Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Concurrency control and recovery in database systems
Concurrency control and recovery in database systems
IEEE Transactions on Software Engineering
A model for the stability analysis of maintenance strategies for linear list
The Computer Journal - Special issue on term rewriting
Fundamentals of database systems (2nd ed.)
Fundamentals of database systems (2nd ed.)
Gigabit networking
Performance analysis of on-the-fly garbage collection
Communications of the ACM
Password security: a case history
Communications of the ACM
On-the-fly garbage collection: an exercise in cooperation
Communications of the ACM
Optimal reorganization of distributed space disk files
Communications of the ACM
Computer Performance Modeling Handbook
Computer Performance Modeling Handbook
Cryptography and data security
Cryptography and data security
Simulation and the Monte Carlo Method
Simulation and the Monte Carlo Method
Operating System Concepts
Multilevel Data Structures: Models and Performance
IEEE Transactions on Software Engineering
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
Issues in Analyzing the Behavior of Event Dispatching Systems
IWSSD '00 Proceedings of the 10th International Workshop on Software Specification and Design
Online reorganization of databases
ACM Computing Surveys (CSUR)
Online monitoring and visualisation of database structural deterioration
International Journal of Autonomic Computing
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We develop a methodology for analyzing the performance and stability of a server that maintains a multilevel data structure to service a set of access operations for (key, value) records. A subset of the operations executed by the server (e.g., insert and delete) require the multilevel data structure be reorganized so that the server can execute all subsequent requests efficiently. We study how often the server should carry out data reorganization (i.e., maintenance) to maximize its performance. If the server is frequently idle then there is no need to impose the reorganization overhead on the operation requests. The reorganization overhead may be completely eliminated by utilizing server-idling periods. If the server is frequently busy, then the reorganization overhead can be minimized by performing a complete reorganization only after the server has served a sufficient number of insert/delete operations so that the amortized cost per operation is small. Therefore, the issue of how often one should perform data reorganization to minimize the average service time depends not only on the multilevel data structure maintained by the server but also on the type and intensity of the system workload. The proposed methodology is exemplified with a two-level sorted file with deferred maintenance. The performance and stability results are compared with those of a single-level binary tree data structure with on-the-fly maintenance. It is shown that deferred maintenance of the two-level sorted file outperforms on-the-fly maintenance of the single-level binary tree in both open and closed systems. Furthermore, deferred maintenance can sustain higher workload intensities without risking system stability.