Performance analysis of 5A's web robots

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1 Scientific Research and Essays Vol. 6(12), pp , 18 June, 2011 Available online at DOI: /SRE ISSN Academic Journals Full Length Research Paper Performance analysis of 5A's web robots Ijaz Ali Shoukat and Mohsin Iftikhar College of Computer and Information Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia. Accepted 6 May, 2011 Human nature is greedy to follow less effort heuristics in seeking of scientific literature. Despite of manual literature investigation, web robots are vital tools that provide vision to gigantic passageway of WWW (World Wide Web) knowledge for information seekers. The reputation and implication of web robots need not be introduced further. Optimal searching approach requires efficient response and reliable services with limited time to quest large array of worldwide information. The list of search engines is too vast with varying index size and performance characteristics. This study evaluates performance metrics like (1) response time, (2) load, (3) page download time, (4) health status, (5) down time, (6) uptime and (7) reliability for popular search engines (AOL, Ask, AltaVista, Alltheweb, Aliweb) starting with initial alphabetic A so called 5A s Web Robots. These 5A s crawlers have not been evaluated with such technical characteristics before. This paper evaluates selected web robots under practical estimation of technical factors with maximum capacity of seven effective performance metrics. We used two web bench marking tools (Mange Engine Application Manager and Web Application Testing WAPT 6.0) under active probing techniques to obtain experimental results as this approach has active literature support. Finally, this study concludes new and beneficial results for researchers. Key words: Performance analysis, web robots, search engine s evaluation, hybrid, Meta crawlers. INTRODUCTION WWW (World Wide Web) domain has effective and painstaking influence from last two decades with massive growth. Researchers, scientists, students and teachers are trendier to use search engines rather to library or other physical searching resources. Nowadays, web searching tools have revolutionary impact in science and discoveries. A long list of searching tools is available but in this paper we studied only some popular tools as summarized in Table 1. Web robots are same term as web spiders or web crawlers or the search engines. Web robots or search engines can be categorized into five classifications: (1) Primary Crawlers like Google, Yahoo, MSN, Aliweb and Ask as these all have their own indexing database with ability to cache some parts of file automatically. (2) Meta crawlers like AOL, Excite, Altavisat, Lycos, AlltheWeb and Dogpile do not maintain their own indexing database but lend services from two or *Corresponding author. ishoukat@ksu.edu.sa. more primary robots to show searching result in combined fashion for end user. (3) Hybrid crawlers like Mamma search engine follows the combined approach of Meta search engine and primary search engine in such a way they posses their own indexing database as well as lend services from two or more primary robots to show large capacity of searching results in combined fashion. (4) Human powered scholar directories like IEEE explorer, ACM, and OpenJGate have their own document databases built by scholars. (5) Informative Paid or free Inclusion like Scribd and DocStoc maintain their own database to store open quality public documents with pay or without pay. These kinds of directories are open access that is why their documents have no quality. In this paper, we evaluated the five web crawlers (Altavista, Ask, AOL, Alltheweb, Aliweb) with large capacity of seven performance metrics with large selection of search engines because previous studies provide limited criteria for comparative analysis with limited number of search engines. Previous studies ignored most important performance metrics like up time, down time, meant

