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Introduction

Distributed Systems CS 3850 Soufiane Noureddine Lectures MWF 14:00 – 14:50 (PE207D) Office Hours MW 11:00 – 12:00 (C520). Introduction. Chapter 1. Computer Networks.

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Introduction

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  1. Distributed SystemsCS 3850Soufiane NoureddineLecturesMWF 14:00 – 14:50 (PE207D)Office HoursMW 11:00 – 12:00 (C520)

  2. Introduction Chapter 1

  3. Computer Networks A collection of computers communicating through an underlying network is called a computer network (in contrast to a single-processor system) Local Area Network: LAN 10 to 1000 Mb/sec Wide Area Network: WAN 64 kbps to gigabits/sec

  4. Definition of a Distributed System (1) • A distributed system is: • A collection of independent computers that appears to its users as a single coherent system. • A. Tanenbaum

  5. Definition of a Distributed System (2) “You know you have one when the crash of a computer you never heard of stops you from getting any work done.” L. Lamport

  6. Organization of a Distributed System 1.1 A distributed system organized as middleware.Note that the middleware layer extends over multiple machines.

  7. Characteristics of a distributed System  Differences between computers are hidden  Communication between computers is hidden  Internal organization of the system is hidden  Single system image: interaction with the system is independent from location (and time)  Ease of extension  High availability

  8. Examples of distributed Systems • Network of workstations + Pool of processors: • - Single file system (uniform naming scheme) • - Processors are allocated dynamically when needed (load sharing) • - System acts like a single-processor system • 2. Workflow systems • - Orders arrive dynamically (e.g. via laptops, cellular phones) • - System assigns orders to the corresponding departments and initiates the needed business processes and users are unaware of the internal flow of orders • - System acts like a centralized database • WWW • - No need to know where documents are stored (at least in theory) • - Accessing remote documents is like accessing local ones

  9. Goals of distributed Systems • Connecting users and resources: •  consequence: communication and collaboration (e.g. joint editing) •  issue: security • 2. Openness • - Services should obey to standard rules specifying syntax and semantics • - Services are specified in general as interfaces in an interface definition language • - IDL includes rather syntax and no semantics • - Specification of interface should be completed and neutral (w.r.t. implementation) • - Openness promotes interoperability and portability • Transparency (see next slides) • Scalability (see next slides)

  10. Transparency in a Distributed System Different forms of transparency in a distributed system. Degree of transparency: More transparency means less performance In reality: Systems are transparent only to certain degree

  11. Network (e.g. Telecom) Clients Software Developers e.g. Company Network Provider

  12. Network (e.g. Telecom) Clients Software Developers e.g. Company Company A Company B Network Provider

  13. Network (e.g. Telecom) Clients Software Developers e.g. Company Company A Company B Network Provider

  14. Network (e.g. Telecom) Clients Software Developers e.g. Company Company A Company B Network Provider

  15. Network (e.g. Telecom) Clients Software Developers e.g. Company Company A Company B Network Provider

  16. Network (e.g. Telecom) Clients Software Developers e.g. Company Applications Operating System & Hardware Network Provider

  17. Network (e.g. Telecom) Clients Software Developers e.g. Company Applications AEM: Availability Enhancing Middleware Operating System & Hardware Network Provider

  18. Scalability Problems A system is scalable when it is easy to extend without loss of performance. • Examples of scalability limitations. • Centralized solutions tend to be non-scalable • Decentralized solutions promote scalability

  19. Decentralized Algorithms • No machine has complete information about the system state • Machines make decisions based only on local information • Failures of one machine does not ruin the whole algorithm • No assumption on the existence of a global time

  20. Scaling Techniques (1) • Ways to solve scalability problems: • Hide communication latencies (geographical scalability) • Use of distribution (in order to avoid bottlenecks) • Use of replication • Ad a) • Batch processing: Asynchronous communication instead of synchronous communication • Interactive applications: Reduce overall communication Example: Move part of computation from server to client (e.g. Java applet)

  21. Scaling Techniques (2) 1.4 • The difference between letting: • a server or • a client check forms as they are being filled

