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Creating descriptive categories and filenames for the documents on your website can not only help you keep your site better organized, but it could also lead to better crawling of your documents by search engines.
Lastly, remember that the URL to a document is displayed as part of a search result in Google, below the document’s title and snippet.
Below is another example showing a URL on our domain for a page containing an article about the rarest baseball cards.
Google is good at crawling all types of URL structures, even if they’re quite complex, but spending the time to make your URLs as simple as possible for both users and search engines can help. Titles for deeper pages on your site should accurately describe the focus of that particular page and also might include your site or business name.
Widget RSSLinux Howtos – Raid1 Setup On CentOS5 February 26, 2011This Howto covers Raid1 setup on preinstalled Centos 5.5 system. The new and improved healthcare.gov website shows some signs of improvement, but many of the issues we found in the previous analysis are still present (see Figure 2). Healthcare.gov shows some improvements in above the fold metrics, but the page has become more complex and slower to load. The new healthcare.gov web site showed some improvements in "above the fold" speed, but slower load times and more complexity than the old version. This article evaluates the website performance issues of the healthcare.gov site, and offers some solutions to improve speed.
Makers of performance products including Fastview (formerly Strangeloop Network's Site Optimizer). Automated website acceleration products can speed up your site without developer intervention. Increase conversions with adaptive multivariate testing to squeeze more leads out of your exiating traffic. Improve your site's look, usability and accessibility for a more credible and successful website. Millions of Americans wanting to enroll in Obamacare use the healthcare.gov official website. The home page of healthcare.gov grew significantly in size and complexity over the past year. With the larger page size and complexity, the page load times and "above the fold" times increased proportionally for healthcare.gov. So the site is clearly larger and slower, but how consistent is the response time under load? One nice feature about the website is that you can create your health plan in stages, and come back later to finish (see Figure 7).
Unfortunately selecting a dental insurance plan spawned the following error repeatedly, despite numerous phone calls to the help line (see Figure 8). While the healthcare.gov website has improved in availability and consistency, performance problems remain one year later.
To test President Obama's promise that the new healthcare.gov web site would be fixed by December 1, we speed audited the improved site. New Delhi, Twitter Advertisement company in aurangabad, Twitter Advertisement company in jodhpur, Twitter Advertisement company in vijaywad, Twitter Advertisement company in guwahati, Twitter Advertisement company in hubli, Twitter Advertisement company in dhanbad, Twitter Advertisement company in dharwad, Twitter Advertisement company in tiruchirappalli, Twitter Advertisement company trivandrum, Twitter Advertisement company in mysore, Twitter Advertisement company in navi mumbai, Twitter Advertisement company in jalandhar, Twitter Advertisement company in ambala, Twitter Advertisement company in hisar, Twitter Advertisement company in bareily, Twitter Advertisement company in kota, Twitter Advertisement company in salem, Twitter Advertisement company in aligarh, Twitter Advertisement company in bhubaneswar, Twitter Advertisement company in moradabad, Twitter Advertisement company in noida, mass mail company in india, Twitter Advertisement company gorakhpur, Twitter Advertisement company in allahabad, Twitter Advertisement company in rajpur, Twitter Advertisement company in bhiwandi, Twitter Advertisement company in kochi, Twitter Advertisement company in jamshedpur, Twitter Advertisement company in bhilai nagar, Twitter Advertisement company in amravati, Twitter Advertisement company in cuttak, Twitter Advertisement company in bikaner, Twitter Advertisement company in warangal, Twitter Advertisement company in mire, Twitter Advertisement company in guntur, Twitter Advertisement company in bhavnagar, Twitter Advertisement company in durgapur, Twitter Advertisement company in asansol, Twitter Advertisement company in ajmer, Twitter Advertisement company kolhapur, Twitter Advertisement company i ulhasnagar, Twitter Advertisement company in siliguri, Twitter Advertisement company in saharanpur, Twitter Advertisement company in dehradun, Twitter Advertisement company in jamnagar, Twitter Advertisement company in bhatpara, Twitter Advertisement company in dewas, Twitter Advertisement company in indore, Twitter Advertisement company in sangli miraj & kupwad, Twitter Advertisement company in kozhikode, Twitter Advertisement company in nanded waghala, Twitter Advertisement company in ujjain, Twitter Advertisement company in gulbarga, Twitter Advertisement company in tiruneveli, toll free no. New Delhi, bulk sms company in bikaner, bulk sms company in warangal, bulk sms company in mire, bulk sms company in guntur, bulk sms company in bhavnagar, bulk sms company in durgapur, bulk sms company in asansol, bulk sms company in ajmer, bulk sms company kolhapur, bulk sms company i ulhasnagar, bulk sms company