2 Shoukat and Iftihkar 2565 Table 1. Category and ranking of web crawlers. Search engine Starting year (Dujmović and Bai, 2006) Information coverage Category Popularity ranking Aliweb 1993 Primary robot ** Ask 1996 Hybrid search engine as it has its own indexing database and it is also powered by Teoma (Das and Nandy, 2010) ****** Altavista Meta robot ******* AlltheWeb 1999 Meta Power by Yahoo ** AOL 2003 Meta search engine powered by Google *** Lycos 1995 Dogpile 1996 Meta search engine as it fetches results from yahoo and Looksmart Meta search engine powered by Google, Yahoo!, Bing and Ask *** **** Teoma 2001 Primary search engine with small indexing database. Teoma contains indexes of 200 million pages (Sherman, 2002) *** time between failures (MTBF), mean time to repair (MTTR) and health severity for all search engines related studies but this study provides comparative evaluation of selected search engines with all these factors in addition to response time and reliability. We also concluded that a day of week with more loads which means least response and most loaded hour among 24 h which means least response and vice versa. We implemented active probing (Cherkasova et al., 2002) technique by utilizing two web application bench marking tools: Mange Engines Application Manager by Zoho Corporation and Web Application Testing Tool (WAPT 6.0), which is a consistent and cost effective approach (Vail, 2005; Gupta et al. (2010; Horák et al., 2009; Rajput et al., 2010) used to obtain experimental results. LITERATURE REVIEW In 2006, Dujmović and Bai (2006) reported that prelimnary effort on searching techniques was started in 1993 and later on it became the part of published literature (Chu and Rosenthal, 1996). Many studies (Sherman, 2002; Das and Nandy, 2010; Baeza-Yates and Ribeiro- Neto, 1999; Chakrabarti, 2003; Jones and Willett, 1997; Hawking, 2006) have been published in next decade from 1993 in order to enhance the searching methodology for public use. Four search engines, Google, Yahoo, Msn and Ask have been quantitatively evaluated by using LPS method in which Google remained superior than Msn and MSN is proved better than Yahoo (Dujmović and Bai, 2006). A comparative analysis of server side and client side searching tools was reported in a study (Chau et al., 2002) in which design of two techniques was discussed in the light of advantages and diversities to conclude, that the selection of searching methods are concerned with the motive of their development and usages limit. McCown and Nelson (2007) conducted a study for analyzing the Application Programming Interfaces (APIs) and Web User Interfaces (WUIs) of Google, Yahoo and MSN. In this study, the measurement methodology was observing the top 10 and 100 search results against a variety of searching quires. The other metrics for this evaluation were total number of indexing of web pages and caching of URLs. Consequently, the same study of McCown and Nelson (2007) concluded that MSN APIs are able to produced good results than Google and Yahoo APIs because Yahoo and Google APIs are not older but smallest than MSN. According to Bar-Iian (1998), when we search some information via search engines, some information is lost or dropped by the same search engine and might be possible to lost measurable portion of information in subsequent tries. In Bar-Ilan (1998) study, six search engines, Altavista, Excite, Hotbot, Infoseek, Lycos and NothernLight were evaluated with a query Informetrics or Informetric as their results shown in Table 2. Now, the web storage has been increased to 11.5 Billion pages (Gulli and Signorini, 2005). To investigate the overlaps among major search engines the Spink and Jansen (2006) collected random queries from a search engine named as Dogpile. After that, an overlap

