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Journal articles on the topic 'Web Caching'

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Published: 4 June 2021
Last updated: 7 September 2023

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1

Srinath, Harsha, and Shiva Shankar Ramanna. "Web caching." Resonance 7, no. 7 (July 2002): 54–62. http://dx.doi.org/10.1007/bf02836754.

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Cáceres, Ramón, Fred Douglis, Anja Feldmann, Gideon Glass, and Michael Rabinovich. "Web proxy caching." ACM SIGMETRICS Performance Evaluation Review 26, no. 3 (December 1998): 11–15. http://dx.doi.org/10.1145/306225.306230.

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3

Berghel, Hal. "Responsible web caching." Communications of the ACM 45, no. 9 (September 2002): 15–20. http://dx.doi.org/10.1145/567498.567514.

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Sathiyamoorthi, V. "A Novel Cache Replacement Policy for Web Proxy Caching System Using Web Usage Mining." International Journal of Information Technology and Web Engineering 11, no. 2 (April 2016): 1–13. http://dx.doi.org/10.4018/ijitwe.2016040101.

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Network congestion remains one of the main barriers to the continuing success of the internet and Web based services. In this background, proxy caching is one of the most successful solutions for civilizing the performance of Web since it reduce network traffic, Web server load and improves user perceived response time. Here, the most popular Web objects that are likely to be revisited in the near future are stored in the proxy server thereby it improves the Web response time and saves network bandwidth. The main component of Web caching is it cache replacement policy. It plays a key role in replacing existing objects when there is no room for new one especially when cache is full. Moreover, the conventional replacement policies are used in Web caching environments which provide poor network performance. These policies are suitable for memory caching since it involves fixed sized objects. But, Web caching which involves objects of varying size and hence there is a need for an efficient policy that works better in Web cache environment. Moreover, most of the existing Web caching policies have considered few factors and ignored the factors that have impact on the efficiency of Web proxy caching. Hence, it is decided to propose a novel policy for Web cache environment. The proposed policy includes size, cost, frequency, ageing, time of entry into the cache and popularity of Web objects in cache removal policy. It uses the Web usage mining as a technique to improve Web caching policy. Also, empirical analyses shows that proposed policy performs better than existing policies in terms of various performance metrics such as hit rate and byte hit rate.
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Sathiyamoorthi and Murali Bhaskaran. "Novel Approaches for Integrating MART1 Clustering Based Pre-Fetching Technique with Web Caching." International Journal of Information Technology and Web Engineering 8, no. 2 (April 2013): 18–32. http://dx.doi.org/10.4018/jitwe.2013040102.

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Web caching and Web pre-fetching are two important techniques for improving the performance of Web based information retrieval system. These two techniques would complement each other, since Web caching provides temporal locality whereas Web pre-fetching provides spatial locality of Web objects. However, if the web caching and pre-fetching are integrated inefficiently, this might cause increasing the network traffic as well as the Web server load. Conventional policies are most suitable only for memory caching since it involves fixed page size. But when one deals with web caching which involves pages of different size. Hence one need an efficient algorithm that works better in web cache environment. Moreover conventional replacement policies are not suitable in clustering based pre-fetching environment since multiple objects were pre-fetched. Hence, it cannot be handled by conventional algorithms. Therefore, care must be taken while integrating web caching with web pre-fetching technique in order to overcome these limitations. In this paper, novel algorithms have been proposed for integrating web caching with clustering based pre-fetching technique. Here Modified ART1 has been used for clustering based pre-fetching technique. The proposed algorithm outperforms the traditional algorithms in terms of hit rate and number of objects to be pre-fetched. Hence saves bandwidth.
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6

Zulfa, Mulki Indana, Rudy Hartanto, and Adhistya Erna Permanasari. "Caching strategy for Web application – a systematic literature review." International Journal of Web Information Systems 16, no. 5 (October 5, 2020): 545–69. http://dx.doi.org/10.1108/ijwis-06-2020-0032.

