Web Caching Research Articles

Pengelolaan Cache pada Aplikasi Pencatatan Penjualan Menggunakan Fuzzy Page Replacement Algorithm

The challenges faced in website development are becoming increasingly diverse, particularly in delivering a responsive website that aligns with user preferences. Progressive Web App (PWA) is an advanced web technology that combines the advantages of mobile applications with the ease of access provided by browsers. With features such as offline access and responsiveness across various devices through the utilization of web caching, PWA can offer a better and more interactive user experience. This study aims to develop a sales recording application based on PWA, optimized using an algorithm with a fuzzy approach, namely the Fuzzy Page Replacement Algorithm (FPRA) in cache management. FPRA is applied to enhance cache efficiency through the clustering of pages based on recency, access frequency, and page reference levels using the Fuzzy C-Means algorithm. The research was conducted with a case study on the sales recording application for a fried chicken business, employing the Rapid Application Development (RAD) method for the design and construction of the application. The results indicate that FPRA successfully reduced page load time significantly, achieving up to 37% faster performance based on the average results of five tested scenarios. The implementation of FPRA in the service worker also increased the average performance score of the application by 15 points, from 56 to 71, as evaluated using the Lighthouse testing tool. Thus, the utilization of caching and the application of FPRA in cache management have been proven to enhance application performance.

Improvement of Spatial Data Service’s Performance with Access Control for Business System by using Web Caching

Improvement of Spatial Data Service’s Performance with Access Control for Business System by using Web Caching

Web Caching Hybrid Algorithm by Semantic Similarity

Recently, most companies have been conducting their business through the cloud network, so increasing the speed of data access via the Internet has become very important. Therefore, the importance of cache algorithms lies in increasing the speed of data access. As we know, there are cache substitution algorithms that work well with the cache when applied to the processor cache, but they hardly work when applied to caching for web purposes. The reason for this discrepancy is that it is not intended to increase the complexity of this type of storage. Considering the challenges of cache usage in terms of the large discrepancy in file size and the heterogeneous model of user access to data in a web environment, especially with pages with dynamic content, there is a real need to develop 'web cache' algorithms. In this paper, a hybrid algorithm for web caching using semantic similarity is developed. The GDFS algorithm was developed using NGD (Normalized Google Distance) to determine the semantic similarity between cache objects, which resulted in better performance in comparison to other algorithms. The results showed that the web cache hybrid algorithm using semantic similarity increased the hit rate compared to the basic algorithms by up to 80.10%. The proposed hybrid algorithm was able to overcome the problem of the low byte hit rate in the GDFS algorithm. The improvement in the byte hit rate reached 65%. This indicates an increase in the byte hit rate. The results showed that the web cache hybrid algorithm using semantic similarity reduced the page load time using distance measured from Google compared to the page load time using other algorithms that do not use semantic similarity and do not use cache. The results showed that the web cache hybrid algorithm using semantic similarity reduced the page load time from 4.17 seconds using GDFS-Line to 2.16 seconds using GDFS-NGD.

An overview of analysis methods and evaluation results for caching strategies

We survey analytical methods and evaluation results for the performance assessment of caching strategies. Knapsack solutions are derived, which provide static caching bounds for independent requests and general bounds for dynamic caching under arbitrary request pattern. We summarize Markov and time-to-live-based solutions, which assume specific stochastic processes for capturing web request streams and timing. We compare the performance of caching strategies with different knowledge about the properties of data objects regarding a broad set of caching demands. The efficiency of web caching must regard benefits for network wide traffic load, energy consumption and quality-of-service aspects in a tradeoff with costs for updating and storage overheads.

