Introduction

1. Introduction

2. Outline • Definitions • Examples • Hardware concepts • Software concepts • Readings: Chapter 1

3. Quotable quote “I think there is a world market for maybe five computers” Thomas J. WatsonChairman of IBM, 1943

4. Definition of a Distributed System (Tannenbaum and van Steen) A distributed system is a piece of software that ensures that A collection of independent computers that appears to its users as a single coherent system.

5. Definition of a Distributed System (Colouris) A distributed system is In which hardware and software components located at networked computers communicate and coordinate their actions only by passing messages.

6. Definition of a Distributed System (Lamport) A distributed system is one in which I cannot get something done because a machine I've never heard of is down.

7. Primary Characteristics of a Distributed System • Multiple computers • Concurrent execution • Independent operation and failures • Communications • Ability to communicate • No tight synchronization • Relatively easy to expand or scale • Transparency

8. Example: A typical intranet (Coulouris)

9. intranet % % ISP % % backbone satellite link desktop computer: server: network link: Example: A typical portion of the Internet (Coulouris)

10. Example: Portable and handheld devices in a distributed system (Coulouris)

11. Why Build Distributed Systems? • Economics • Share resources • Relatively easy to expand or scale • Speed – A distributed system may have more total computing power then a mainframe. • Reliability • If a machine crashes, the system as a whole can survive. • People are distributed, information is distributed.

12. Key Design Goals • Connectivity • Transparency • Reliability • Consistency • Security • Openness • Scalability

13. Connectivity • It should be easy for users to access remote resources and to share them with other users in a controlled fashion. • Resources that can be shared include printers, storage facilities, data, files, web pages, etc; • Why? Economical • Connecting users and resources makes collaboration and the exchange of information easier. • Just look at e-mail

14. Transparency • A distributed system that is able to present itself to users and applications as if it were only a single computer system is said to be transparent. • Very difficult to make distributed systems completely transparent. • You may not want to, since transparency often comes at the cost of performance.

15. Transparency in a Distributed System Different forms of transparency in a distributed system.

16. Degree of Transparency • The goal of full transparency is not always desirable. • Users may be located in different continents; distribution is apparent and not something you want to hide. • Completely hiding failures of networks and nodes is (theoretically and practically) impossible: • You cannot distinguish a slow compuer from a failing one. • You can never be sure that a server actually performed an operation before a crash. • Full transparency will cost in performance. • Keeping Web caches exactly up-to-date with the master copy • Immediately flushing write operations to disk for fault tolerance.

17. Openness • An open distributed system allows for interaction with services from other open systems, irrespectively of the underlying environment. • Systems should conform to well-defined interfaces. • Systems should support portability of applications. • Systems should easily interoperate. Interoperability is characterized by the extent by which two implementations of systems or components from different manufacturers can co-exist and work together. • Example: In computer networks there are rules that govern the format, contents and meaning of messages send and received.

18. Scalability • There are three dimensions to scalability: • The number of users and processes (size scalability) • The maximum distance between nodes (geographical scalability) • The number of administrative domains (administrative scalability) • Most systems focus on administrative size scalability • Well sort of – the typical solution is to buy powerful servers.

19. Techniques for Scaling • Partition data and computations across multiple machines • Move computations to clients (Java applets) • Decentralized naming services (DNS) • Decentralized information systems (WWW) • Make copies of data available at different machines • Replicated file servers (for fault tolerance) • Replicated databases • Mirrored web sites • Allow client processes to access local copies • Web caches (browser/Web proxy) • File caching (at server and client)

20. Scaling – The problem • Applying scaling techniques is easy, except for the following: • Having multiple copies (cached or replicated) leads to inconsistencies – modifying one copy makes that copy different from the rest. • Always keeping copies consistent requires global synchronization. • Global synchronization is expensive with respect to performance. • We have learned to tolerate some inconsistencies.

21. Challenges • Heterogeneity • Networks • Hardware • Operating systems • Programming languages

22. Challenges • Failure Handling • Partial failures • Can non-failed components continue operation? • Can the failed components easily recover? • Detecting failures • Recovery • Replication

23. Hardware Concepts • Multiprocessors • Multicomputers • Networks of computers

24. Multiprocessors and Multicomputers 1.6 Different basic organizations and memories in distributed computer systems

25. Multiprocessors • Coherent memory • Each CPU writes though, reflected at other immediately • Note the use of cache memory for efficiency • Limited to small number of processors

26. Homogeneous Multicomputer Systems • Grid • Hypercube 1-9

27. Multiprocessor Usage • Scientific and engineering applications often require loops over large vectors e.g., matrix elements or points in a grid or 3D mesh. Applications include • computational fluid dynamics • dynamic structures • scheduling (airline) • health and biological modeling • economics and financial modelling (e.g., option pricing) • Other applications include: • Transaction processing • Video on demand

28. Networks of Computers • High degree of node heterogeneity • Nodes include PCs, workstations, multimedia workstations, palmtops, laptops • High degree of network heterogeneity • This includes local-area ethernet, Atm and wireless connections. • A distributed system should try to hide these differences. • In this course, the focus really is in networks of computers.

29. Software Concepts • An overview between • DOS (Distributed Operating Systems) • NOS (Network Operating Systems) • Middleware

30. Distributed Operating System OS on each computer knows about the other computers OS on different computer is generally the same Services are generally (transparently) distributed across computers. 1.14

31. Distributed Operating System • This is harder to implement then a traditional operating system. Why? • Memory is not shared • No simple global communication • No simple systemwide synchronization mechanisms • May require that OS maintain global memory map in software. • No central point where resource allocation decisions can be made. • Only very few truly multicomputer operating systems exist.

32. Network Operating System • Each computer has its own operating system with networking facilities • Computers work independently i.e., they may even have different operating systems • Services are tied to individual nodes (ftp, telnet, www) • Highly file oriented

33. Middleware OS on each computer need not know about the other computers OS on different computers may be different Services are generally (transparently) distributed across computers.

34. Middleware and Openness • In an open middleware-based distributed system, the protocols used by each middleware layer should be the same, as well as the interfaces they offer to applications. 1.23

35. Middleware Services • Communication Services • Hide “primitive” socket programming • Data management in a distributed system • Naming services • Directory services (e.g., LDAP, search engines) • Location services for tracking mobile objects • Persistent storage facilities • Data caching and replication

36. Middleware Services • Services giving applications control over when, where and how they access data. • Distributed transaction processing • Code migration • Services for securing processing and communication: • Authentication and authorization services • Simple encryption services • Auditing services • There are varying levels of success in being able to provide these types of middleware services.