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Purpose Internet users and Web-based applications continue to grow every day. The response time on a Web application really determines the convenience of its users. Caching Web content is one strategy that can be used to speed up response time. This strategy is divided into three main techniques, namely, Web caching, Web prefetching and application-level caching. The purpose of this paper is to put forward a literature review of caching strategy research that can be used in Web-based applications. Design/methodology/approach The methods used in this paper were as follows: determined the review method, conducted a review process, pros and cons analysis and explained conclusions. The review method is carried out by searching literature from leading journals and conferences. The first search process starts by determining keywords related to caching strategies. To limit the latest literature in accordance with current developments in website technology, search results are limited to the past 10 years, in English only and related to computer science only. Findings Note in advance that Web caching and Web prefetching are slightly overlapping techniques because they have the same goal of reducing latency on the user’s side. But actually, the two techniques are motivated by different basic mechanisms. Web caching uses the basic mechanism of cache replacement or the algorithm to change cache objects in memory when the cache capacity is full, whereas Web prefetching uses the basic mechanism of predicting cache objects that can be accessed in the future. This paper also contributes practical guidelines for choosing the appropriate caching strategy for Web-based applications. Originality/value This paper conducts a state-of-the art review of caching strategies that can be used in Web applications. Exclusively, this paper presents taxonomy, pros and cons of selected research and discusses data sets that are often used in caching strategy research. This paper also provides another contribution, namely, practical instructions for Web developers to decide the caching strategy.
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Davison, B. D. "A Web caching primer." IEEE Internet Computing 5, no. 4 (2001): 38–45. http://dx.doi.org/10.1109/4236.939449.

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Chauhan, Shobhit. "Caching in Web Applications." International Journal of Computer Trends and Technology 68, no. 8 (August 25, 2020): 14–20. http://dx.doi.org/10.14445/22312803/ijctt-v68i8p102.

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Afonso, Manuel, Alexandre Santos, and Freitas Vasco. "QoS in Web caching." Computer Networks and ISDN Systems 30, no. 22-23 (November 1998): 2093–103. http://dx.doi.org/10.1016/s0169-7552(98)00255-4.

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Kalyanasundaram, B., J. Noga, K. R. Pruhs, and G. J. Woeginger. "Caching for Web Searching." Algorithmica 33, no. 3 (January 1, 2002): 353–70. http://dx.doi.org/10.1007/s00453-001-0123-6.

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Rajendran Baskaran, Kuttuva, and Chellan Kalaiarasan. "Improved Performance by Combining Web Pre-Fetching Using Clustering with Web Caching Based on SVM Learning Method." International Journal of Computers Communications & Control 11, no. 2 (January 26, 2016): 67. http://dx.doi.org/10.15837/ijccc.2016.2.897.

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Combining Web caching and Web pre-fetching results in improving the bandwidth utilization, reducing the load on the origin server and reducing the delay incurred in accessing information. Web pre-fetching is the process of fetching the Web objects from the origin server which has more likelihood of being used in future. The fetched contents are stored in the cache. Web caching is the process of storing the popular objects ”closer” to the user so that they can be retrieved faster. In the literature many interesting works have been carried out separately for Web caching and Web pre-fetching. In this work, clustering technique is used for pre-fetching and SVM-LRU technique forWeb caching and the performance is measured in terms of Hit Ratio (HR) and Byte Hit Ratio (BHR). With the help of real data, it is demonstrated that the above approach is superior to the method of combining clustering based prefetching technique with traditional LRU page replacement method for Web caching.
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Azi, Muhammad Naufal Ammar, Bongga Arifwidodo, and Eka Wahyudi. "Analisis Performansi Web Server Saat Menangani Permintaan Client Menggunakan Metode Reserve Proxy Caching dan Varnish." Journal of Telecommunication, Electronics, and Control Engineering (JTECE) 5, no. 1 (January 31, 2023): 14–21. http://dx.doi.org/10.20895/jtece.v5i1.843.