Coloring Embedder: Towards Multi-Set Membership Queries in Web Cache Sharing

Multi-set membership queries are fundamental operations in data science. In this paper, we propose a new data structure for multi-set membership queries, named coloring embedder, which is fast, accurate, and memory efficient. The idea of coloring embedder is to first map elements to a high-dimensional space, which nearly eliminates hashing collisions, and then use a dimensional reduction representation, similar to coloring a graph, to save memory. Theoretical proofs and experimental results show that the coloring embedder is effective in solving the problem of multi-set membership queries. We also find that web cache sharing is one of the typical application scenarios of the multi-set membership queries and current methods based on Bloom filters always send redundant queries. We apply coloring embedder to web cache sharing by arranging our data structure on the on-chip and off-chip memory and designing query, insertion and deletion operations for this scenario. The experimental results show that compared with the present method, our method can reduce the queries sent by proxies while reaching equal hit rate with the same size of on-chip memory. The source code of coloring embedder has been released on Github.

Analisis Forensik Aplikasi Michat Menggunakan Metode Digital Forensics Research Workshop

The development of information technology has had various positive and negative effects. The positive impact that information technology can have is to make it easier for people to communicate with others in the world, and the negative impact is that society is out of control when using its applications. It is an attitude that causes various crimes in the world caused by cyberspace (cybercrime) One of the most widely used instant messaging applications is Michat. The MiChat app causes cybercrime, pornography, online gambling, fraud, cyberbullying and drug trafficking. Evidence research is conducted using one of the frameworks of the digital forensic research workshop. In this framework, forensic identification, preservation, collection, investigation, analysis, and presentation phases are designed to find evidence of digital crime. The forensic tools used to collect evidence are mobility forensic express pro, a DB browser for SQLite, and oxygen forensic detective. Results are presented in the form of reports and evidence, and text chat files, contacts, images, audio, video, and web caches are generated. Forensic tools have a 100% success rate in finding evidence. Comparing the functions of the three forensic tools, the mobility forensic express pro has a processing rate of 66.7%, DB browser for SQLite has 33.3%, and oxygen forensic detective has 83.3%. Digital evidence can be used as corroborating evidence in a trial

Awrapper algorithm improve data transfer and synchornization performance of RSYNC

Data transfer involving large files between two geographically distributed distant points and the problem of synchronization in a distributed environment still remain as challenging tasks. The synchronization problem exists in several data transfer applications such as web caching network, data mirroring on the web, network storage, searching engine on the web, and some online data mining systems. In this paper, a wrapper algorithm is proposed to improve the performance of the well-known RSYNC algorithm for data transfer and to improve the synchronization of deep hierarchical folders on a wide area network. The proposed algorithm can be used not only for RSYNC but also for other applications involving data transfer and synchronization. The experimental results show that the proposed framework and techniques achieve significant improvements over RSYNC with regard to data transfer speed and synchronization time.

Development of Web Caching Replacement in Internet Service Based on GDSF

This paper presents a policy to replace the cached web content named GDSF-EXT based on GDSF by adding an extensible cache located in the network device. In processing, these web contents will be retrieved instead of having to search in other devices on the same network layer or at a higher network layer. That helps to reduce the response time of the user's request. The proposed algorithm is compared to GDSF original to evaluate the performance of the network

IMPLEMENTASI TEKNOLOGI ASYNCHRONOUS DENGAN MENGGUNAKAN SQUID UNTUK MENYIMPAN CACHE WEBSITE

Information technology, especially the internet, is currently growing very rapidly, due to the increasing number of people who disseminate information through the internet. The development of the number of users of Internet information technology is currently not followed by the addition of appropriate bandwidth, so problems often arise related to the speed of access to get internet services. An easy way to save bandwidth and force authentication on information traffic is to use squid. The use of Squid can be used to increase the need to speed up information retrieval. By using the Squid application, the router can be used as a proxy server for internet web cache. At the time of installing Squid without a proxy, testing was carried out on the https://www.kompas.com url and the results of the first load on a website resulted in a load time of 36 seconds, there was no difference in bandwidth usage and time whether using a proxy server or not, but the second page load on the same site with a faster load time of 30 seconds will save bandwidth. Then the installation of Squid using a proxy was carried out, testing was carried out on the https://www.kompas.com url and the results of the first load on a website resulted in a load time of 34 seconds, there was no difference in bandwidth usage and time, whether using a proxy server or not, but on the second page load on the same site with a faster load time of 16 seconds, it will save bandwidth and be faster by using squid compared to not using squid.