in siliguri, bulk sms company in saharanpur, bulk sms company in dehradun, bulk sms company in jamnagar, bulk sms company in bhatpara, bulk sms company in dewas, bulk sms company in indore, bulk sms company in sangli miraj & kupwad, bulk sms company in kozhikode, bulk sms company in nanded waghala, bulk sms company in ujjain, bulk sms company in gulbarga, bulk sms company in tiruneveli, toll free no. For his doctoral thesis at the University of Glasgow, Thiam Kian Chiew studied web page performance. Unlike most research into web performance that deals with server and network issues, Chiew's thesis focused on the performance analysis of web pages themselves. Web page response time is the most straightforward metric in quantifying user satisfaction (Hoxmeier & DiCesare, 2000). As bandwidth has increased (more than 63% of the US is now on broadband), so have user expectations towards response times. The response time of downloading a Web page can be decomposed into its constituent components. The particular Web page response time will be affected by identifiable characteristics of the Web pages. It is possible to provide recommendations for resolving or relieving some of the identified performance problems that may cause poor response time based on the identified characteristics that affect Web page response time.
This Chapter provides background information and research into computer system performance as it relates to the Web.
States the problems to be addressed and the framework as well as approaches for addressing the problems. This chapter introduces two Web page response time measurement methods (the Muffin proxy, and the Frame method), which allow response time to be decomposed into three of its constituents, i.e.
This chapter explains the complexity of Web pages from two perspectives: creation and content. This chapter shows how Web page response time and responsiveness can be monitored and estimated based on server access log analysis.


Describes two scenarios to show how the measurement, modelling, and monitoring modules can be used in Web page design to produce Web pages that deliver satisfactory response times. The author discusses server-side and network performance techniques such as caching, prefetching, content delivery networks, load balancing, and server tuning briefly.
There is a significant amount of overhead in serving dynamic content (Titchkosky et al., 2003). In actual tests of instrumented web pages the author found the effects of different techniques (see Table 2).
In terms of content, web page complexity is largely made up of the number of embedded objects in a web page, and its total size. The amount of HTML code affects the response time of a web page, but not as much as the number of embedded objects or total page size. The response time of a web page grows in proportion to the number of embedded objects in the page (see Figure 2).
The response time of a web page is proportional to the total size of the page (see Figure 3). Chiew went on to test the effects of JavaScript, CSS, programming constructs, and database access. Chiew went onto model web page complexity with six components, and created software modules to model, measure, monitor, and improve web page response times.
This research into web page performance quantifies what web page attributes effect response times the most. If your URL contains relevant words, this provides users and search engines with more information about the page than an ID or oddly named parameter would.
Like the title and snippet, words in the URL on the search result appear in bold if they appear in the user’s query.
If you do find that people are accessing the same content through multiple URLs, setting up a 301 redirect from non-preferred URLs to the dominant URL is a good solution for this. The site showed some improvements in "above the fold" speed, but slower load times than the old version.
The old site was notoriously slow and spawned many "wait" error messages for users looking for health care.
The engineers at healthcare.gov wanted faster display of useful content, which is what these metrics measure.
To see how much speed can be squeezed out of this page, we asked the folks at Radware to run healthcare.gov through their Fastview cloud optimization service. A brief analysis shows a number of issues that could be addressed to improve the user experience. We test the effectiveness of Radware's Fastview appliance on a test site and find significant improvements in speed.
Just over one year ago, health care consumers were directed to log on to the healthcare.gov website starting on October 1, 2013. Page size grew by 85% from 677K to 1252K (see Figure 2) and total objects grew by 172% from 40 objects to 109 objects (see Figure 3). Users seeing this error are told to wait a while to see iand try again, or delete their 2015 plan and create a new one. In the larger waterfall you'll notice the Home.png main banner image loads slowly, it was 471K!
This is smaller than the average top 1000 page size (1807K) and about the same as the average number of objects (114, source httparchive.org). Healthcare.gov home page response times have slowed down by 62% to 78%, while page size and complexity have grown by 85% to 172% over the past year. As part of his research, Chiew explored the different factors that affect web page speed, testing and modeling the key components to web page download times. But as bandwidth and user experience have increased, the guidelines for web page response times have evolved.
