Comparison of Different Caching Techniques for High-Performance Web Map Services

The demand for digital maps on the Internet has increased considerably in the last few years. Therefore the performance of Web Mapping Services is becoming more and more important. This article introduces different caching techniques for high performance transfer of data using standardized Open Geospatial Consortium (OGC) Web Map Services (WMS). It describes and examines different caching mechanisms based on tile caching, reverse proxy caching and web application acceleration. Furthermore it demonstrates benefits, problems and how data needs to be modified for different caching techniques. The article outlines the advantages of WMS caching systems and investigates the behaviour of these systems with an increasing number of concurrent requests using benchmark tests. This includes the examination of applicability of the INSPIRE service level agreement for view services

AOP-Based Caching of Dynamic Web Content: Experience with J2EE Applications

Caching dynamic web content is an appealing approach to reduce Internet latency and server load. In aspect-oriented programming, caching is usually presented as an orthogonal aspect that could be automatically integrated to an application. A classical AOP motivating example is adding caching of static data with no underlying consistency. But what about caching dynamic data? In this paper, we explore the feasibility of aspectizing consistent caching of dynamically generated web documents. We use two J2EE web applications to validate our experiments: the TPC-W on-line bookstore and the RUBiS auction site. To the question "Can we consider consistent caching of dynamic web content as a separate aspect that could be transparently and efficiently integrated to a dynamic web application?", our conclusions are the following: (a) Just as in the classic AOP caching example having no consistency management, AOP provides a modular way to add caching having a strong consistency policy. (b) However, maintaining strong consistency on web pages results in prohibitively expensive run-time processing and, thus, any straightforward implementation in AOP is too slow. We propose an optimization that essentially eliminates all the run-time overhead in practice. (c) Furthermore, we identify in-stances where consistent web caching may not be orthogonal to J2EE applications, especially for those applications that rely on sophisticated web techniques (e.g., cookies). In summary, adding caching supporting strong consistency using AOP turned out to be an unexpected chal-lenge

Improving the latency of Python-based web applications

This paper describes the process of optimizing the latency of Python-based Web applications. The case study used to validate the optimizations is an article sharing system, which was developed in Django. Memcached, Celery and Varnish enabled the implementation of additional performance optimizations. The latency of operations was measured, before and after the application of the optimization techniques. The optimization of the application was performed at various levels, including the transfer of content across the network and the back-end services. HTTP caching, data compression and minification techniques, as well as static content replication using Content Delivery Networks, were used. Partial update of the application’s pages on the front-end and asynchronous processing techniques were applied. The database utilization was optimized by creating indexes and by taking advantage of a NoSQL solution. Memory caching strategies, with distinct granularities, were implemented to store tem plates and application objects. Furthermore, asynchronous task queues were used to perform some costly operations. All of the aforementioned techniques favorably contributed to the Web application’s latency decrease. Since Django operates on the back-end, and optimizations must be implemented at various levels, it was necessary to use other toolsFCT – Fundaçãopara a Ciência e Tecnologia within the Project Scope:UID/CEC/00319/201

Design and Implementation of a Web Usage Mining Model Based On Upgrowth and Preflxspan

Web Usage Mining (WUM) integrates the techniques of two popular research fields - Data Mining and the Internet. By analyzing the potential rules hidden in web logs, WUM helps personalize the delivery of web content and improve web design, customer satisfaction and user navigation through pre-fetching and caching. This paper introduces two prevalent data mining algorithms - FPgrowth and PrefixSpan into WUM and they are applied in a real business case. Maximum Forward Path (MFP) is also used in the web usage mining model during sequential pattern mining along with PrefixSpan so as to reduce the interference of false visit caused by browser cache and raise the accuracy of mining frequent traversal paths. Detailed analysis and application on the corresponding results are discussed

