Adapting ACME to the database caching environment : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Information Systems at Massey University

The field of database cache replacement has seen a great many replacement policies presented in the past few years. As the challenge to find the optimal replacement policy continues, new methods and techniques of determining cache victims have been proposed, with some methods having a greater effect on results than others. Adaptive algorithms attempt to adapt to changing patterns of data access by combining the benefits of other existing algorithms. Such adaptive algorithms have recently been proposed in the web-caching environment. However, there is a lack of such research in the area of database caching. This thesis investigates an attempt to adapt a recently proposed adaptive caching algorithm in the area of web-caching, known as Adaptive Caching with Multiple Experts (ACME), to the database environment. Recently proposed replacement policies are integrated into ACME'S existing policy pool, in an attempt to gauge its ability and robustness to readily incorporate new algorithms. The results suggest that ACME is indeed well-suited to the database environment, and performs as well as the best currently caching policy within its policy pool at any particular point in time in its request stream. Although execution time increases by integrating more policies into ACME, the overall time saved increases by avoiding disk reads due to higher hit rates and fewer misses on the cache

Pattern Matching Query Verification on the Cloud

Query verification protocols allow cloud consumers to validate the correctness of query results posed against cloud-hosted data. This study proposed query verification protocols for verifying the correctness of pattern-matching queries posed against cloud-hosted data. Efficient protocols were proposed for string matching and regular expression queries executed on the cloud

String matching query verification on the cloud-hosted databases

Database query verification schemes attempt to provide authenticity, completeness, and freshness guarantees for queries executed on untrusted cloud servers. A number of such schemes currently exist in the literature, allowing query verification for queries that are based on matching whole values (such as numbers, dates, etc.) or for queries based on keyword matching. However, there is a notable gap in the research with regard to query verification schemes for pattern-matching queries. Our contribution here is to provide such a verification scheme that provides correctness guarantees for pattern-matching queries executed on the cloud. We describe a trivial scheme, ȃŸż and show how it does not provide completeness guarantees, and then proceed to describe our scheme based on efficient primitives such as cryptographic hashing and Merkle hash trees along with suffix arrays. We also provide experimental results based on a working prototype to show the practicality of our scheme.Ÿ

Query verification schemes for cloud-hosted databases: a brief survey

Database query verification schemes provide correctness guarantees for database queries. Typically such guarantees are required and advisable where queries are executed on untrusted servers. This need to verify query results, even though they may have been executed on one’s own database, is something new that has arisen with the advent of cloud services. The traditional model of hosting one’s own databases on one’s own servers did not require such verification because the hardware and software were both entirely within one’s control, and therefore fully trusted. However, with the economical and technological benefits of cloud services beckoning, many are now considering outsourcing both data and execution of database queries to the cloud, despite obvious risks. This survey paper provides an overview into the field of database query verification and explores the current state of the art in terms of query execution and correctness guarantees provided for query results. We also provide indications towards future work in the area

String matching query verification on the cloud-hosted databases

Database query verification schemes attempt to provide authenticity, completeness, and freshness guarantees for queries executed on untrusted cloud servers. A number of such schemes currently exist in the literature, allowing query verification for queries that are based on matching whole values (such as numbers, dates, etc.) or for queries based on keyword matching. However, there is a notable gap in the research with regard to query verification schemes for pattern-matching queries. Our contribution here is to provide such a verification scheme that provides correctness guarantees for pattern-matching queries executed on the cloud. We describe a trivial scheme, ȃŸż and show how it does not provide completeness guarantees, and then proceed to describe our scheme based on efficient primitives such as cryptographic hashing and Merkle hash trees along with suffix arrays. We also provide experimental results based on a working prototype to show the practicality of our scheme.Ÿ

Using Reflection for Querying XML Documents

XML-based databases have become a major area of interest in database research. Abstractly speaking they can be considered as a resurrection of complexvalue databases using constructors for records, lists, unions plus optionality and references. XQuery has become the standard query language for XML. In this paper an implementation of XQuery based on linguistic reflection is proposed. That is, XQuery is translated into a query algebra for rational tree types based on simple operations and structural recursion for lists. The major purpose of using reflection is to expand path expressions in a type-safe way