3 2566 Sci. Res. Essays Table 2. Relative coverage of search engines (Bar-Ilan, 1998). Search tools Total relative coverage (%) Average relative coverage (%) Relative coverage by Lawrence and Giles (%) Relative coverage by Bharat and Broder (%) ALtavista Excite Hotbot Inforseek Lycos NorternLight algorithm is applied to collect the percentages of overlaps results with 31.5% in Yahoo, 25.8% in Google and 27.7% in Ask. On the other hand, the shared results percentage, remained 3.3% for Google and Yahoo, 6.3% for Google and Ask and 2.2% for Ask and Yahoo. The more interesting finding is that the unique results from all three search engines (Google, Yahoo and Ask) are only 3%. The notable thing is that for 26.4% queries, the results remained un-sponsored from either Yahoo or Google. In a summarized conclusion of Spink and Jansen (2006) study, overlaps among major search engines are too low. In searching point of view, the quality of searching results counts for scholars to justify their opinions. To evaluate quality metrics (corpus size, index freshness and duplication in results), Yossef and Gurevich (2007) conducted a study which adopted the sampling procedure for generating results for the aforementioned quality metrics. World Wide Web comprises of huge set of information which creates hurdles for users in terms of seeing all the set of searching results via any search engine; therefore, the ranking of results is needed. To provide this ranking support, Bar-Ilan (2005) study became the part of literature in 20, April 2005 with this statement that the ranking differs by algorithms of search engines and the better ranking depends upon the eyes of user, however the coverage against various set of queries (q1, q2, q3 qn); the number of shown results are indicated in Table 3 with coverage percentage as shown in the square brackets (Bar-Ilan, 2005). Up to date repository of search engines represents the quality of fresh indexing with new information. For checking the freshness, Dasdan and Xinh (2009) conducted a study which introduced staleness frequency measurement of already stored document as metric to check the freshness of searching repository. According to this study, if a Link or pages is viewed or clicked too many times, it means it is old and not fresh and which pages is clicked or viewed only few times it means it is fresh. Rangaswamy et al. (2009) reported the importance of search regarding the business point of view in such a way what we can do with search engines exactly? Some layman users do not professional in searching their desire information that is why sometime they are unable to find most relevant keywords regarding to their desired search. For these kind of peoples and for those information which does not indexed by search engines, the social networks play a major role by providing the facility for questioning an answering. (Morris et al. (2010) reported the comparison of social networks and search engines. Furthermore, this study differentiates the pros and cons of searching vs. asking as asking is easy with social networks and searching is easy with search engines but both have their own merits and demerits. Murugesh et al. (2010) reports the comparison of three search engines (Google, Yahoo, MSN) by analyzing two properties, (1) total search results against a same query for all three search engines, and (2) searching time for the same query by each search engine. This study found that Google is better than Yahoo and Yahoo is better than MSN. Furthermore, this study reported some other results which are shown in a Table 4. According to US Search Engine Report comscore Releases April 2009, the core percentage of search done by Google, Yahoo, MSN, Ask and AOL is as shown in a Table 5. In this study, we have practically analyzed the Google, Yahoo, MSN, Gigablast, Mamma and Excite with maximum capacity of more performance metrics. There are still no such study is available which provides the experimental analysis with such maximized exposure as we have done. MATERIAL AND METHODS In order to find out the experimental results against performance metrics like latency, response time, Page download time, availability, health status and reliability. We used active probing technique rather than Web Page Instrumentation (Cherkasova et al., 2003). Non- technical readers are referred to consult Cherkasova et al. (2003) to know the basics about active probing and web instrumentation methods. Our experimental setup follows the following steps: 1. Installation of WAPT 6.0 and Manage Engine Application Manager 9 on a single fixed point machine (Windows XP OS, RAM 2GB, Processor 2.4 GHz., firewall was disabled) at Department of Computer Science, King Saud University, Riyadh KSA. 2. Definition and creation of URL instances against each desired

4 Shoukat and Iftihkar 2567 Table 3. Result coverage (Bar-Ilan, 2005). Query No. Query Result s coverage Google AlltheWeb AltaVista HotBot Total q01 relative ranking TREC 58 [66%] 30[34%] 24[27%] 6[7%] 88 q02 SIGIR [81%] 40 [18%] 27 [12%] 30 [14%] 219 q03 everyday life information seeking 170 [65%] 114 [44%] 60 [23%] 67 [26%] 262 q04 natural language processing for IR 137 [60%] 78 [34%] 12 [5%] 63 [28%] 229 q05 multilingual retrieval Hebrew 22 [73%] 6 [20%] 4 [13%] 4 [13%] 30 q06 relative ranking IR 568 [72%] 292 [37%] 114 [37%] 56 [7%] 792 q07 social network analysis information retrieval 748 [67%] 408 [36%] 169 [15%] 206 [18%] 1120 q08 link mining 269 [58%] 209 [45%] 115 [25%] 84 [18%] 464 q09 citation analysis link structure 377 [58%] 157 [24%] 65 [10%] 57 [9%] 652 q10 bibliometrics link analysis 315 [82%] 106 [28%] 60 [16%] 46 [12%] 382 q 11 relevance ranking link analysis 1000 (1640) [56%] 696 (1233) [39%] 426 (708) [24%] 345 (540) [19%] 1791 q 12 Cross-language retrieval 1000 (2480) [40%] 1093 (5675) [44%] 1000 (1100) [40%] 421 (840) [17%] 2477 q 13 Question answering IR 1000 (3960) [37%] 1088 (8346) [40%] 1000 (1177) [37%] 671 (1492) [25%] 2709 q 14 information retrieval 1000 (1,090,000) [34%] 1100 (1,091,278) [38%] 994 (264,826) [34%] 449 (247,992) [15%] 2914 q 15 data mining 998 (1,730,000) [35%] 1100 (1,274,549) [39%] 963 (367,411) [34%] 450 (384,846) [16%] 2856 search engine by entering their universal domain name of their servers with interval time 10 min in each going hour. 3. Continuous monitoring of selected search engines with selected tool (s) for every hour of a day for several weeks from May to June, 2010 to get automatic reading against the desired performance bottlenecks (as mentioned earlier) 4. Finally, we analyzed and calculated average cases for getting final results.

