1. Introduction
Chapter 1

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. Definition of a Distributed System (2)
1.1
A distributed system organized as middleware. Note that the middleware layer extends over multiple machines.

4. Goals of a Distributed System
Accessibility: A distributed system should easily connect users to resources.
Groupware is software for collaborative editing, teleconferencing, and so on.
Transparency: It should hide the fact that resources are distributed across a network.
Openness: It should be open.
An open distributed system is a system that offers services according to standard rules that describe the syntax and semantics of those services.
Scalability: It should be scalable.

5. Transparency in a Distributed System
Description
Access
Hide differences in data representation and how a resource is accessed
Location
Hide where a resource is located
Migration
Hide that a resource may move to another location
Relocation
Hide that a resource may be moved to another location while in use
Replication
Hide that a resource may be shared by several competitive users
Concurrency
Failure
Hide the failure and recovery of a resource
Persistence
Hide whether a (software) resource is in memory or on disk
Different forms of transparency in a distributed system.

6. Openness Problems
In distributed systems, services are generally specified through interfaces, which are described in an Interface Definition Language (IDL).
Interoperability characterizes the extent by which two implementations of systems or components from different manufactures can co-exist and work together by merely relying on each other’s services as specified by a common standard.
Example: Mobile phones
Portability characterizes to what extent an application developed for a distributed system A can be executed, without modification, on a different system B that implements the same interface as A.
Example: Java
Flexibility means that it should be easy to configure the system out of different components possibly from different developers.

7. Scalability Problems
Scalability of a system can be measured in three dimensions:
Size
Geographically scalable
Administratively scalable

8. Examples of scalability limitations.
Scalability Problems
Concept
Example
Centralized services
A single server for all users
Centralized data
A single on-line telephone book
Centralized algorithms
Doing routing based on complete information
Examples of scalability limitations.

9. Scalability Problems
Decentralized algorithms have the following characteristics:
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.
There are basically three techniques for scaling: hiding communication latencies, distribution, and replication.

10. Scaling Techniques (1) 1.4 The difference between letting: a server or
a client check forms as they are being filled
Example: Java applets

11. An example of dividing the DNS name space into zones.
Scaling Techniques (2)
1.5
An example of dividing the DNS name space into zones.

12. Hardware Concepts
Computers that have shared memory are called multiprocessors.
Computers that do not have shared memory are called multicomputers.
Two types of interconnection network are used: bus and switched.
In multicomputers, a further distinction can be made between homogeneous and heterogeneous systems.
Examples of switched homogenous multicomputers:
Massively Parallel Processors (MPPs) are huge, multimillion dollar supercomputers consisting of thousands of CPUs.
Clusters of Workstations (COWs) are basically a collection of standard PCs connected through off-the-shelf communication components such as Myrinet boards.
Heterogenous multicomputers need distributed system as a software layer.

13. Hardware Concepts
1.6
Different basic organizations and memories in distributed computer systems: multiprocessors vs. multicomputers

14. Multiprocessors (bus-based)
1.7
A bus-based multiprocessor.
The problem: More CPUs will overload the bus.
The solution is to add a high-speed cache.
It causes the incoherent memory.
Limited scalability.

15. Multiprocessors (Switch-based)
1.8
A crossbar switch
An omega switching network

16. Homogeneous Multicomputer Systems
1-9
Grid
Hypercube

17. Software Concepts Distributed systems:
Act as resource managers.
Hide the intricacies and heterogeneous nature of the underlying hardware.
Distributed operating systems can be divided into two categories:
In tightly-coupled systems, the operating system tries to maintain a single, global view of the resources (e.g. DOS).
Loosely-coupled systems can be thought of as a collection of computers to make their own services and resources available to the others (e.g. NOS).

18. Software Concepts An overview between
System
Description
Main Goal
DOS
Tightly-coupled operating system for multi-processors and homogeneous multicomputers
Hide and manage hardware resources
NOS
Loosely-coupled operating system for heterogeneous multicomputers (LAN and WAN)
Offer local services to remote clients
Middleware
Additional layer atop of NOS implementing general-purpose services
Provide distribution transparency
An overview between
DOS (Distributed Operating Systems)
NOS (Network Operating Systems)
Middleware

19. Uniprocessor Operating Systems
The operating system is a virtual machine offering multitasking facilities to applications.
Applications are protected from each other.
Two modes of operation
In kernel mode, all instructions are permitted to be executed, and the whole memory and all registers are accessible.
In user mode, memory and register access is restricted.
Having all operating system code to be executed in kernel mode results in a monolithic operating system that is not a good idea from the perspective of openness, software engineering, reliability, or maintainability.
A flexible approach is to have a module for managing devices executed in user mode and a microkernel containing the code for hardware access.
Advantages: flexibility
Disadvantages: different from the current operating system and extra communication.

