Junho Shim

Bio: Junho Shim is an academic researcher from Sookmyung Women's University. The author has contributed to research in topics: Cache & Ontology (information science). The author has an hindex of 17, co-authored 69 publications receiving 1146 citations. Previous affiliations of Junho Shim include NEC & Seoul National University.

Proxy cache algorithms: design, implementation, and performance

Abstract: Caching at proxy servers is one of the ways to reduce the response time perceived by World Wide Web users. Cache replacement algorithms play a central role in the response time reduction by selecting a subset of documents for caching, so that a given performance metric is maximized. At the same time, the cache must take extra steps to guarantee some form of consistency of the cached documents. Cache consistency algorithms enforce appropriate guarantees about the staleness of the cached documents. We describe a unified cache maintenance algorithm, LNC-R-WS-U, which integrates both cache replacement and consistency algorithms. The LNC-R-WS-U algorithm evicts documents from the cache based on the delay to fetch each document into the cache. Consequently, the documents that took a long time to fetch are preferentially kept in the cache. The LNC-R-W3-U algorithm also considers in the eviction consideration the validation rate of each document, as provided by the cache consistency component of LNC-R-WS-U. Consequently, documents that are infrequently updated and thus seldom require validations are preferentially retained in the cache. We describe the implementation of LNC-R-W3-U and its integration with the Apache 1.2.6 code base. Finally, we present a trace-driven experimental study of LNC-R-W3-U performance and its comparison with other previously published algorithms for cache maintenance.

WATCHMAN: A Data Warehouse Intelligent Cache Manager

Abstract: Data warehouses store large volumes of data which are used frequently by decision support applications. Such applications involve complex queries. Query performance in such an environment is critical because decision support applications often require interactive query response time. Because data warehouses are updated infrequently, it becomes possible to improve query performance by caching sets retrieved by queries in addition to query execution plans. In this paper we report on the design of an intelligent cache manager for sets retrieved by queries called WATCHMAN, which is particularly well suited for data warehousing environment. Our cache manager employs two novel, complementary algorithms for cache replacement and for cache admission. WATCHMAN aims at minimizing query response time and its cache replacement policy swaps out entire retrieved sets of queries instead of individual pages. The cache replacement and admission algorithms make use of a profit metric, which considers for each retrieved set its average rate of reference, its size, and execution cost of the associated query. We report on a performance evaluation based on the TPC-D and Set Query benchmarks. These experiments show that WATCHMAN achieves a substantial performance improvement in a decision support environment when compared to a traditional LRU replacement algorithm.

A case for delay-conscious caching of Web documents

Abstract: Caching at proxy servers plays an important role in reducing the latency of the user response, the network delays and the load on Web servers. The cache performance depends critically on the design of the cache replacement algorithm. Unfortunately, most cache replacement algorithms ignore the Web's scale. In this paper we argue for the design of delay-conscious cache replacement algorithms which explicitly consider the Web's scale by preferentially caching documents which require a long time to fetch to the cache. We present a new, delay-conscious cache replacement algorithm LNC-R-W3 which maximizes a performance metric called delay-savings-ratio. Subsequently, we test the performance of LNC-R-W3 experimentally and compare it with the performance of other existing cache replacement algorithms, namely LRU and LRU-MIN.

An Ontology-Based Product Recommender System for B2B Marketplaces

Abstract: An ontology-based product-recommender system can help catalog administrators in B2B marketplaces maintain up-to-date product databases by acquiring mapping information between the new product data and existing data. The proposed approach is keyword-based and independent of the underlying physical structure of product ontology. With a Bayesian belief network as its basis, the ranking algorithm utilizes semantics embedded within relationships defined in ontology to probabilistically determine the ranking scores. The methodology is implemented on a practical ontology system powerful enough to assist users in B2B marketplaces. Its effectiveness is demonstrated in comparison to the conventional search engines.

Recommender system application developments

Abstract: A recommender system aims to provide users with personalized online product or service recommendations to handle the increasing online information overload problem and improve customer relationship management. Various recommender system techniques have been proposed since the mid-1990s, and many sorts of recommender system software have been developed recently for a variety of applications. Researchers and managers recognize that recommender systems offer great opportunities and challenges for business, government, education, and other domains, with more recent successful developments of recommender systems for real-world applications becoming apparent. It is thus vital that a high quality, instructive review of current trends should be conducted, not only of the theoretical research results but more importantly of the practical developments in recommender systems. This paper therefore reviews up-to-date application developments of recommender systems, clusters their applications into eight main categories: e-government, e-business, e-commerce/e-shopping, e-library, e-learning, e-tourism, e-resource services and e-group activities, and summarizes the related recommendation techniques used in each category. It systematically examines the reported recommender systems through four dimensions: recommendation methods (such as CF), recommender systems software (such as BizSeeker), real-world application domains (such as e-business) and application platforms (such as mobile-based platforms). Some significant new topics are identified and listed as new directions. By providing a state-of-the-art knowledge, this survey will directly support researchers and practical professionals in their understanding of developments in recommender system applications. Research papers on various recommender system applications are summarized.The recommender systems are examined systematically through four dimensions.The recommender system applications are classified into eight categories.Related recommendation techniques in each category are identified.Several new recommendation techniques and application areas are uncovered.

The state of the art in distributed query processing

Abstract: Distributed data processing is becoming a reality. Businesses want to do it for many reasons, and they often must do it in order to stay competitive. While much of the infrastructure for distributed data processing is already there (e.g., modern network technology), a number of issues make distributed data processing still a complex undertaking: (1) distributed systems can become very large, involving thousands of heterogeneous sites including PCs and mainframe server machines; (2) the state of a distributed system changes rapidly because the load of sites varies over time and new sites are added to the system; (3) legacy systems need to be integrated—such legacy systems usually have not been designed for distributed data processing and now need to interact with other (modern) systems in a distributed environment. This paper presents the state of the art of query processing for distributed database and information systems. The paper presents the “textbook” architecture for distributed query processing and a series of techniques that are particularly useful for distributed database systems. These techniques include special join techniques, techniques to exploit intraquery paralleli sm, techniques to reduce communication costs, and techniques to exploit caching and replication of data. Furthermore, the paper discusses different kinds of distributed systems such as client-server, middleware (multitier), and heterogeneous database systems, and shows how query processing works in these systems.

A survey of Web cache replacement strategies

Abstract: Web caching is an important technique to scale the Internet. One important performance factor of Web caches is the replacement strategy. Due to specific characteristics of the World Wide Web, there exist a huge number of proposals for cache replacement. This article proposes a classification for these proposals that subsumes prior classifications. Using this classification, different proposals and their advantages and disadvantages are described. Furthermore, the article discusses the importance of cache replacement strategies in modern proxy caches and outlines potential future research topics.

A survey of web caching schemes for the Internet

Abstract: The World Wide Web can be considered as a large distributed information system that provides access to shared data objects. As one of the most popular applications currently running on the Internet, the World Wide Web is of an exponential growth in size, which results in network congestion and server overloading. Web caching has been recognized as one of the effective schemes to alleviate the service bottleneck and reduce the network traffic, thereby minimize the user access latency. In this paper, we first describe the elements of a Web caching system and its desirable properties. Then, we survey the state-of-art techniques which have been used in Web caching systems. Finally, we discuss the research frontier in Web caching.