ARTIFICIAL INTELLIGENCE ENGINEERING | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
CMP4502 | Distributed Databases | Spring |
3 | 0 | 3 | 6 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Non-Departmental Elective |
Course Level: | Bachelor’s Degree (First Cycle) |
Mode of Delivery: | Face to face |
Course Coordinator : | Dr. Öğr. Üyesi TARKAN AYDIN |
Recommended Optional Program Components: | None |
Course Objectives: | Communication paradigms: client/server protocols, remote procedure call (e.g., Java RMI), multicast protocols handling asynchronous communication and failures. Distributed transaction management requires enhanced concurrency control methods. Comparing algorithms proposed by researchers and commercial solutions. Replicating data to increase fault-tolerance and the performance of databases. |
The students who have succeeded in this course; 1. Be able to understand Distributed computing systems, their characteristics, and desired functionality 2. Become familiar with Distributed computer system models and architectures 3. Be able to understand Synchronization 4. Be able to understand Replication 5. Be able to use distributed naming 6. Be able to understand Fault-tolerance |
1.Introduction 2.DDBMS Architecture 3.Distributed Database Design 4.Semantic Integrity Control 5.Query decomposition and data localization 6.Optimization of Distributed Queries 7.Transactions 8.Concurrency Control 9.Reliability |
Week | Subject | Related Preparation |
1) | Introduction: syllabus, administration and organization of the course, general introduction in distributed DBMS | None |
2) | DDBMS Architecture: definition of DDBMS architecture, ANSI/SPARC standard, global, local, external, and internal schemas, DDBMS architectures, components of DDBMS | None |
3) | Distributed Database Design: conceptual design (what can be distributed, design patterns), top-down, bottom-up patterns, technical design (fragmentation, allocation and replication of fragments, optimality, heuristics) | None |
4) | Semantic Integrity Control: view management, security control, integrity control | None |
5) | Semantic Integrity Control: view management, security control, integrity control | None |
6) | Midterm Exam 1 | Review all the topics |
7) | Query decomposition and data localization: normalization, analysis, elimination of redundancy, rewriting, reduction for HF, reduction for VF | None |
8) | Optimization of Distributed Queries: basic concepts, distributed cost model, database statistics | None |
9) | Optimization of Distributed Queries: ordering of joins and semijoins, query optimization algorithms, INGRES, System R, hill climbing | None |
10) | Transactions: introduction to transactions, definition and examples, properties, classification, processing issues, execution | None |
11) | Midterm Exam 2 | Review all the topics |
12) | Concurrency Control: definition, execution schedules, examples, locking based algorithms, timestamp ordering algorithm, deadlock management | None |
13) | Reliability: definitions, basic concepts, local recovery management, distributed reliability protocols | None |
14) | Reliability: distributed reliability protocols, 2PC protocol | None |
Course Notes / Textbooks: | Principles of Distributed Database Systems by M. Tamer Özsu and Patrick Valduriez |
References: | None |
Semester Requirements | Number of Activities | Level of Contribution |
Project | 1 | % 10 |
Midterms | 2 | % 40 |
Final | 1 | % 50 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 40 | |
PERCENTAGE OF FINAL WORK | % 60 | |
Total | % 100 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Have sufficient background in mathematics, science and artificial intelligence engineering. | |
2) | Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions. | |
3) | Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose. | |
4) | Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction. | |
5) | Select and use modern techniques and tools necessary for engineering applications. | |
6) | Design and conduct experiments, collect data, and analyse and interpret results. | |
7) | Work effectively both as an individual and as a multi-disciplinary team member. | |
8) | Access information via conducting literature research, using databases and other resources | |
9) | Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning. | |
10) | Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field. | |
11) | Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level. | |
12) | Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age. | |
13) | Have a sense of professional and ethical responsibility. | |
14) | Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices. |