prediction in time and in space .In this paper, we present Web performance prediction in time by making a forecast of a Web resource downloading using the Turning Bands (TB) geostatistical simulation method. Real-life data for the research were obtained from our own website named "Distributed forecasting system". We generate log file form our website and performing monitoring of a group of Web clients from connected LAN. For better web forecasting we used spatio temporal prediction method with time utility for downloading particular file from website with locations. Also perform comparison study in between spatio temporal method & TB methods. The results show good quality of Web performance prediction using the TB method. Keyword: Distributed Computer System ,Turning Band,, Qos-Aware Systems, Geostatistics, Spatio-Temporal Prediction.

Monitoring and evaluation is a part of management that must be done if want to an increase, and improvement in performance. Therefore, these activities are needed as an effort to develop, manage and optimize the Biodiversity Resource Portal. This study aims to analyze the efficiency of the Biodiversity resource portal of the key performance indicators on Image and script (CSS / JScript) content. Pre-Test and Post-Test analysis methods using Web Performance Optimization Techniques. Evaluation the test results showed an increase in end-to-end web performance after optimization, from the efficiency score of pretest Grade F (13%) to Grade B (82%) post-test.

The aggregation of web performance (page count and visibility) of internal university units could constitute a more precise indicator than the overall web performance of the universities and, therefore, be of use in the design of university web rankings. In order to test this hypothesis, a longitudinal analysis of the internal units of the Spanish university system was conducted over the course of 2010. For the 13800 URLs identified, page count and visibility was calculated using the Yahoo API. The internal values obtained were aggregated by university and compared with the values obtained from the analysis of the university general URLs. The results indicate that, although the correlations between general and internal values are high, internal performance is low in comparison to general performance, and that they give rise to different performance rankings. The conclusion is that the aggregation of unit performance is of limited use due to the low levels of internal development of the websites, and so its use is not recommended for the design of rankings. Despite this, the internal analysis enabled the detection of, amongst other things, a low correlation between page count and visibility due to the widespread use of subdirectories and problems accessing certain content.

With the increasing development of distributed computer systems (DCSs) in networked industrial and manufacturing applications on the World Wide Web (WWW) platform, including service-oriented architecture and Web of Things QoS-aware systems, it has become important to predict the Web performance. In this paper, we present Web performance prediction in time and in space by making a forecast of a Web resource downloading using the Turning Bands (TB) geostatistical simulation method. Real-life data for the research were obtained in an active experiment conducted by our multi-agent measurement system MWING performing monitoring of a group of Web servers worldwide from agents localized in different geographical localizations in Poland. The results show good quality of Web performance prediction made by means of the TB method, especially in the case when European Web servers were monitored by an MWING agent localized in Gliwice, Poland.

At present, online teaching platform has become an important part of modern education. With the emergence of a large number of online teaching platform, people are increasingly high demand for online teaching platform. Html5 technology is the latest Web standard, has a strong Web performance, Flex technology is currently the most widely used RIA technology. This paper presents the use of Html5 technology and Flex technology to build an online teaching RIA platform, through the realization of web video, audio, electronic whiteboard, camera camera, web graphics and other functions will be the network teaching become rich and vivid, greatly improving the user experience.

Page load speed reflects the website´s performance. It has a significant influence on user experience and satisfaction. In this work we study and analyze the reasons cause the slowness of webpages laod speed. By the deep invistigation of the related literature and the reviwe of websites’s speed testing services from different perspectives such as functions, interface and additional settings. We present a detailed recommendations that can be followed to optimize site's performance. Our hypotheses about reliability of website speed testing has been tested and conformed experimentally. 378 individual speed tests with various combinations of settings experiemnts have been performed to confirm out hypotheses, and recommendations have been provided based on our results. We believe that following these rules would ensure significantly more reliable website speed testing in comparison with a common practice.

The goals of this paper is to implement classification technique in web usage mining to a bank company that can help the company to identify web performance issue. Web usage mining consists of three phases: data preprocessing, pattern discovery, and pattern analysis. In pattern discovery phase, we propose to use classification technique with k-nearest neighbor algorithm implemented with standardized Euclidean distance to classifying frequent access pattern. The result shows that the k-nearest neighbor algorithm can be implemented in web usage mining and can help company to find interesting knowledge in web server log.

