Survey of Autonomic Computing and Experiments on JMX-based Autonomic Features

Autonomic Computing (AC) aims at solving the problem of managing the rapidly-growing complexity of Information Technology systems, by creating self-managing systems. In this thesis, we have surveyed the progress of the AC field, and studied the requirements, models and architectures of AC. The commonly recognized AC requirements are four properties - self-configuring, self-healing, self-optimizing, and self-protecting. The recommended software architecture is the MAPE-K model containing four modules, namely - monitor, analyze, plan and execute, as well as the knowledge repository. In the modern software marketplace, Java Management Extensions (JMX) has facilitated one function of the AC requirements - monitoring. Using JMX, we implemented a package that attempts to assist programming for AC features including socket management, logging, and recovery of distributed computation. In the experiments, we have not only realized the powerful Java capabilities that are unknown to many educators, we also illustrated the feasibility of learning AC in senior computer science courses

Network and Database Security: Regulatory Compliance, Network, and Database Security - A Unified Process and Goal

Database security has evolved; data security professionals have developed numerous techniques and approaches to assure data confidentiality, integrity, and availability. This paper will show that the Traditional Database Security, which has focused primarily on creating user accounts and managing user privileges to database objects are not enough to protect data confidentiality, integrity, and availability. This paper is a compilation of different journals, articles and classroom discussions will focus on unifying the process of securing data or information whether it is in use, in storage or being transmitted. Promoting a change in Database Curriculum Development trends may also play a role in helping secure databases. This paper will take the approach that if one make a conscientious effort to unifying the Database Security process, which includes Database Management System (DBMS) selection process, following regulatory compliances, analyzing and learning from the mistakes of others, Implementing Networking Security Technologies, and Securing the Database, may prevent database breach

Gewinnung, Verwaltung und Anwendung von Performance-Daten zur Unterstützung des autonomen Datenbank-Tuning

In den letzten Jahrzehnten ist die Komplexität und Heterogenität von Informationssystemen rapide gestiegen. Die Folge ist, dass viele moderne IT-Systeme aufgrund ihrer heterogenen Architektur- und Applikationsvielfalt sehr kostenintensiv in der Entwicklung, fehleranfällig in der Nutzung und schwierig durch Administratoren kontrollier- bzw. konfigurierbar sind. Initiativen wie das Autonomic Computing helfen, der steigenden Komplexität Herr zu werden, indem sie den „Problemfaktor Mensch“ entlasten und Technik nutzen, um Technik zu verwalten. Durch die Anpassung bzw. Erweiterung der System-Umgebung versuchen derartige Ansätze neben derzeitiger manueller, reaktiver Performance-Optimierung, eine automatisierte reaktive und proaktive Performance-Kontrolle zu gewährleisten. Zentrale Grundvoraussetzung für eine autonome Infrastruktur ist eine verlässliche, globale Daten- bzw. Wissensbasis. Wir erarbeiten, wie Performance-Daten über das Verhalten und den Zustand des Systems mit aus dem Data-Warehousing bekannten Techniken gesammelt, konsolidiert, verwaltet und zur Laufzeit ausgewertet werden können. Neben der Architektur und den funktionalen Komponenten eines solchen Performance Data Warehouse wird zudem dessen Datenmodell erläutert und die Anbindung an das vorausgehende Monitoring sowie die nachfolgende Analyse spezifiziert. Mit dem Ziel, die menschliche Vorgehensweise „nachzuahmen“ und somit die Administratoren bei ihren Routine-Tätigkeiten zu entlasten, widmen wir uns der Konzipierung und Beschreibung einer möglichen Infrastruktur zur Automatisierung typischer Tuning-Aufgaben. Wir erarbeiten allgemein und anhand von Beispielen, wie Tuning-Wissen und bewährte Praktiken von DBAs abgebildet, in Form von Workflows formalisiert und zur Laufzeit für die Problemlösung angewendet werden können

Sizing Multiple Buffer Pools for

The buffer area is a key resource in database management systems (DBMSs) and the performance of a DBMS is greatly influenced by the effective use of the buffer area. Current DBMSs such as DB2 Universal Database (DB2/UDB), logically divide the buffer area into a number of independent buffer pools. Each database object (table or index) is assigned to a specific buffer pool. The task of configuring the buffer pools, which defines the mapping of database objects to buffer pools and the setting the size for each of the buffer pools, is crucial for achieving optimal performance. In this thesis, we focus on the buffer pool sizing problem. The goal of our research is to support the DBMS automatically determining an optimal buffer pool sizes for a given workload. This problem has been shown to be a complex constrained optimization problem. Currently this task is performed manually by the database administrators (DBAs). We present a cost model based on data access time and use a greedy algorithm to solve the optimization problem. The approach is implemented and verified against the TPC-C benchmark database using DB2/UDB. Experimental results show the cost model is accurate, and that the greedy algorithm is fast and sufficient in finding an optimal buffer pool sizes. i Acknowledgements I would like to express my sincere gratitude to my supervisor, Dr. Pat Martin, for his excellent guidance, precious advice and endless support during my graduate study and research at Queen's University. Without his help, this thesis would never have got finished. I would also like to thank Wendy Powley, our wonderful database expert, for the help in setting up the experimental environments and the suggestions about writing this thesis. My thanks also go to my friendly labmates, whose help and advice is very helpful to this thesis. Special thanks are given to the School of Computing at Queen’s University for providing me the opportunity to pursue graduate studies and their support. I also thank IBM Canada Ltd. NSERC, and CITO for the financial support. Finally, I would like to thank my parents, and my beautiful wife, Jie Lu, for their love, support, and encouragement in these years. i

Abstract Configuring Buffer Pools in DB2 UDB *♦ Database Management Systems (DBMSs) use a

main memory area as a buffer to reduce the number of disk accesses performed by a transaction. DB2 Universal Database divides the buffer area into a number of independent buffer pools and each database object (table or index) is assigned to a specific buffer pool. The tasks of configuring the buffer pools, which defines the mapping of database objects to buffer pools and setting a size for each of the buffer pools, is crucial for achieving optimal performance. Mapping database objects to buffer pools, which we refer to as the “buffer pool configuration problem", is the focus of this paper. Mapping database objects to buffer pools can be viewed as a partitioning problem, that is, we partition the database objects into groups where each group is assigned a separate buffer pool. The partitioning of objects is based on how the objects are used and on the inherent properties of objects. We present an approach to the configuration problem based on analyzing the access behaviour of a given database workload to the set of database objects. The approach is demonstrated with a typical OLTP workload.