A Sustainable Method for Publishing Interoperable Open Data on the Web

Smart cities need (sensor) data for better decision-making. However, while there are vast amounts of data available about and from cities, an intermediary is needed that connects and interprets (sensor) data on a Web-scale. Today, governments in Europe are struggling to publish open data in a sustainable, predictable and cost-effective way. Our research question considers what methods for publishing Linked Open Data time series, in particular air quality data, are suitable in a sustainable and cost-effective way. Furthermore, we demonstrate the cross-domain applicability of our data publishing approach through a different use case on railway infrastructure—Linked Open Data. Based on scenarios co-created with various governmental stakeholders, we researched methods to promote data interoperability, scalability and flexibility. The results show that applying a Linked Data Fragments-based approach on public endpoints for air quality and railway infrastructure data, lowers the cost of publishing and increases availability due to better Web caching strategies.

Optimal chunk caching in network coding-based qualitative communication

Network processing in the current Internet is at the entirety of the data packet, which is problematic when encountering network congestion. The newly proposed Internet service named Qualitative Communication changes the network processing paradigm to an even finer granularity, namely chunk level, which obsoletes many existing networking policies and schemes, especially the caching algorithms and cache replacement policies that have been extensively explored in Web Caching, Content Delivery Networks (CDN) or Information-Centric Networks (ICN). This paper outlines all the new factors that are brought by random linear network coding-based Qualitative Communication and proves the importance and necessity of considering them. A novel metric is proposed by taking these new factors into consideration. An optimization problem is formulated to maximize the metric value of all retained chunks in the local storage of network nodes under the constraint of storage limit. A cache replacement scheme that obtains the optimal result in a recursive manner is proposed correspondingly. With the help of the introduced intelligent cache replacement algorithm, the performance evaluations show remarkably reduced end-to-end latency compared to the existing schemes in various network scenarios.

An Improved Web Caching System With Locally Normalized User Intervals

Caching is one of the most promising areas in the field of future internet architecture like Information-centric Networking, Software Defined Networking, and IoT. In Web caching, most of the web content is readily available across the network, even if the webserver is not reachable. Several existing traditional caching methods and cache replacement strategies are evaluated based on the metrics like hit ratio and byte hit Ratio. However, these metrics have not been improved over the period because of the traditional caching policies. So, in this paper, we have used an intelligent function like locally normalized intervals of page visit, website duration, users’ interest between user groups is proposed. These intervals are combined with multiple distance metrics like Manhattan, squared Euclidean, and 3-,4-,5-norm Minkowski. In order to obtain significant common user navigation patterns, the clustering relation between the users using different intervals and distances is thoroughly analyzed. These patterns are successfully coupled with greedy web cache replacement strategies to improve the efficiency of the proposed web cache system. Particularly for improving the caching metrics more, we used an AI-based intelligent approach like Random Forest classifier to boost the prefetch buffer performance and achieves the maximum hit rate of 0.89, 0.90, and byte hit rate of 0.87, 0.89 for Greedy Dual Size Frequency and Weighted Greedy Dual Size Frequency algorithms, respectively. Our experiments show good hit/byte hit rates than the frequently used algorithms like least recently used and least frequently used.

Information‐Centric Networking Cache Placement Method Based on Cache Node Status and Location

Information‐Centric Networking with caching is a very promising future network architecture. The research on its cache deployment strategy is divided into three categories, namely, noncooperative cache, explicit collaboration cache, and implicit collaboration cache. Noncooperative caching can cause problems such as high content repetition rate in the web cache space. Explicit collaboration caching generally reflects the best caching effect but requires a lot of communication to satisfy the exchange of cache node information and depends on the controller to perform the calculation. On this basis, implicit cooperative caching can reduce the information exchange and calculation between cache nodes while maintaining a good caching effect. Therefore, this paper proposes an on‐path implicit cooperative cache deployment method based on the dynamic LRU‐K cache replacement strategy. This method evaluates the cache nodes based on their network location and state and selects the node with the best state value on the transmission path for caching. Each request will only select one or two nodes for caching on the request path to reduce the redundancy of the data. Simulation experiments show that the cache deployment method based on the state and location of the cache node can improve the hit rate and reduce the average request length.