  22. Scaling Techniques (3) Ad b) Use of distribution 1.5 An example of dividing the DNS name space into zones. Clientserver Z1: nl.vu.cs.fluit Server Z1  Client: address of Z2 Clientserver Z2: vu.cs.fluit …

  23. Scaling Techniques (4) • Ad c) Use of replication • Replication raises: • Availability: in general the primary goal • Performance: • By balancing the load among replicas • By locating replicas close to users/clients • Example: Caching (e.g. browser cache for used WWW pages) • Main issue in connection with replication: consistency

  24. Hardware Concepts 1.6 Different basic organizations and memories in distributed computer systems

  25. Multiprocessors (1) 1.7 A bus-based multiprocessor. Issues: Scalability Cache consistency

  26. Multiprocessors (2) 1.8 • A crossbar switch: n2 switches! • An omega switching network: less switches

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

  28. Software Concepts • An overview of • DOS (Distributed Operating Systems) • NOS (Network Operating Systems) • Middleware

  29. Uniprocessor Operating Systems 1.11 Separating applications from operating system code through a microkernel.

  30. Multiprocessor Operating Systems (1) monitor Counter { private: int count = 0; public: int value() { return count;} void incr () { count = count + 1;} void decr() { count = count – 1;} } A monitor to protect an integer against concurrent access.

  31. Multiprocessor Operating Systems (2) monitor Counter { private: int count = 0; int blocked_procs = 0; condition unblocked; public: int value () { return count;} void incr () { if (blocked_procs == 0) count = count + 1; else signal (unblocked); } void decr() { if (count ==0) { blocked_procs = blocked_procs + 1; wait (unblocked); blocked_procs = blocked_procs – 1; } else count = count – 1; } } A monitor to protect an integer against concurrent access, but blocking a process.

  32. Multicomputer Operating Systems (1) 1.14 General structure of a multicomputer operating system

  33. Multicomputer Operating Systems (2) 1.15 Alternatives for blocking and buffering in message passing.

  34. Multicomputer Operating Systems (3) Relation between blocking, buffering, and reliable communications.

  35. Distributed Shared Memory Systems (1) • Pages of address space distributed among four machines • Situation after CPU 1 references page 10 • Situation if page 10 is read only and replication is used • Replicating all pages: •  Coherence protocols: • a) strong (transparent) • b) weak (not transparent)

  36. Distributed Shared Memory Systems (2) Page size: small  more communication overhead large  less communication, but false sharing may occur 1.18 False sharing of a page between two independent processes. Problem with DSM: not as efficient as expected

  37. Network Operating System - NOS (1) 1-19 General structure of a network operating system. Main features: Independent operating systems Services for accessing remote resources

  38. Network Operating System (2) 1-20 Two clients and a server in a network operating system.

  39. Network Operating System (3) 1.21 Different clients may mount the servers in different places.

  40. NOS vs DOS (3) Distributed operating system: Fully transparent For homogeneous systems  computers are not independent More secure, but less scalable and less open Network operating system: Not transparent For heterogeneous system  computers are independent Easier to extend (e.g. adding a new node in the Internet) Both do not really qualify as a distributed system!!!  Solution: Middleware atop of a NOS hiding heterogeneity and improving transparency

  41. Positioning Middleware 1-22 General structure of a distributed system as middleware. Middleware Services: rather a functionally complete set of services in order to hide heterogeneity, direct access to NOS is discouraged.

  42. Middleware and Openness 1.23 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.  implementations of the middleware should not use the NOS-provided protocols

  43. Comparison between Systems A comparison between multiprocessor operating systems, multicomputer operating systems, network operating systems, and middleware-based distributed systems.

  44. Clients and Servers 1.25 General interaction between a client and a server.

  45. An Example Client and Server (1) The header.h file used by the client and server.

  46. An Example Client and Server (2) A sample server.

  47. An Example Client and Server (3) 1-27 b A client using the server to copy a file.

  48. Processing Level 1-28 The general organization of an Internet search engine into three different layers

  49. Multitiered Architectures (1) 1-29 Alternative client-server organizations (a) – (e).

  50. Multitiered Architectures (2) 1-30 An example of a server acting as a client.

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