Distributed (Operating) Systems -Introduction-

1. Distributed (Operating) Systems-Introduction- Fall 2011 Kocaeli University Computer Engineering Department

2. Course Outline • Introduction • What, why, basics... • Distributed Architectures • Interprocess Communication • RPCs, RMI, message- and stream-oriented communication. • Processes and their scheduling • Thread/process scheduling, code/process migration, virtualization. • Naming and location management • Entities, addresses, access points

3. Course Outline • Canonical problems and solutions • Mutual exclusion, leader election, clock synchronization, … • Resource sharing, replication and consistency • DFS, consistency issues, caching and replication • Fault-tolerance • Node failure or network failure ? • Security in distributed Systems • Distributed middleware • Advanced topics: web, cloud computing, green computing, multimedia, and mobile systems.

4. Why Distributed Systems? • Many systems that we use on a daily basis are distributed • World wide web, Google • Face-book • Peer-to-peer file sharing systems • SETI@Home • Grid and cluster computing • Banks (Cash machines) • Useful to understand how such real-world systems work • Course covers basic principles for designing distributed systems

5. Definition of a Distributed System • A distributed system: • Multiple connected CPUs working together • A collection of independent computers that appears to its users as a single coherent system • Examples: parallel machines, networked machines • Advantages • Communication and resource sharing possible • Economics – price-performance ratio • Reliability, scalability • Potential for incremental growth • Disadvantages • Distribution-aware PLs, OSs and applications • Network connectivity essential • Security and privacy

6. Transparency in a Distributed System Transparency is a GOAL of Distributed Systems

7. Degree of Transparency • Transparency is • Not always desirable • Users located in different continents (context-aware) • Not always possible • Hiding failures (you can distinguish a slow computer from a failing one) • Trade-off between a high degree of transparency and the performance of the system

8. Openness (Another goal of DS) • Offer services that are described a priori • Syntax and semantics are known via protocols • Servies specified via interfaces • Benefits • Interoperability • Portability • Extensibility • Open system evolve over time and should be extensible to accommodate new functionality. • Separate policy from mechanism

9. Scalability Problems Examples of scalability limitations Three different dimensions of Scalability • Size (the number of users and/or processes) • Geographical (maximum distance betweenparticipants) • Administrative (number of administrativedomains)

10. Scaling Techniques • Characteristics of decentralized algorithms • No machine has complete state • Make decision based on local information • A single failure does not bring down the system • No global clock • Techniques • Asynchronous communication (for geographical scalability) • Distribution (slide no 12) • Caching and replication

11. Scaling Techniques (1) • The difference between letting: • A server or • A client check forms as they are being filled

12. Scaling Techniques (2) An example of dividing the DNS name space into zones.

13. Distributed Systems Models • Distributed Computing Systems • Cluster Computing • Grid Computing • Cloud Computing • Distributed Information Systems • Distributed Embedded Systems

14. Cluster Computing Systems • Collection of similar workstations and PCs closely connected by means of high-speed local area network

15. Grid Computing Systems • Collection of distributed systems where each system may fall under a different administrative domain. • Hardware, software and network are most probably very different Grid middleware layer

16. Cloud Computing • Cloud computing is a type of Grid computing OR evaluation result of Grid computing • Grid says: “Let’s join our domains and efforts by shaing your resurces in order to get more computational power”. • Cloud says: “We can provide you more computational power than what you need. Just tell us what you want and we will give it to you”.

17. Emerging Models • Distributed Pervasive Systems • “smaller” nodes with networking capabilities • Computing is “everywhere” • lack of human admin control • Home networks: TiVO, Windows Media Center, … • Mobile computing: smart phones, iPODs, Car-based PCs • Sensor networks* • Health-care: personal area networks*

18. Pervasive/Ubiquitous Computing • Move beyond desktop machine • Computing is embedded everywhere in the environment • Computing capabilities, any time, any place • “Invisible” resources • Machines sense users’ presence and act accordingly

19. Sensor Networks (1) • Questions concerning sensor networks: • How do we (dynamically) set up an efficient tree in a sensor network? • How does aggregation of results take place? Can it be controlled? • What happens when network links fail?

20. Sensor Networks (2) • Organizing a sensor network database, while storing and processing data (a) only at the operator’s site or …

21. Sensor Networks (3) • Organizing a sensor network database, while storing and processing data … or (b) only at the sensors

22. Electronic Health Care Systems (1) • Questions to be addressed for health care systems: • Where and how should monitored data be stored? • How can we prevent loss of crucial data? • What infrastructure is needed to generate and propagate alerts? • How can physicians provide online feedback? • How can extreme robustness of the monitoring system be realized? • What are the security issues and how can the proper policies be enforced?

23. Electronic Health Care Systems (2) • Figure 1-12. Monitoring a person in a pervasive electronic health care system, using (a) a local hub or • (b) a continuous wireless connection.

24. Types of Operating Systems

25. Uniprocessor Operating Systems • An OS acts as a resource manager or an arbitrator • Manages CPU, I/O devices, memory • OS provides a virtual interface that is easier to use than hardware • Structure of uniprocessor operating systems • Monolithic (e.g., MS-DOS, early UNIX) • One large kernel that handles everything • Layered design • Functionality is decomposed into N layers • Each layer uses services of layer N-1 and implements new service(s) for layer N+1

26. Uniprocessor Operating Systems • Microkernel architecture • Small kernel • user-level servers implement additional functionality

27. Distributed Operating System • Manages resources in a distributed system • Seamlessly and transparently to the user • Looks to the user like a centralized OS • But operates on multiple independent CPUs • Provides transparency • Location, migration, concurrency, replication,… • Presents users with a virtual uniprocessor

28. Multiprocessor Operating Systems • Multi-core • Like a uniprocessor operating system • Manages multiple CPUs transparently to the user • Shared main memory and controlled by a single OS instance • Each processor has its own hardware cache • Maintain consistency of cached data

29. Distributed Operating Systems (1) • Example: MOSIX cluster - single system image

30. Distributed Operating Systems (2) • Gives illusion of single system • Users not aware of multiplicity of machines • Access to remote resources similar to access to local resources • Data Migration – transfer data by transferring entire file, or transferring only those portions of the file necessary for the immediate task • Computation Migration – transfer the computation, rather than the data, across the system

31. Network Operating System (1)

32. Network Operating System (2) • Users are aware of multiplicity of machines. Access to resources of various machines is done explicitly by: • Remote logging into the appropriate remote machine (telnet, ssh) • Remote Desktop (Microsoft Windows) • Transferring data from remote machines to local machines, via the File Transfer Protocol (FTP) mechanism

33. Middleware-based Systems

34. Types of Distributed OSs

35. Comparison between Systems

36. Pitfalls when Developing Distributed Systems • False assumptions made by first time developer: • The network is reliable. • The network is secure. • The network is homogeneous. • Latency is zero. • Bandwidth is infinite. • Transport cost is zero. • There is one administrator.