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Web Technology Surveys peningkatan pengguna internet yang mengakses website terus meningkat setiap tahunnya terutama web server Apache dan Nginx. Hal ini dapat menyebabkan performa dari sebuah web server menjadi berat dan jika melebihi kapasitas maka bisa terjadi downtime server. Maka dari itu diperlukannya reverse proxy caching. Reverse proxy caching mampu menyeimbangkan beban pada beberapa server back-end dan menyediakan caching untuk server back-end yang lamban terutama pada web server Apache. Penelitian kali ini adalah reverse proxy caching nginx dan varnish. Pengujian performa web server dilakukan dengan mengirim 3 macam uji yaitu dengan mengirimkan beban 200 koneksi, 2.000 koneksi dan 20.000 koneksi dengan 200 Conccurency yang diukur dengan apache benchmark Tools. Berdasarkan hasil pengujian bahwa Apache web server yang telah dikonfigurasikan reverse proxy caching Nginx memberikan hasil kinerja lebih baik dari reverse proxy caching Varnish. Parameter request per second sebesar 1207 req/seconds (39,6% Lebih baik dibandingkan Varnish), Time taken for test sebesar 16,65 seconds (28,3% Lebih baik dibandingkan Varnish), Time per request sebesar 166,4 ms (28,4% Lebih baik dibandingkan Varnish), dan Transfer rate sebesar 13,15 MB/sec (38,4% Lebih baik dibandingkan Varnish)
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Qiang Yang and H. H. Zhang. "Web-log mining for predictive web caching." IEEE Transactions on Knowledge and Data Engineering 15, no. 4 (July 2003): 1050–53. http://dx.doi.org/10.1109/tkde.2003.1209022.

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Raza, Ali, Yasir Zaki, Thomas Pötsch, Jay Chen, and Lakshmi Subramanian. "Extreme Web Caching for Faster Web Browsing." ACM SIGCOMM Computer Communication Review 45, no. 4 (September 22, 2015): 111–12. http://dx.doi.org/10.1145/2829988.2790032.

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15

Michel, Scott, Khoi Nguyen, Adam Rosenstein, Lixia Zhang, Sally Floyd, and Van Jacobson. "Adaptive web caching: towards a new global caching architecture." Computer Networks and ISDN Systems 30, no. 22-23 (November 1998): 2169–77. http://dx.doi.org/10.1016/s0169-7552(98)00246-3.

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Rodriguez, P., C. Spanner, and E. W. Biersack. "Analysis of Web caching architectures: hierarchical and distributed caching." IEEE/ACM Transactions on Networking 9, no. 4 (2001): 404–18. http://dx.doi.org/10.1109/90.944339.

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Wang, James Z., Zhidian Du, and Pradip K. Srimani. "Cooperative Proxy Caching for Wireless Base Stations." Mobile Information Systems 3, no. 1 (2007): 1–18. http://dx.doi.org/10.1155/2007/371572.

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This paper proposes a mobile cache model to facilitate the cooperative proxy caching in wireless base stations. This mobile cache model uses a network cache line to record the caching state information about a web document for effective data search and cache space management. Based on the proposed mobile cache model, a P2P cooperative proxy caching scheme is proposed to use a self-configured and self-managed virtual proxy graph (VPG), independent of the underlying wireless network structure and adaptive to the network and geographic environment changes, to achieve efficient data search, data cache and date replication. Based on demand, the aggregate effect of data caching, searching and replicating actions by individual proxy servers automatically migrates the cached web documents closer to the interested clients. In addition, a cache line migration (CLM) strategy is proposed to flow and replicate the heads of network cache lines of web documents associated with a moving mobile host to the new base station during the mobile host handoff. These replicated cache line heads provide direct links to the cached web documents accessed by the moving mobile hosts in the previous base station, thus improving the mobile web caching performance. Performance studies have shown that the proposed P2P cooperative proxy caching schemes significantly outperform existing caching schemes.
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Rastogi, Abhishek, Shashank Vats, Shivam Pundir, and Ramender Singh. "Web Browsing with Edge Computing." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 2 (July 30, 2021): 97–103. http://dx.doi.org/10.35940/ijrte.b6187.0710221.

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Webpages have become increasingly complex in recent years, with longer loading times to match. This paper uses tailored edge computing to address this issue. As is customary, A grip server interacts with cloud web servers in edge computing. In A footing server, on the other hand, is a personalised edge computing system. referred to as a foothold The Server in the Middle (ESM) collaborates with other servers. users' cell phonesThis research focuses on two strategies based on personalised edge computing: edge aided caching and edge aided reprioritizing. Edge-assisted caching decreases the time it takes for a page to load. Because an ESM saves the cached data on mobile devices, So far, we've got components. Edge helps in the reprioritization of forces on the internet. browser to show visual components earlier and lowers the amount of white space Time spent in front of a screen.In addition, the ESM uses HTTP/2 rather than HTTP/1.1. This decreases the number of interactions between a mobile device and, as a result, the ESM, allowing advanced functionalities to be used. such as priority and server push Edge-assisted caching has been implemented. built in a high-end PC for Google's web browser Chrome for Android is a mobile web browser. Edge aided in an experiment, according to the results. The time it took for a popular website to load was cut in half because to caching. 59 percent in a network that is extremely congested. Another experiment found that edge-assisted reprioritization cut the white screen time of a webpage with a lot of photo photos by 21%. edge computing, reprioritization, mobile device, index terms browsing the web, caching
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19

