This article discusses the challenges in computer systems research posed by the emerging field of pervasive computing. It first examines the relationship of this new field to its predecessors: distributed systems and mobile computing. It then identifies four new research thrusts: effective use of smart spaces, invisibility, localized scalability, and masking uneven conditioning. Next, it sketches a couple of hypothetical pervasive computing scenarios, and uses them to identify key capabilities missing from today's systems. The article closes with a discussion of the research necessary to develop these capabilities.

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Pervasive computing: vision and challenges

This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels. The material concentrates on fundamental theories as well as techniques and algorithms. The advent of the Internet and the World Wide Web, and, more recently, the emergence of cloud computing and streaming data applications, has forced a renewal of interest in distributed and parallel data management, while, at the same time, requiring a rethinking of some of the traditional techniques. This book covers the breadth and depth of this re-emerging field. The coverage consists of two parts. The first part discusses the fundamental principles of distributed data management and includes distribution design, data integration, distributed query processing and optimization, distributed transaction management, and replication. The second part focuses on more advanced topics and includes discussion of parallel database systems, distributed object management, peer-to-peer data management, web data management, data stream systems, and cloud computing. New in this Edition: New chapters, covering database replication, database integration, multidatabase query processing, peer-to-peer data management, and web data management. Coverage of emerging topics such as data streams and cloud computing Extensive revisions and updates based on years of class testing and feedback Ancillary teaching materials are available.

Principles of Distributed Database Systems

Mining for a.ssociation rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an efficient algorithm for mining association rules that is fundamentally different from known algorithms. Compared to previous algorithms, our algorithm not only reduces the I/O overhead significantly but also has lower CPU overhead for most cases. We have performed extensive experiments and compared the performance of our algorithm with one of the best existing algorithms. It was found that for large databases, the CPU overhead was reduced by as much as a factor of four and I/O was reduced by almost an order of magnitude. Hence this algorithm is especially suitable for very large size databases.

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An Efficient Algorithm for Mining Association Rules in Large Databases

This survey covers rollback-recovery techniques that do not require special language constructs. In the first part of the survey we classify rollback-recovery protocols into checkpoint-based and log-based.Checkpoint-based protocols rely solely on checkpointing for system state restoration. Checkpointing can be coordinated, uncoordinated, or communication-induced. Log-based protocols combine checkpointing with logging of nondeterministic events, encoded in tuples called determinants. Depending on how determinants are logged, log-based protocols can be pessimistic, optimistic, or causal. Throughout the survey, we highlight the research issues that are at the core of rollback-recovery and present the solutions that currently address them. We also compare the performance of different rollback-recovery protocols with respect to a series of desirable properties and discuss the issues that arise in the practical implementations of these protocols.

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A survey of rollback-recovery protocols in message-passing systems

Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On the contrary, modern data models exacerbate the problem: In order to manipulate large sets of complex objects as efficiently as today's database systems manipulate simple records, query-processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software. This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.

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Query evaluation techniques for large databases

From the Publisher:
The key to client/server computing.
Transaction processing techniques are deeply ingrained in the fields of databases and operating systems and are used to monitor, control and update information in modern computer systems. This book will show you how large, distributed, heterogeneous computer systems can be made to work reliably. Using transactions as a unifying conceptual framework, the authors show how to build high-performance distributed systems and high-availability applications with finite budgets and risk.

The authors provide detailed explanations of why various problems occur as well as practical, usable techniques for their solution. Throughout the book, examples and techniques are drawn from the most successful commercial and research systems. Extensive use of compilable C code fragments demonstrates the many transaction processing algorithms presented in the book. The book will be valuable to anyone interested in implementing distributed systems or client/server architectures.

Transaction Processing: Concepts and Techniques

Three benchmarks are defined: Sort, Scan and DebitCredit. The first two benchmarks measure a system's input/output performance. DebitCredit is a simple transaction processing application used to define a throughput measure -Transactions Per Second (TPS). These benchmarks measure the performance of diverse transaction processing systems. A standard system cost measure is stated and used to define price/performance metrics. A condensed version of this paper appears in Datamation, April 1, 1985

A measure of transaction processing power

On April 23, 1993 a panel discussion was held at the IEEE International Conference on Data Engineering in Vienna, Austria, at which five members of the data base research community discussed future research topics in the DBMS area. This paper summarizes the discussion which took place. The panel followed a similar format to that used at Laguna Beach four years earlier, and four of the five panelists attended the earlier conference. As such, we contrast the recommendations of the Laguna Beach participants with those obtained four years later by a similar group.

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DBMS Research at a Crossroads: The Vienna Update

On February 4-5, 1988, the International Computer Science Institute sponsored a two day workshop at which 16 senior members of the data base research community discussed future research topics in the DBMS area. This paper summarizes the discussion which took place.

Andreas Reuter

Papers

Transaction Processing: Concepts and Techniques

A measure of transaction processing power

DBMS Research at a Crossroads: The Vienna Update

Future Directions in DBMS Research - The Laguna Beach Participants

Future directions in DBMS research