HTTP/2 is the next-generation Web protocol based on Google's SPDY protocol, and attempts to solve the shortcomings and inflexibilities of HTTP/1.x. As smartphones become the main access channel for Web services, we are curious if HTTP/2 can really help the performance of Web browsing. In this paper, we conduct a measurement study on the performance of HTTP/2 and HTTPS to reveal the mystery of HTTP/2. We clone the Alexa top 200 websites into our own server, and revisit them through HTTP/2-enabled proxy, and HTTPS-enabled proxy, respectively. We compare HTTP/2 and HTTPS as a transport protocol to transfer Web objects to identify the factors that may affect HTTP/2, including Round-Trip Time (RTT), bandwidth, loss rate, number of objects on a page, and objects sizes. We find that HTTP/2 hurts with high packet loss, but helps many small objects. The computation and dependencies of fetching Web objects reduce the performance improvement of HTTP/2, and sometimes can even hurt the performance of page loading. At last, we test the server push feature of HTTP/2 to leverage the performance.

The transition of businesses to the digital marketplace has presented many opportunities andchallenges for e-commerce and ICT services providers. This research was carried out during theongoing diffusion of a technological innovation, at Telia Company's Content Delivery Network(CDN) unit, in a bid to understand the technology adoption process. The researchers' approachwas to get insights from different stakeholders in the Swedish e-commerce industry and tocompare the qualitative research findings with theoretical secondary data and definitions. Sixinterviews were performed, constituting the empirical data. After the analysis and discussion ofthe results and frameworks, the researchers propose a merged theoretical framework thatcould be used for designing compelling value propositions, and as such improve the conveyingof the value of an offering. The thesis concludes with recommendations to further validate theproposed framework through further research.

The transition of businesses to the digital marketplace has presented many opportunities and challenges for e-commerce and ICT services providers. This research was carried out during the ongoing diffusion of a technological innovation, at Telia Company's Content Delivery Network (CDN) unit, in a bid to understand the technology adoption process. The researchers' approachwas to get insights from different stakeholders in the Swedish e-commerce industry and to compare the qualitative research findings with theoretical secondary data and definitions. Six interviews were performed, constituting the empirical data. After the analysis and discussion of the results and frameworks, the researchers propose a merged theoretical framework thatcould be used for designing compelling value propositions, and as such improve the conveying of the value of an offering. The thesis concludes with recommendations to further validate the proposed framework through further research.

The widespread adoption of high speed Internet access and it's usage for everyday tasks are causing profound changes in users' expectations in terms of Web site performance and reliability. At the same time, server management is living a period of changes with the emergence of the cloud computing paradigm that enables scaling server infrastructures within minutes. To help set performance objectives for maximizing user satisfaction and sales, while minimizing the number of servers and their cost, we present a methodology to determine how user sales are affected as response time increases. We begin with the characterization of more than 6 months of Web performance measurements, followed by the study of how the fraction of buyers in the workload is higher at peak traffic times, to then build a model of sales through a learning process using a 5-year sales dataset. Finally, we present our evaluation of high response time on users for popular applications found in the Web.

Broadband characterization has recently attracted much attention from the research community and the general public. Given this interest and the important business and policy implications of residential Internet service characterization, recent years have brought a variety of approaches to profiling Internet services, ranging from Web-based platforms to dedicated infrastructure inside home networks. We have previously argued that network-intensive applications provide an almost ideal vantage point for broadband service characterization at sufficient scale, nearly continuously and from end users. While we have shown that the approach is indeed effective at characterization and can enable performance comparisons between service providers and geographic regions, a key unanswered question is how well the performance characteristics captured by these network-intensive applications can predict the overall user experience with other applications. In this paper, using BitTorrent as an example network-intensive application, we present initial results that demonstrate how to obtain estimates of bandwidth and latency of a network connection by leveraging passive monitoring and limited active measurements from network intensive applications. We then analyze user experienced web performance under a variety of network conditions and show how estimated metrics from this network intensive application can serve as good web performance predictors.

Among a myriad of spider web geometries, the orb web presents a fascinating, exquisite example in architecture and evolution. Orb webs can be divided into two categories according to the capture silk used in construction: cribellate orb webs (composed of pseudoflagelliform silk) coated with dry cribellate threads and ecribellate orb webs (composed of flagelliform silk fibres) coated by adhesive glue droplets. Cribellate capture silk is generally stronger but less-extensible than viscid capture silk, and a body of phylogenic evidence suggests that cribellate capture silk is more closely related to the ancestral form of capture spiral silk. Here, we use a coarse-grained web model to investigate how the mechanical properties of spiral capture silk affect the behaviour of the whole web, illustrating that more elastic capture spiral silk yields a decrease in web system energy absorption, suggesting that the function of the capture spiral shifted from prey capture to other structural roles. Additionally, we observe that in webs with more extensible capture silk, the effect of thread strength on web performance is reduced, indicating that thread elasticity is a dominant driving factor in web diversification.