While the average web page size and complexity have increased significantly since the 1990s to over 315K and 50 total objects, users expect faster response times with their faster wireless and broadband connections. Explores the history of the Internet and the Web, response time research, and how this research relates to the Web.
Titchkosky found that the overhead of serving dynamic content reduced the peak rate of Apache 1.3x by up to 8 times, depending on workload conditions and the software used (see Table 1). The number of objects in a web page determines the number of round trip requests required to a server from a client. For similar pages with 5, 10, and 15 embedded objects the response times increased nearly linearly with the number of embedded objects from 955 ms, to 1527ms, to 2056 ms respectively. For similar pages with the same number of lines of code, response time grew linearly with total page size (see Figure 3). The most important factors in speeding up web page response times are minimizing the number of embedded objects and the amount of dynamic data. The researchers found that the Definition Time (DT) and Waiting Time (WT) of objects have a significant impact on the total latency of web object retrieval, yet they are largely ignored in object-level studies.


Visitors may be intimidated by extremely long and cryptic URLs that contain few recognizable words. Also, users may believe that a portion of the URL is unnecessary, especially if the URL shows many unrecognizable parameters. To learn even more about good URL structure, we recommend this Webmaster Help Center page on creating Google-friendly URLs.
Just in time, President Obama made a pledge that the site would be fixed (with a new performance czar) by the end of November. Unfortunately, the number of objects has increased since the older version from 40 objects onload to 60, and 44 fully loaded objects to 83 requests (see Figure 2). The site didn't have as many "waiting room" delays as before, but still spawned a few errors (see Figure 6).
This was our initial analysis of the site shortly after it officially launched in October 2013. Instead of being the result of server and network conditions, Chiew treats response time as an attribute of web pages. Schneiderman established in the 1980s that 1-2 second response times were ideal and that 15 seconds was a tolerable wait time (TWT - Schneiderman 1984). The current guidelines on response times have split into faster response times for broadband users (3-4 seconds) and slower response times for dial-up users (on the order of 8-10 seconds).
With the average number of embedded objects now over 50 per web page, object overhead now dominates the latency of most web pages (Yuan 2005).
So a 200% increase in embedded objects (from 5 to 15 objects) gave a 113% increase in response time (from 955 to 2056 ms).
As page size grew from 1501, to 2001, to 2501 bytes, response time grew from 751, to 806, to 860 milliseconds respectively.
The number of embedded objects was 2.6 times more costly than total page size for response time. The DT and WT composed from 50 to 85% of total wait time, depending on the number of objects in a page.
To test his promise, we reviewed the site shortly after that deadline, in early December (see Figure 1).
Figure 4 shows the home page waterfall with no fastview treatment on a NY cable connection.
To address response time, Chiew proposes a framework of measurement, modeling, and monitoring. As the Internet and the Web emerged into the general modem-toting public in the 1990s, longer response times were tolerated, on the order of 8-12 seconds without feedback, and 20 to 30 seconds or more with feedback (King 2003).
The author set about to test the web page attributes that contribute to response times, including lines of code, embedded objects, total page size, and JavaScript and CSS usage.
So on average a 100% increase in embedded objects would yield a 56.5% increase in response time. He found that more session variables in a cookie does not have a significant effect on response time. In 1996 Jacob Nielsen wrote that 10 seconds was the maximum response time before a user loses interest (Nielsen 1996). Towards that end this research provides test results to compare different optimization techniques, as well as software tools for modeling and monitoring web page performance.
This shows that longer pages with the same page size will have slightly longer response times than shorter pages of the same file size.
Since cookies contain a small amount of textual information, more session variables mean a slightly larger text load, but still a small payload overall.
The number of lines of code and the size of cookies were found to affect response times the least. To see how much the site could be improved further, we had our friends over at Radware test the site with their automatic optimization software called Fastview, which we reviewed in a previous article. Using this framework, web developers can assess that web pages can meet or reduce tolerable wait times to ensure higher user satisfaction with web sites.
Zona Research published an oft-cited study for Akamai that offered the 8 second rule (Zona 1999). These figures show that, under the conditions of this test, embedded objects affect response times nearly 2.6 times more than total page size.
In early 2003, my first book found that the average TWT was 8.6 seconds, for the current conditions (King 2003).



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