Database server workload characterization in an e-commerce environment

A typical E-commerce system that is deployed on the Internet has multiple layers that include Web users, Web servers, application servers, and a database server. As the system use and user request frequency increase, Web/application servers can be scaled up by replication. A load balancing proxy can be used to route user requests to individual machines that perform the same functionality. To address the increasing workload while avoiding replicating the database server, various dynamic caching policies have been proposed to reduce the database workload in E-commerce systems. However, the nature of the changes seen by the database server as a result of dynamic caching remains unknown. A good understanding of this change is fundamental for tuning a database server to get better performance. In this study, the TPC-W (a transactional Web E-commerce benchmark) workloads on a database server are characterized under two different dynamic caching mechanisms, which are generalized and implemented as query-result cache and table cache. The characterization focuses on response time, CPU computation, buffer pool references, disk I/O references, and workload classification. This thesis combines a variety of analysis techniques: simulation, real time measurement and data mining. The experimental results in this thesis reveal some interesting effects that the dynamic caching has on the database server workload characteristics. The main observations include: (a) dynamic cache can considerably reduce the CPU usage of the database server and the number of database page references when it is heavily loaded; (b) dynamic cache can also reduce the database reference locality, but to a smaller degree than that reported in file servers. The data classification results in this thesis show that with dynamic cache, the database server sees TPC-W profiles more like on-line transaction processing workloads

Stochastic Query Covering for Fast Approximate Document Retrieval

We design algorithms that, given a collection of documents and a distribution over user queries, return a small subset of the document collection in such a way that we can efficiently provide high-quality answers to user queries using only the selected subset. This approach has applications when space is a constraint or when the query-processing time increases significantly with the size of the collection. We study our algorithms through the lens of stochastic analysis and prove that even though they use only a small fraction of the entire collection, they can provide answers to most user queries, achieving a performance close to the optimal. To complement our theoretical findings, we experimentally show the versatility of our approach by considering two important cases in the context of Web search. In the first case, we favor the retrieval of documents that are relevant to the query, whereas in the second case we aim for document diversification. Both the theoretical and the experimental analysis provide strong evidence of the potential value of query covering in diverse application scenarios

Basis Token Consistency: A Practical Mechanism for Strong Web Cache Consistency

With web caching and cache-related services like CDNs and edge services playing an increasingly significant role in the modern internet, the problem of the weak consistency and coherence provisions in current web protocols is becoming increasingly significant and drawing the attention of the standards community [LCD01]. Toward this end, we present definitions of consistency and coherence for web-like environments, that is, distributed client-server information systems where the semantics of interactions with resource are more general than the read/write operations found in memory hierarchies and distributed file systems. We then present a brief review of proposed mechanisms which strengthen the consistency of caches in the web, focusing upon their conceptual contributions and their weaknesses in real-world practice. These insights motivate a new mechanism, which we call "Basis Token Consistency" or BTC; when implemented at the server, this mechanism allows any client (independent of the presence and conformity of any intermediaries) to maintain a self-consistent view of the server's state. This is accomplished by annotating responses with additional per-resource application information which allows client caches to recognize the obsolescence of currently cached entities and identify responses from other caches which are already stale in light of what has already been seen. The mechanism requires no deviation from the existing client-server communication model, and does not require servers to maintain any additional per-client state. We discuss how our mechanism could be integrated into a fragment-assembling Content Management System (CMS), and present a simulation-driven performance comparison between the BTC algorithm and the use of the Time-To-Live (TTL) heuristic.National Science Foundation (ANI-9986397, ANI-0095988

MADServer: An Architecture for Opportunistic Mobile Advanced Delivery

Rapid increases in cellular data traffic demand creative alternative delivery vectors for data. Despite the conceptual attractiveness of mobile data offloading, no concrete web server architectures integrate intelligent offloading in a production-ready and easily deployable manner without relying on vast infrastructural changes to carriers’ networks. Delay-tolerant networking technology offers the means to do just this. We introduce MADServer, a novel DTN-based architecture for mobile data offloading that splits web con- tent among multiple independent delivery vectors based on user and data context. It enables intelligent data offload- ing, caching, and querying solutions which can be incorporated in a manner that still satisfies user expectations for timely delivery. At the same time, it allows for users who have poor or expensive connections to the cellular network to leverage multi-hop opportunistic routing to send and receive data. We also present a preliminary implementation of MADServer and provide real-world performance evaluations