PurposeIn the hotel industry today, web site marketing and third party distribution metrics are of critical importance in understanding the effectiveness of hotel revenue management objectives. The purpose of this paper is to propose a new model which tests hotel web‐effectiveness using the following variables: reach, content, consistency and price parity (RCO2P).Design/methodology/approachFor the current RCO2P study, the hotel sample was broken down into two segment groupings of five hotels: luxury; and upper‐upscale. The ten full‐service hotels were monitored over a 90‐day period using room rate quotations and ordinal values across 14 dimensions based on three pre‐selected arrival dates.FindingsResults of the RCO2P study indicated preferential display sequencing emerged as a significant factor in the reach category among all hotel properties reviewed. Only six of ten properties were measured as having achieved optimal web‐effectiveness, while poor price‐parity competency reflected the most situation‐critical performance among sampled hotel properties.Originality/valueInternational comparative research methodologies were examined and determined to be effective models of certain hotel web‐effectiveness dimensions; however, a comprehensive hotel web‐effectiveness measurement model is still lacking which can better inform hotel industry executives. Therefore, future research should incorporate a best practice research approach combining the current RCO2P study elements with other web‐effectiveness measurement criteria based on the collective best practices identified among the research studies reviewed.

Client-perceived web performance prediction is a challenging for the knowledge engineering community. This article presents the application of the turning bands TB method to discover knowledge about the client-perceived spatiotemporal web performance. The TB method is used to study spatial or spatiotemporal phenomena. We conducted an experimental study to apply this technique. The MWING system was used to collect performance measurement for four clients, each monitoring the same group of web servers during several weeks of observations. In this article we present TB-based web performance prediction for an agent localized in Wroclaw, Poland, and monitoring European web servers. The results of the spatial prediction of the total download web page times within a forecast of a two-week period showed that the TB simulation is efficient.

Although Internet service providers and communications companies are continuously offering higher and higher bandwidths, users still complain about the high latency they perceive when downloading pages from the web. Therefore, latency can be considered as the main web performance metric from the user's point of view. Many studies have demonstrated that web prefetching can be an interesting technique to reduce such latency at the expense of slightly increasing the network traffic. In this context, this paper presents an empirical study to investigate the maximum benefits that web users can expect from prefetching techniques in the current web. Unlike previous theoretical studies, this work considers a realistic prefetching architecture using real traces. In this way, the influence of real imple- mentation constraints are considered and analyzed. The results obtained show that web prefetching could improve page latency up to 52% in the studied traces. ©Springer Science+Business Media, LLC 2011

In order to improve the QoS of applications, clusters of web servers are increasingly used in web services. Caching helps improve performance in web servers, but is largely exploited only for static web content. With more web applications using backend databases today, caching of dynamic content has a crucial role in web performance. This paper presents a set of cache management schemes for handling dynamic data in web clusters by sharing cached contents. These schemes use either automatic or expiry-based cache validation, and work with any type of request distribution. The techniques improve response by utilizing the caches efficiently and reducing redundant database accesses by web servers while ensuring cache consistency. The authors present caching schemes for both horizontal and vertical cluster architectures. Simulations show an appreciable performance rise in response times of queries in clustered web servers.

The long-term success of the World Wide Web depends on fast response time. People use the Web to access information from remote sites, but do not like to wait long for their results. The rapid growth in the amount of information and the number of users has lead to difficulty in providing effective response time for the web users and this increased web latency; resulting in decreased web performance. Although several proposals have been made for reducing this latency, like it can be improved by caching, the benefit of using it is rather limited owing to filling the cache with documents without any prior knowledge.Predictive caching becomes an attractive solution wherein the forthcoming page likely to be requested soon are predicted based on user access logs information and pre-fetched ,while the user is browsing the current display pages. As web page prediction gained its importance, This paper proposes a bracing approach for increasing web server performance by analyzing user behavior, in this pre-fetching and prediction is done by pre-processing the user access log and integrating the three techniques i.e. Clustering, Markov model and association rules which achieves better web page access prediction accuracy;This work also overcomes the limitation of path completion i.e. by extracting web site structure paths are completed,which helps in better prediction, decreasing access time of user and improving web performance.

JavaScript is widely used to offer interactive web service and dynamic content. However, the number and size of JavaScript constituting the web page has been increasing steadily, and this circumstance leads to falling web performance. In this paper, we suggest a scheme for acceleration of JavaScript transmission considering software module reusability. We perform network simulation for the performance evaluation and analysis about the suggested scheme, and then confirm that the suggested scheme offers better performance in term of page loading time and the amount of traffic generated in the network than the transmission method using Gzip.