Sathiyamoorthi V., Suresh P., Jayapandian N., Kanmani P., Deva Priya M., and Sengathir Janakiraman. "An Intelligent Web Caching System for Improving the Performance of a Web-Based Information Retrieval System." International Journal on Semantic Web and Information Systems 16, no. 4 (October 2020): 26–44. http://dx.doi.org/10.4018/ijswis.2020100102.

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With an increasing number of web users, the data traffic generated by these users generates tremendous network traffic which takes a long time to connect with the web server. The main reason is, the distance between the client making requests and the servers responding to those requests. The use of the CDN (content delivery network) is one of the strategies for minimizing latency. But, it incurs additional cost. Alternatively, web caching and preloading are the most viable approaches to this issue. It is therefore decided to introduce a novel web caching strategy called optimized popularity-aware modified least frequently used (PMLFU) policy for information retrieval based on users' past access history and their trends analysis. It helps to enhance the proxy-driven web caching system by analyzing user access requests and caching the most popular web pages driven on their preferences. Experimental results show that the proposed systems can significantly reduce the user delay in accessing the web page. The performance of the proposed system is measured using IRCACHE data sets in real time.
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German, Mihail Sergeevich, and Alexey Viktorovitch Ermakov. "Block caching of web-pages structure." Keldysh Institute Preprints, no. 240 (2018): 1–17. http://dx.doi.org/10.20948/prepr-2018-240.

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Premkumar, Vandana, and Vinil Bhandari. "Caching in Amazon Web Services." International Journal of Computer Trends and Technology 69, no. 4 (April 25, 2021): 1–5. http://dx.doi.org/10.14445/22312803/ijctt-v69i4p101.

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Zakhary, Victor, Divyakant Agrawal, and Amr El Abbadi. "Caching at the web scale." Proceedings of the VLDB Endowment 10, no. 12 (August 2017): 2002–5. http://dx.doi.org/10.14778/3137765.3137831.

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Menasce, D. A. "Scaling Web sites through caching." IEEE Internet Computing 7, no. 4 (July 2003): 86–89. http://dx.doi.org/10.1109/mic.2003.1215665.

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Xueyan Tang and S. T. Chanson. "Coordinated en-route Web caching." IEEE Transactions on Computers 51, no. 6 (June 2002): 595–607. http://dx.doi.org/10.1109/tc.2002.1009146.

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Karger, David, Alex Sherman, Andy Berkheimer, Bill Bogstad, Rizwan Dhanidina, Ken Iwamoto, Brian Kim, Luke Matkins, and Yoav Yerushalmi. "Web caching with consistent hashing." Computer Networks 31, no. 11-16 (May 1999): 1203–13. http://dx.doi.org/10.1016/s1389-1286(99)00055-9.

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Starobinski, David, and David Tse. "Probabilistic methods for web caching." Performance Evaluation 46, no. 2-3 (October 2001): 125–37. http://dx.doi.org/10.1016/s0166-5316(01)00045-1.

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Chidlovskii, Boris, and Uwe M. Borghoff. "Semantic caching of Web queries." VLDB Journal 9, no. 1 (2000): 2. http://dx.doi.org/10.1007/s007780050080.

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Ma, Hong Yuan. "Design and Implementation of a Cache System in Web Search Engines." Applied Mechanics and Materials 462-463 (November 2013): 1106–9. http://dx.doi.org/10.4028/www.scientific.net/amm.462-463.1106.

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Web search engine caches the results which is frequently queried by users. It is an effective approach to improve the efficiency of Web search engines. In this paper, we give some valuable experience in our design and implementation of a Web search engine cache system. We present there design principles: logical layer processing, event-based communication architecture and avoiding frequent data copy. We also introduce the architecture presented in practice, including connection processor, application processor, query results caching processor, inverted list caching processor and list intersection caching processor. Experiments are conducted in our cache system using a real Web search engine query log.
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Tay, T. T., and Y. Zhang. "Minimal web patch generation for incremental web caching." IEE Proceedings - Communications 152, no. 2 (2005): 185. http://dx.doi.org/10.1049/ip-com:20045043.