5 2568 Sci. Res. Essays Table 4. Daily search and ranking (Murugesh et al., 2010). Search engine Daily search done (%) US research ranking Boolean search Google Limited Boolean search Index size Google does not agree on yahoo s 20 billion pages index. May yahoo has more duplicate results than Google Yahoo Better than Google 20 Billions pages MSN Offers full Boolean search??? Rest of search engines Limited index sizes or some are used the indexing of Google, Yahoo or MSN Table 5. Core percentage of search done. Search engine Core percentage of search done in April 2009 (%) Core Percentage of Search done in March 2009 (%) Google Yahoo MSN Ask AOL Response time: Min. Average: ms Max. average: ms Average: ms Figure 1. Altavista s response time. The utilized benchmarking tools have significance literature support in which one is Mange Engine Application Manger 9 by Zoho Corporation and the other is the Web Application Testing Tool (WAPT 6.0). The evaluation of WAPT reported by Vail (2005) supports its use as a consistent and cost effective approach. Many studies (Gupta and Sharma, 2010; Horák et al., 2009; Rajput et al., 2010) have used WAPT6.0 for getting their experimental results like response time, latency, availability and reliability. EXPERIMENTAL RESULTS The experimental results of top five search engines (Altavista, Ask, AOL, Alltheweb, and Aliweb) are reported subsequently with graphical representations as well as some are in tabular forms. These search engines are monitored with Manage Engine Application Manager 9 and WAPT 6.0 against every hour of each day and night for many weeks of May and June, 2010, regularly. Hourly based average response time of Altavista The average response time against each going hour of all day from May 12, 2010 to June 7, 2010 is graphically shown in Figure 2. The best average response was found at 3:00 PM and lowest response time was found at 6:00 AM which means Google usage is on peak at 6:00 AM in the whole world.

6 Shoukat and Iftihkar 2569 Figure 2. Hourly based Altavista s response time. Table 6. Altavista s response time for days of the Week. Day of week Minimum value in ms Maximum value in ms Hourly average in ms Sunday 359 8, Monday 359 8, Tuesday 0 60, Wednesday , Thursday 358 7, Friday , Saturday 359 7, Response time: Min. Average: ms Max. Average: ms Average: ms Figure 3. Ask response time. Average response time of Altavista against days of the week The average response time of Altavista against the day of week for all days has been monitor against each going hour from May 12, 2010 to June 7, 2010 as shown in a Table 6. The results of the table report that Tuesday has highest response time; while Friday has least response time which means on Thursday the Altavista is used by most of peoples in the world. Hourly based average response time of Ask The average response time against each going hour of each day from May 12, 2010 to June 7, 2010 is

7 2570 Sci. Res. Essays Figure 4. Hourly based Ask s response time. Response time: Minimum average: ms Max. average: ms Average: ms Figure 5. AOL response time. Figure 6. Hourly based response time of AOL.

8 Shoukat and Iftihkar 2571 Table 7. Ask s response time for days of the week. Day of the week Minimum value in ms Maximum value in ms Hourly average in ms Sunday 0 11, Monday 296 8, Tuesday , Wednesday , Thursday , Friday , Saturday , Response time: Minimum average: ms Max. average: ms Average: ms Figure 7. Response time of AlltheWeb search engine. graphically shown in Figure 4. Average hourly response time at 6:00 PM was found highest and lowest response time was found at 06:00 AM which means Yahoo usages is on peak at 06:00 AM in the whole world. Average response time of Ask against the day of week The average response time of Ask against the day of week for all days has been monitored against each going hour from May 12, 2010 to June 7, 2010 as shown in a Table 7. The results of the table report that Monday has highest response time, while Thursday has least response time for Ask search engine. Hourly based average response time of AOL The average response time against each going hour of all day from May 12, 2010 to June 7, 2010 is graphically shown in Figure 6. Average hourly response time at 3:00 PM was found highest and lowest response time was found at 06:00 AM which means AOL usages is on peak at 06:00 AM in the whole world. Average response time of AOL against the days of the week The average response time of AOL against the day of week for all days has been monitor against each going hour from May 12, 2010 to June 7, 2010 as shown in a Table 8. The results of the table clearly invoke that Monday has highest response time, while Friday has least response time for AOL search engine. Hourly based average response time of AlltheWeb The average response time against each going hour of all day from May 12, 2010 to June 7, 2010 is graphically shown in Figure 8. Average hourly response time at 3:00 PM was found highest and lowest response time was found at 06:00 AM which means AlltheWeb usages is on peak at 06:00 AM in the whole world. Average response time of AlltheWeb against the day of week The average response time of AlltheWeb against the day

