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Journal articles on the topic 'Web Caching'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Srinath, Harsha, and Shiva Shankar Ramanna. "Web caching." Resonance 7, no. 7 (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 (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 (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 (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 r

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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 (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 involve

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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 (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

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Dr., H. B. Patelpaik. "Machine Learning-Based Optimization of Web Caching: A Support Vector Machine Model." International Journal of Advance and Applied Research S6, no. 18 (2025): 282–88. https://doi.org/10.5281/zenodo.15259563.

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<em>In the era of information technology, the Internet serves as a critical medium for accessing information globally. The World Wide Web (WWW) facilitates a diverse range of Internet-based services, including e-commerce, online banking, entertainment, education, and e-governance. However, the exponential growth in web applications has led to a substantial increase in network traffic, causing congestion and elevating server loads. This, in turn, results in higher response times, thereby negatively impacting user experience. Web caching has emerged as an effective solution to mitigate latency i

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8

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 (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

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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 (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 (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 (2002): 353–70. http://dx.doi.org/10.1007/s00453-001-0123-6.

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13

V., Raghunatha Reddy. "WEB PROXY CACHE REPLACEMENT POLICIES USING NAÏVE BAYES (NB) MACHINE LEARNING TECHNIQUE FOR ENHANCED PERFORMANCE OF WEB PROXY." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 8, no. 5 (2019): 229–39. https://doi.org/10.5281/zenodo.7027357.

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Web cache is a mechanism for the temporary storage (caching) of web documents, such as HTML pages and images, to reduce bandwidth usage, server load, and perceived lag. A web cache stores the copies of documents passing through it and any subsequent requests may be satisfied from the cache if certain conditions are met. In this paper, Naïve Bayes (NB) a machine learning technique has been used to increase the performance of traditional Web proxy caching policies such as SIZE, and Hybrid. Naïve Bayes (NB) is used and integrated with traditional Web proxy caching techniques to form bet

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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 (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

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15

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 c

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16

Qiang Yang and H. H. Zhang. "Web-log mining for predictive web caching." IEEE Transactions on Knowledge and Data Engineering 15, no. 4 (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 (2015): 111–12. http://dx.doi.org/10.1145/2829988.2790032.

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18

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 (1998): 2169–77. http://dx.doi.org/10.1016/s0169-7552(98)00246-3.

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19

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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20

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 (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-aw

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21

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 (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 i

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22

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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23

Abhishek, Rastogi, Vats Shashank, Pundir Shivam, and Singh Ramender. "Web Browsing with Edge Computing." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 2 (2021): 97–103. https://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 phones This research focuses on two strategies based on personalised edge computing: edge aided caching and edge aided reprioritizing. Edge-assisted caching decreases the t

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24

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

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25

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

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26

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

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27

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

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28

Karger, David, Alex Sherman, Andy Berkheimer, et al. "Web caching with consistent hashing." Computer Networks 31, no. 11-16 (1999): 1203–13. http://dx.doi.org/10.1016/s1389-1286(99)00055-9.

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29

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

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30

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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31

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 intersect

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Privalov, Maksim Vladimirovich, and Mariya Valerevna Stupina. "Improving web-oriented information systems efficiency using Redis caching mechanisms." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 3 (2024): 1667. http://dx.doi.org/10.11591/ijeecs.v33.i3.pp1667-1675.

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The responsiveness of a web application with minimum latency time and maximum web pages loading speed is determined by its overall performance. When dealing with a large number of users and amount of data, the performance of web applications is significantly affected by ways of data processing, storage and access. This paper identifies the significance of data caching process to speed up access to relational database. The study examines approaches to improve the performance of web applications through the joint use of MySQL relational database management system (DBMS) and Redis NoSQL DBMS. The

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Privalov, Maksim Vladimirovich, and Mariya Valerevna Stupina. "Improving web-oriented information systems efficiency using Redis caching mechanisms." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 3 (2024): 1667–75. https://doi.org/10.11591/ijeecs.v33.i3.pp1667-1675.

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The responsiveness of a web application with minimum latency time and maximum web pages loading speed is determined by its overall performance. When dealing with a large number of users and amount of data, the performance of web applications is significantly affected by ways of data processing, storage and access. This paper identifies the significance of data caching process to speed up access to relational database. The study examines approaches to improve the performance of web applications through the joint use of MySQL relational database management system (DBMS) and Redis NoSQL DBMS. The

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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 (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

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35

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 (2004): 113–27. http://dx.doi.org/10.1007/bf02944789.

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37

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 (2015): 41–45. http://dx.doi.org/10.5120/ijca2015906656.

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38

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

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39

Sathiyamoorthi, V. "Improving the Performance of an Information Retrieval System through WEB Mining." Information Technologies and Control 14, no. 2 (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 a

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40

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 (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 propo

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41

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

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42

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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43

Li, W., W. B. Zheng, and X. H. Guan. "Application controlled caching for web servers." Enterprise Information Systems 1, no. 2 (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 (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 (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 (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 (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 (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 (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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