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Liu, Ming-Kuan, Fei-Yue Wang, and Daniel Dajun Zeng. "Web caching: A way to improve web QoS." Journal of Computer Science and Technology 19, no. 2 (March 2004): 113–27. http://dx.doi.org/10.1007/bf02944789.

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Raghunathan, A., and K. Murugesan. "Performance-Enhanced Caching Scheme for Web Clusters for Dynamic Content." International Journal of Business Data Communications and Networking 7, no. 3 (July 2011): 16–36. http://dx.doi.org/10.4018/jbdcn.2011070102.

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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.
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Nanda, Pranay, Shamsher Singh, and G. L. Saini. "A Review of Web Caching Techniques and Caching Algorithms for Effective and Improved Caching." International Journal of Computer Applications 128, no. 10 (October 15, 2015): 41–45. http://dx.doi.org/10.5120/ijca2015906656.

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Kumar, Chetan, and Sean Marston. "Accelerating the Internet in the presence of Big Data: Reducing user delays by leveraging historical user request patterns for web caching." Journal of Information Systems and Technology Management 16 (March 30, 2019): 1–10. http://dx.doi.org/10.4301/s1807-1775201916006.

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Approximately 4 billion people have access to the Internet, additionally 23 billion devices are connected as of 2018. This has allowed for a substantial growth in data collection which has allowed for Big Data to flourish. The continued increase in user, devices, and Big Data usage has created a significant intensification in Internet traffic. This in turn has the potential to increase user delays when accessing data on the Internet. There are a number of ways to help reduce user latency, web caching is able to reduce web user delays in addition to reducing network traffic and the load on web servers. In this study we propose a proxy level web caching mechanism leveraging historical web patterns to help reduce user latency and accelerate the Internet. In addition we survey the state of the art of other caching approaches. Our investigation shows that using historical patterns as part of a proxy caching mechanisms in large scale networks can significantly shorten the latency for users in this era of Big Data
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Sathiyamoorthi, V. "Improving the Performance of an Information Retrieval System through WEB Mining." Information Technologies and Control 14, no. 2 (June 1, 2016): 28–34. http://dx.doi.org/10.1515/itc-2017-0004.

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AbstractIt is generally observed throughout the world that in the last two decades, while the average speed of computers has almost doubled in a span of around eighteen months, the average speed of the network has doubled merely in a span of just eight months!. In order to improve the performance, more and more researchers are focusing their research in the field of computers and its related technologies. World Wide Web (WWW) acts as a medium for sharing of information. As a result, millions of applications run on the Internet and cause increased network traffic and put a great demand on the available network infrastructure. The slow retrieval of Web pages may reduce the user interest from accessing them. To deal with this problem Web caching and Web pre-fetching are used. This paper focuses on a methodology for improving the proxy-based Web caching system using Web mining. It integrates Web caching and Pre-fetching through an efficient clustering based pre-fetching technique.
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., Ranju Khemka. "HYBRID WEB CACHING FRAMEWORK FOR REDUCTION OF WEB LATENCY." International Journal of Research in Engineering and Technology 03, no. 04 (April 25, 2014): 836–41. http://dx.doi.org/10.15623/ijret.2014.0304148.

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Jarukasemratana, Sorn, and Tsuyoshi Murata. "Web Caching Replacement Algorithm Based on Web Usage Data." New Generation Computing 31, no. 4 (October 2013): 311–29. http://dx.doi.org/10.1007/s00354-013-0404-z.

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Shin, Yong-Hyeon. "An Efficient Cooperative Web Caching Scheme." KIPS Transactions:PartC 13C, no. 6 (October 30, 2006): 785–94. http://dx.doi.org/10.3745/kipstc.2006.13c.6.785.

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Aggarwal, C., J. L. Wolf, and P. S. Yu. "Caching on the World Wide Web." IEEE Transactions on Knowledge and Data Engineering 11, no. 1 (1999): 94–107. http://dx.doi.org/10.1109/69.755618.