9 2572 Sci. Res. Essays Table 8. AOL s response time against days of the week. Days of the week Minimum value in ms Maximum value in ms Hourly average in ms Sunday , Monday , Tuesday , Wednesday , Thursday , Friday 0 66, Saturday 0 70, Figure 8. Hourly based AlltheWeb s response time. Response time: Minimum Average: 31.5 ms Max. average: ms Average: ms Figure 9. Response Time of AliWeb. of week for all days has been monitor against each going hour from May12, 2010 to June 7, 2010 as shown in Table 9. According to the results of the table, Tuesday has highest response time, while Thursday has least response time for AlltheWeb search engine. Hourly based average response time of AliWeb The average response time against each going hour of all 2:00 PM was found highest and lowest response time was found at 10:00 PM which means AliWeb usages is on peak at 10:00 PM in the whole world. Average response time of AliWeb against days of the week The average response time of AliWeb against the day of week for all days has been monitor against each going

10 Shoukat and Iftihkar 2573 Figure 10. Hourly based response time of AliWeb. Table 9. Response time against days of the week for AlltheWeb. Day of the week Minimum value in ms Maximum value in ms Hourly average in ms Sunday 340 8, Monday 359 7, Tuesday , Wednesday , Thursday 357 8, Friday 358 7, Saturday 359 8, Table 10. Response time of AliWeb against the days of the week. Day of the week Minimum value in ms Maximum value in ms Hourly average in ms Sunday 15 33, Monday 0 35, Tuesday 15 35, Wednesday 15 34, Thursday 0 38, Friday 15 58, Saturday 15 37, hour from May 12, 2010 to June 7, 2010 as shown in a Table 10. The results of the table show that Tuesday has highest response time, while Wednesday has least response time for AliWeb search engine. Average page download time results in seconds The graphical representation of Table 11 is shown in a Figure 11 which clearly shows that main page down load time of Altavista and AlltheWeb is same and superior to the AOL, Ask and Aliweb. Availability of search engines The availability of any search engines, depends upon the AOL, Ask and Aliweb their server s up time, down time, mean time between failures (MTBF) and mean time to repair (MTTR) as shown in Table 12. The results of the table claim that up time percentages of all search engines are almost same but down time, MTBF and MTTR has

11 2574 Sci. Res. Essays Table 11. Average page download time results. Day AltaVista (s) Ask (s) AOL (s) AliWeb (s) AlltheWeb (s) 15 May May May May May May June June June June October October November Average page loading time (s) Figure 11. Avgerage download time of main page. Table 12. Down time report from May 12 to June 6, Factor AltaVista Ask AOL AliWeb AlltheWeb Up time (%) Total down time (%) 32 min 38 s (0.09) 1 h 44 min 19 s (0.29) 2 h 47 min 55 s (0.46) min 34 s (0.09) MTTR 16 min 19 s 34 min 46 s 13 min 59 s 0.0 s 16 min 47 s MTBF 300 h 52 min 17 s 200 h 21 min 37 s 49 h 59 min 5 s 0.0 s 301 h 6 min 26 s considerable variations. Critical health status The critical or bad health status of all reported search engines is summarized in a Table 13. Hence, the results of the Table report that Aliweb s health remains power full and Asl s health is critical than Aliweb but better than Altavista, AlltheWeb and AOL. DISCUSSION AND ANALYSIS We found on which day of week and hour of day among 24 h the usage of which crawler is at the peak or least,

