1. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 1 DISTRIBUTED SYSTEMS Principles and Paradigms Second Edition ANDREW S. TANENBAUM MAARTEN VAN STEEN Chapter 1 Introduction

2. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 2 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.

3. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 3 Definition of a Distributed System (2) Figure 1-1. A distributed system organized as middleware. The middleware layer extends over multiple machines, and offers each application the same interface.

4. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 4 Transparency in a Distributed System Figure 1-2. Different forms of transparency in a distributed system (ISO, 1995).

5. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 5 Scalability Problems Figure 1-3. Examples of scalability limitations.

6. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 6 Scalability Problems Scalability can be measure along 3 dimensions: Size scalable: easily add more users & recourses to the system Geographically scalable: users & resources may lie far apart Administratively scalable: it can still be easy to manage even if it spans independent administrative organizations

7. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 7 Scalability Problems Characteristics of decentralized algorithms: No machine has complete information about the system state. Machines make decisions based only on local information. Failure of one machine does not ruin the algorithm. There is no implicit assumption that a global clock exists.

8. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 8 Scaling Techniques (1) Figure 1-4. The difference between letting (a) a server or (b) a client check forms as they are being filled.

9. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 9 Scaling Techniques (2) Figure 1-5. An example of dividing the DNS name space into zones.

10. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 10 Pitfalls when Developing Distributed Systems False assumptions made by first time developer: The network is reliable. The network is secure. The network is homogeneous. The topology does not change. Latency is zero. Bandwidth is infinite. Transport cost is zero. There is one administrator.

11. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 11 Types of Distributed Systems: 1.Distributed Computing Systems –Cluster Computing Systems –Grid Computing Systems 2.Distributed Information Systems –Transaction Processing Systems –Enterprise Application Integration (Exchange info via RPC or RMI) 3.Distributed Pervasive Systems (usually small, battery- powered systems, Mobile & wireless) –Home Systems (e.g. Smart phones, PDAs) –Electronic Health care systems (Heart monitors, BAN: Body Area Networks) –Sensor Networks (distributed Databases connected wirelessly)

12. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 12 Cluster Computing Systems –Hooking up a collection of simple computers via high-speed networks to build a supercomputing environment –Mostly homogenous –Example: server clusters at Banks, Brokerages, etc.

13. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 13 Cluster Computing Systems Figure 1-6. An example of a cluster computing system.

14. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 14 Grid Computing Systems –In contrast to cluster computing, grid computing systems have a high degree of heterogeneity, no assumption are made concerning hardware, OS, Networks, Security, … –Users and recourses from different organizations are brought together to allow collaboration (i.e. a V.O. = Virtual Organization) –Members belonging to the same V.O. have access rights to a common set of recourses (e.g. Police, FBI, and some local agencies may form a computing grid)

15. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 15 Grid Computing Systems Figure 1-7. A layered architecture for grid computing systems. Grid Middleware Applications operate within a virtual organization and make use of grid computing environment

16. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 16 Grid Computing Layers: 1.Collective layer: access to multiple resources and typically consists of services for resource discovery, allocation and scheduling. 2.Connectivity layer: transfer data between resources or access a resource from a remote location 3.Resource layer: managing a single recourse such as creating a process or reading data 4.Fabric layer: provides interface to local resources at a specific site within a V.O.

17. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 17 Transaction Processing Systems (1) Figure 1-8. Example primitives for transactions.

18. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 18 Transaction Processing Systems (2) Characteristic properties of transactions: Atomic: To the outside world, the transaction happens indivisibly. Consistent: The transaction does not violate system invariants. Isolated: Concurrent transactions do not interfere with each other. Durable: Once a transaction commits, the changes are permanent.

19. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 19 Transaction Processing Systems (3) Figure 1-9. A nested transaction.

20. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 20 Transaction Processing Systems (4) Figure 1-10. The role of a TP monitor in distributed systems.

21. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 21 Enterprise Application Integration Figure 1-11. Middleware as a communication facilitator in enterprise application integration.

22. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 22 Enterprise Application Integration Various middleware packages and communication protocols are used in support of Enterprise applications such as: CORBA ( Common Object Request Broker Architecture ) DCOM ( Distributed Component Object Management ) RPC ( Remote Procedure Call ) RMI ( Remote Method Invocation )

23. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 23 Distributed Pervasive Systems Requirements for pervasive systems: Embrace contextual changes (i.e. I was a phone now I am a web access device. A device must continuously be aware of the fact that its environment may change) Encourage ad hoc composition (used differently by different users, e.g. PDA) Recognize sharing as the default (easily read, store, manage, and share info)

24. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 24 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?

25. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 25 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.

26. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 26 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?

27. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 27 Sensor Networks (2) Figure 1-13. Organizing a sensor network database, while storing and processing data (a) only at the operator’s site or …

28. Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved. 0-13-239227-5 28 Sensor Networks (3) Figure 1-13. Organizing a sensor network database, while storing and processing data … or (b) only at the sensors.