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Li, W., W. B. Zheng, and X. H. Guan. "Application controlled caching for web servers." Enterprise Information Systems 1, no. 2 (May 2007): 161–75. http://dx.doi.org/10.1080/17517570701243273.

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Bahn, Hyokyung, Hyunsook Lee, Sam H. Noh, Sang Lyul Min, and Kern Koh. "Replica-aware caching for Web proxies." Computer Communications 25, no. 3 (February 2002): 183–88. http://dx.doi.org/10.1016/s0140-3664(01)00365-6.

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Caughey, S. J., D. B. Ingham, and M. C. Little. "Flexible open caching for the Web." Computer Networks and ISDN Systems 29, no. 8-13 (September 1997): 1007–17. http://dx.doi.org/10.1016/s0169-7552(97)00015-9.

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Bakiras, Spiridon, Thanasis Loukopoulos, Dimitris Papadias, and Ishfaq Ahmad. "Adaptive schemes for distributed web caching." Journal of Parallel and Distributed Computing 65, no. 12 (December 2005): 1483–96. http://dx.doi.org/10.1016/j.jpdc.2005.05.020.

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Feder, Tomás, Rajeev Motwani, Rina Panigrahy, Steve Seiden, Rob van Stee, and An Zhu. "Combining request scheduling with web caching." Theoretical Computer Science 324, no. 2-3 (September 2004): 201–18. http://dx.doi.org/10.1016/j.tcs.2004.05.016.

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Pais, V. F., and V. Stancalie. "Caching web service for TICF project." Fusion Engineering and Design 83, no. 2-3 (April 2008): 425–28. http://dx.doi.org/10.1016/j.fusengdes.2007.11.008.

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Terry, Douglas D., and Venugopalan Ramasubramanian. "Caching XML Web Services for Mobility." Queue 1, no. 3 (May 2003): 70–78. http://dx.doi.org/10.1145/846057.864024.

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Kenyon, C. "The evolution of Web-caching markets." Computer 34, no. 11 (2001): 128–30. http://dx.doi.org/10.1109/2.963449.

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Markatos, Evangelos P. "Main memory caching of Web documents." Computer Networks and ISDN Systems 28, no. 7-11 (May 1996): 893–905. http://dx.doi.org/10.1016/0169-7552(96)00035-9.

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Yasin. "WINDOWS WEB PROXY CACHING SIMULATION: A TOOL FOR SIMULATING WEB PROXY CACHING UNDER WINDOWS OPERATING SYSTEMS." Journal of Computer Science 10, no. 8 (August 1, 2014): 1380–88. http://dx.doi.org/10.3844/jcssp.2014.1380.1388.

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Sathiyamoorthi V., Jayapandian N., Gnana Prakasi O. S., Kanmani P., Revathi Vaithiyanathan, and Prasanth Rao A. "Analyzing and Optimizing the Usability of Website Access." International Journal of Web Portals 12, no. 2 (July 2020): 22–40. http://dx.doi.org/10.4018/ijwp.2020070102.

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The world wide web (WWW) plays a significant role in information sharing and distribution. In web-based information access, the speed of information retrieval plays a critical role in shaping the web usability and determining the user satisfaction in accessing webpages. To deal with this problem, web caching is used. The problem with the present web caching system is that it is very hard to recognize webpages that are to be accessed and then to be cached. This is forced by the fact that there are broad categories of users and each one having their own preferences. Hence, it is decided to propose a novel approach for web access pattern generation by analyzing the web log file present in the proxy server. Further, it tries to propose a novel hybrid policy called popularity-aware modified least frequently used (PMLFU) that best suits for the current proxy-based web caching environment. It combines features such as frequency, recency, popularity, and user page count in decision-making policy. The performance of the proposed system is observed using real-time datasets, empirically using IRCACHE datasets.
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Kurko, V. S., I. S. Kolesnik, and T. M. Borovskaya. "A method of increasing the speed of loading web pages." Optoelectronic Information-Power Technologies 41, no. 1 (July 28, 2021): 13–19. http://dx.doi.org/10.31649/1681-7893-2021-41-1-13-19.

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Developed software for secure configuration of caching of dynamic content of web pages, which aims to simplify the user's process of configuring dynamic content that can be cached, reduce the risk of caching personal data, increase the percentage of cached pages containing dynamic content, reduce the load on the main server, and speed up page loading for the end user.
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