12 Shoukat and Iftihkar 2575 Table 13. Health status from May 12 to June 6, Search engine Health severity percentile based on up and down time (%) Altavista Ask AOL AliWeb AlltheWeb Critical heath percentile based on health severity (%) Table 14. Result s comparison. Performance metrics Altavista Ask AOL Aliweb AlltheWeb Response time (Average) (s) Highest response day of week Tuesday Monday Monday Tuesday Tuesday Least response day of the week Friday Thursday Friday Wednesday Thursday Highest response hour (PM) 3:00 6:00 3:00 2:00 3:00 Least response hour (AM) 6:00 6:00 6:00 10:00 6:00 Main page download time (s) UP time (%) Down time (%) Mean time between failure (Average) 16 min 19 s 34 min 46 s 14 min 0.0 s 16 min 47 s Mean time to repair (Average) 300 h 52 min 17 s 200 h 21 min 37 s 49 h 59 min 5 s 0.0 s 301 h 6 min 26 s Critical or bad health status (%) Reliability Medium Average Low Average Medium which indicates the load ratio for respective day and hour. From seven days of week, Ask and AOL have proved good in response time on Monday but Altavista, Aliweb, AlltheWeb possess good response on Tuesday averagely which means they bear low load on these days. Furthermore, within 24 h of a day, Altavista, Ask, AOL and AlltheWeb contain least response at 6.00 AM which means more at these respective hours; while Altavista, AOL and AlltheWeb contain highest response at 3:00 PM which means more load at these hours. Finally, we analyzed the results as summarized in Table 14. However, the Figures (1, 3, 5, 7 and 9) represent the minimum, maximum and average ratings of response time against the selected web crawlers (Altavista, Ask, AOL, AlltheWeb and Aliweb) respectively. Conclusion Optimal performance and efficiency is reliant on response time, download time, server up time, server down time, mean time between failure, mean time to repair and the severity of critical health status. The experimental result s comparison (Table 14 and Figure 13) of these study shows that Ask web crawler possesses good response within (2.01 s) and after that Altavista has (2.34 s) response time penalty which is superior to AOL, AlltheWeb and Aliweb. Moreover, AlltheWeb is on 3rd position with (2.42 s) response time penalty and AOL search engine is proved to be worst in early responding with response time (4.0 s). According to main page download time Altavista and AlltheWeb is equal in ranking with download time penalty of (0.040 s) followed by AOL with (0.24 s) main page downloading penalty as shown in Figure 12. Up time of all reported search engines seems to be almost same but in case of down time Aliweb is at first position with (0.00%) down time but Altavista and AlltheWeb is at 2nd position with same down time (0.09%) followed by Ask with (0.29%) down time as shown in Figure 13. According to MTBF once again Aliweb is at 1st position with no failure and AOL is at 2nd position with (14 min)

13 2576 Sci. Res. Essays Figure 12. Up and down time. Time (s) Percentage Figure 14. Health status and reliability. Avg. Response Time (s) Main page Junior Time (s) Figure 13. Response and page download time. MTBF penalty but Altavista and AlltheWeb are at 3rd position with same penalty of (16 min). According to MTTR AliWeb is at 1st position and AOL is better than the other ones followed by Ask but again the Altavista and AlltheWeb has close equal competition for 3rd position in this regards as discussed in Table 14 and graphically shown in Figure 15. The reliability of Ask and Aliweb is average and better than the others; while the reliability of Altavista and AlltheWeb is medium but AOL has Low reliability. According to critical or bad health status, Aliweb is better than the others with health severity of (11.64%) and Ask is at 2nd position withhealth severity of (23.70%) followed by close competition of Altavista and Aliweb but AOL contains sever health status with (52%) critical health penalty as represented in Figure 14. In the light of all performance metrics averagely, there Figure 15. MTBF and MTTR. is a close competition among Altavista, Ask and AlltheWeb. According to response time, health severity, MTT and reliability, Ask is better than Altavista and Alltheweb but according to main page download time, down time and MTBF Altavista and AlltheWeb is same in ranking mutually and better than Ask search engine.