Caching strategy for Web application – a systematic literature review

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.

An Intelligent Web Caching System for Improving the Performance of a Web-Based Information Retrieval System

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.

Stable learned bloom filters for data streams

Bloom filter and its variants are elegant space-efficient probabilistic data structures for approximate set membership queries. It has been recently shown that the space cost of Bloom filters can be significantly reduced via a combination with pre-trained machine learning models, named Learned Bloom filters (LBF). LBF eases the space requirement of a Bloom filter by undertaking part of the queries using a classifier. However, current LBF structures generally target a static member set. Their performances would inevitably decay when there is a member update on the set, while this update requirement is not uncommon for real-world data streaming applications such as duplicate item detection, malicious URL checking, and web caching. To adapt LBF to data streams, we propose the Stable Learned Bloom Filters (SLBF) which addresses the performance decay issue on intensive insertion workloads by combining classifier with updatable backup filters. Specifically, we propose two SLBF structures, Single SLBF (s-SLBF) and Grouping SLBF (g-SLBF). The theoretical analysis on these two structures shows that the expected false positive rate (FPR) of SLBF is asymptotically a constant over the insertion of new members. Extensive experiments on real-world datasets show that SLBF introduces a similar level of false negative rate (FNR) but yields a better FPR/storage trade-off compared with the state-of-the-art (non-learned) Bloom filters optimized on data streams.

A Review of Probabilistic Techniques Used for Web browsers’ Caching

Cache memory plays a central role in improving the performance of web servers, especially for big data transmission, which response time is constrained. It is necessary to use an effective method, such as web cache. Browsers' cache has a significant role according to less bandwidth use, response time and traffic load as well as beneficial if the internet connection is slow. Due to the space limitations, modern browsers companies attempt to use a method to store a great number of web objects and to advance the effectiveness of web browsers. Many scientists have been working to discover and recommend various techniques for this purpose. This study consequently reviews the recent likelihood probabilistic methods, to figure out how browsers store web objects in their caches, and which methods are used to load more speedily and to store a great number of web objects. The comparison between numerous browsers performed to pick and recommend the utmost one for usage. The result has shown that each browser using RI (Ratio Improvement) has powerful performance; to be discussed later. It has proposed using Google Chrome browser because web objects are placed in its cache through the RI technique that correlated with browsers' effectiveness.

Review of Probabilistic Techniques Used for Web browsers’ Caching

Cache memory plays a central role in improving the performance of web servers, especially for big data transmission, which response time is constrained. It is necessary to use an effective method, such as web cache. Browsers' cache has a significant role according to less bandwidth use, response time and traffic load as well as beneficial if the internet connection is slow. Due to the space limitations, modern browsers companies attempt to use a method to store a great number of web objects and to advance the effectiveness of web browsers. Many scientists have been working to discover and recommend various techniques for this purpose. This study consequently reviews the recent likelihood probabilistic methods, to figure out how browsers store web objects in their caches, and which methods are used to load more speedily and to store a great number of web objects. The comparison between numerous browsers performed to pick and recommend the utmost one for usage. The result has shown that each browser using RI (Ratio Improvement) has powerful performance; to be discussed later. It has proposed using Google Chrome browser because web objects are placed in its cache through the RI technique that correlated with browsers' effectiveness.

Analyzing and Optimizing the Usability of Website Access

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.

Evaluation of an Evolutionary Algorithm to Dynamically Alter Partition Sizes in Web Caching Systems

There has been an explosion in the volume of data that is being accessed from the Internet. As a result, the risk of a Web server being inundated with requests is ever-present. One approach to reducing the performance degradation that potentially comes from Web server overloading is to employ Web caching where data content is replicated in multiple locations. In this paper, we investigate the use of evolutionary algorithms to dynamically alter partition size in Web caches. We use established modeling techniques to compare the performance of our evolutionary algorithm to that found in statically-partitioned systems. Our results indicate that utilizing an evolutionary algorithm to dynamically alter partition sizes can lead to performance improvements especially in environments where the relative size of large to small pages is high.