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

21. Multiprocessor Operating Systems
Multiprocessor Operating Systems aim to support high performance through multiple CPUs.
Protection against simultaneous data access is done through synchronization primitives: semaphores and monitors.
A semaphore can be thought of as an integer with two operations, down (wait) and up (signal).
down (S):
while S 0 do no-op; S--;
up (S):
S++;
Semaphore operations need to be atomic (once it starts, no other process can access it.)

22. Multiprocessor Operating Systems
The use of semaphores can easily lead to unstructed code.
A monitor is a programming-language construct.
A monitor is an object that allows only a single process at a time to execute a procedure.
A monitor can block a process based on condition variables.
Condition variables are special variables with two operations wait and signal.

23. 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.

24. 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.

25. Multicomputer Operating Systems
Communication for multicomputer operating systems is through message passing.
Each node has its own kernel containing separate modules for managing local resources and interprocessor communication.

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

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

28. Multicomputer Operating Systems (3)
Synchronization point
Send buffer
Reliable comm. guaranteed?
Block sender until buffer not full
Yes
Not necessary
Block sender until message sent No
Block sender until message received
Necessary
Block sender until message delivered
Relation between blocking, buffering, and reliable communications.

29. Distributed Shared Memory Systems
The goal is to provide a virtual shared memory machine, running on a multicomputer, for which applications can be written using the shared memory model even though this is not present.
A page­based distributed shared memory (DSM) is to use the virtual memory capabilities of each individual node to support a large virtual address space.
Having data belonging to two independent processes in the same page is called false sharing.
If a page contains data of two independent processes on different processors, the operating system may need to repeatedly transfer the page between those two processors.

30. 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

31. Distributed Shared Memory Systems (2)
1.18
False sharing of a page between two independent processes.

32. Network Operating System
In network operating system, the machines and their operating systems may be different, but they are all connected to each other in a computer network.
Services available in NOS are:
Remote login: rlogin
Remote copy: rcp machine1:file1 machine2:file2
File servers are used to provide a shared, global file system.
Different clients can have different a view of the file system based on different file mounting.

33. Network Operating System (1)
1-19
General structure of a network operating system.

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

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

36. Middleware
Middleware is an additional layer of software that is used in network operating systems to more or less hide the heterogeneity of the collection of underlying platforms but also to improve distribution transparency.
Middleware models:
File: Everything is treated as a file.
Distributed file systems: Only traditional files are concerned.
Remote Procedure Calls (RPCs): A process can call a procedure located on a remote machine like a local call.
Distributed objects: Objects are invoked through the interface.
Distributed documents: Information is orgainzed into documents (WWW).

37. Positioning Middleware
1-22
General structure of a distributed system as middleware.

38. Middleware Middleware services:
Communication facilities
Naming
Persistence storage
Distributed transactions
Security
Middleware interoperability can be only achieved by the same protocols and interfaces.

39. 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.

40. Comparison between Systems
Item
Distributed OS
Network OS
Middleware-based OS
Multiproc.
Multicomp.
Degree of transparency
Very High
High
Low
Same OS on all nodes
Yes No
Number of copies of OS 1 N
Basis for communication
Shared memory
Messages
Files
Model specific
Resource management
Global, central
Global, distributed
Per node
Scalability
Moderately
Varies
Openness
Closed
Open
A comparison between multiprocessor operating systems, multicomputer operating systems, network operating systems, and middleware based distributed systems.

41. The Client-Server Model
In the basic client-server model, processes are divided into two groups:
A server is a process implementing a specific service.
A client is a process that requests a service from a server.
The client-server interaction is known as request-reply behavior.
Communication between a client and a server can be implemented by means of a simple connectionless protocol based on the hypothesis that the underlying network is reliable.
Many client-server systems use a reliable connection-oriented protocol.

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

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

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

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

46. Layering Client-Server Model
Client-server applications can be made distinct among the following three levels:
The user-interface level: the programs that allow end users to interact with applications.
The processing level: the core functions of applications.
The data level: the programs that maintain the actual data.

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

48. Client-Server Architectures
Multitiered Architecture is to distribute the programs in the application layers across different machines.
Two-tieried architecture distribute programs to two kinds of machines: clients and servers.
Three-tired architecture divides applications into a user-interface, process components, and a data level.
This type of distribution is referred as vertical distribution.

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.

51. Client-Server Architectures
In horizontal distribution, multiple clients or servers, each of which has its own data set, work together to share the load.
Example: Multiple Web servers
For simple collaborative applications, there could be no server but only peer-to-peer distribution.

52. An example of horizontal distribution of a Web service.
Modern Architectures
1-31
An example of horizontal distribution of a Web service.