14 Shoukat and Iftihkar 2577 ACKNOWLEDGEMENT We appreciate the Research Center of College of Computer and Information Sciences for their generous support in this work. We are really grateful to them in this regard. REFERENCES Baeza-Yates R, Ribeiro-Neto B (1999). Modern Information Retrieval. Addison-Wesley Publisher. Bar-Ilan J (1998). Search Engine Results over Time-A Case Study on Search Engine Stability. Int. J. Scientomet., Inform. Bibliomet. Cybermetrics. Issues Contents., 2(3) Bar-Ilan J (2005). Comparing rankings of search results on the Web. Inform. Process. Manage., 41(2005): Chakrabarti S (2003). Book-Mining the Web: Analysis of Hypertext and Semi Structured Data. ISBN: , Elsevier Publisher. Chau M, Chen H, Qin J, Zhou Y, Qin Y, Sung WK, McDonald D (2002). Comparison of Two Approaches to Building a Vertical Search Tool: A Case Study in the Nanotechnology Domain. In Proc. JCDL 02, July ACM /02/0007. Cherkasova C, Fu Y, Tang W, Vahdat A (2003). Measuring End-to-End Internet Service Performance. In J. ACM Trans. On Inter. Tech., 3(4): Chu H, Rosenthal M (1996). Search Engines for the World Web Web: A Comparative study and Evaluation Methodology. ASIS 1996 Annual Conf. in Proc. October Das A, Nandy S (2010). Hybrid Focused Crawler - A Fast Retrieval Of Topic Related Web Resource For Domain Specific Searching. Int. J. Inf. Tech. Knowl. Manage., 2(2): Dasdan A, Xinh HX (2009). User-Centric Content freshness Metrics for Search Engines. In WWW 2009, April 20-24, 2009, Madrid, Spain. ACM /09/04. Dujmović J, Bai H (2006). Evaluation and Comparison of Search Engines Using the LSP Method. ComSIS, 3(2): UDC Gulli A, Signorini A (2005). The indexable web is more than 11.5 billion pages. In Proc. of the World Wide Web 2005 Conference, May 10-14, Chiba, Japan. Gupta S, Sharma DL (2010). Performance Analysis of Internal vs. External Security Mechanism in Web Applications. Int. J. Adv. Netw. Appl., 01(05): Hawking D (2006). Web Search Engines. Comput., 39(6): Part 1 and 39(8): Part 2. Horák J, Ardielli J, Horáková B (2009). Testing of Web Map Services. Int. J. Spat. Data Infra. Res. Special Issue GSDI-11. Jones SK, Willett P (1997). Book-Readings in Information Retrieval. Morgan Kaufmann Series in Multimedia Information and Systems. ISBN: , Elsevier Publisher. McCown F, Nelson ML (2007). Agreeing to Disagree: Search Engines and Their Public Interfaces. In Proc. ACM, JCDL 07, June 17 22, 2007, Vancouver, British Columbia, Canada. Morris MR, Teevan J, Panovich K (2010), A Comparison of Information Seeking Using Search Engines and Social. Murugesh V, Onyango D, Murugesh S (2010). Exploring Google search engine functionalities and Google search capabilities, in proc. Inter. Resch Symp. in Service Manage., pp Rajput S, Vadivel S, Shetty S (2010). Design and Security Analysis of web application based and web services based Patient Management System (PMS). Int. J. Comput. Sci. Netw. Sec., 10(3): Rangaswamy A, Giles CL, Seres S (2009). A Strategic perspective on Search Engines: Thought Candies for Practitioners and Researchers. in J. Interac. Mark., 23 (2009): Elsevier. Sherman C (2002). Teoma vs. Google, Round Two, cited at Spink A, Jansen BJ (2006). Overlap among major web search engines, Published in Inter. Res. 16(4): Emerald Group Publishing Limited DOI / Vail C (2005). Stress, Load, Volume, Performance, Benchmark and Base Line Testing Tool Evaluation and Comparison. Cited at http//: Yossef ZB, Gurevich M (2007). Efficient Search Engine Measurements, in proc. of WWW 2007, May 8-12, 2007, Banff, Alberta, Canada. ACM /07/0005.