Unit 2 Distributed Systems R.Yamini Dept. Of CA, SRM University Kattankulathur

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1 Unit 2 Distributed Systems R.Yamini Dept. Of CA, SRM University Kattankulathur 1

2 Introduction to Distributed Systems Why do we develop distributed systems? availability of powerful yet cheap microprocessors (PCs, workstations), continuing advances in communication technology, What is a distributed system? A distributed system is a collection of independent computers that appear to the users of the system as a single system. Examples: Network of workstations Distributed manufacturing system (e.g., automated assembly line) Network of branch office computers 2

3 Advantages of Distributed Systems over Centralized Systems Economics: a collection of microprocessors offer a better price/performance than mainframes. Low price/performance ratio: cost effective way to increase computing power. Speed: a distributed system may have more total computing power than a mainframe. Ex. 10,000 CPU chips, each running at 50 MIPS. Not possible to build 500,000 MIPS single processor since it would require nsec instruction cycle. Enhanced performance through load distributing. Inherent distribution: Some applications are inherently distributed. Ex. a supermarket chain. Reliability: If one machine crashes, the system as a whole can still survive. Higher availability and improved reliability. Incremental growth: Computing power can be added in small increments. Modular expandability Another deriving force: the existence of large number of personal computers, the need for people to collaborate and share information. 3

10,000 CPU chips, each running at 50 MIPS. Not possible to build 500,000 MIPS single processor since it would require 0.002 nsec instruction cycle. Enhanced performance through load distributing.

4 Advantages of Distributed Systems over Independent PCs Data sharing: allow many users to access to a common data base Resource Sharing: expensive peripherals like color printers Communication: enhance human to human communication, e.g., , chat Flexibility: spread the workload over the available machines 4

peripherals like color printers Communication: enhance human to human

5 Disadvantages of Distributed Systems Software: difficult to develop software for distributed systems Network: saturation, lossy transmissions Security: easy access also applies to secrete data 5

systems Network: saturation, lossy transmissions

6 Hardware Concepts Taxonomy (Fig. 9 4) MIMD (Multiple Instruction Multiple Data) Tightly Coupled versus Loosely Coupled Tightly coupled systems (multiprocessors) o shared memory o intermachine delay short, data rate high Loosely coupled systems (multicomputers) o private memory o intermachine delay long, data rate low 6

Coupled Tightly coupled systems (multiprocessors) o shared memory o

7 Bus versus Switched MIMD Bus: a single network, backplane, bus, cable or other medium that connects all machines. E.g., cable TV Switched: individual wires from machine to machine, with many different wiring patterns in use. Multiprocessors (shared memory) Bus Switched Multicomputers (private memory) Bus Switched 7

, cable TV Switched: individual wires from machine to machine, with many

8 Switched Multiprocessors Switched Multiprocessors (Fig. 9 6) for connecting large number (say over 64) of processors crossbar switch: n**2 switch points omega network: 2x2 switches for n CPUs and n memories, log n switching stages, each with n/2 switches, total (n log n)/2 switches delay problem: E.g., n=1024, 10 switching stages from CPU to memory. a total of 20 switching stages. 100 MIPS 10 nsec instruction execution time need 0.5 nsec switching time NUMA (Non Uniform Memory Access): placement of program and data building a large, tightly coupled, shared memory multiprocessor is possible, but is difficult and expensive 9

switching stages, each with n/2 switches, total (n log n)/2 switches delay problem: E.g., n=1024, 10 switching stages from CPU to memory.

9 Multicomputers Bus Based Multicomputers (Fig. 9 7) easy to build communication volume much smaller relatively slow speed LAN ( MIPS, compared to 300 MIPS and up for a backplane bus) Switched Multicomputers (Fig. 9 8) interconnection networks: E.g., grid, hypercube hypercube: n dimensional cube 10

LAN (10 100 MIPS, compared to 300 MIPS and up for a backplane bus) Switched

10 Software Concepts Software more important for users Three types: 1. Network Operating Systems 2. (True) Distributed Systems 3. Multiprocessor Time Sharing 11

11 Network Operating Systems loosely coupled software on loosely coupled hardware A network of workstations connected by LAN each machine has a high degree of autonomy o rlogin machine o rcp machine1:file1 machine2:file2 Files servers: client and server model Clients mount directories on file servers Best known network OS: o Sun s NFS (network file servers) for shared file systems (Fig. 9 11) a few system wide requirements: format and meaning of all the messages exchanged 12

client and server model Clients mount directories on file servers Best known network OS: o Sun s NFS (network file

12 NFS NFS Architecture Server exports directories Clients mount exported directories NSF Protocols For handling mounting For read/write: no open/close, stateless NSF Implementation 13

13 (True) Distributed Systems tightly coupled software on loosely coupled hardware provide a single system image or a virtual uniprocessor a single, global interprocess communication mechanism, process management, file system; the same system call interface everywhere Ideal definition: A distributed system runs on a collection of computers that do not have shared memory, yet looks like a single computer to its users. 14

management, file system; the same system call interface everywhere Ideal definition: A distributed

14 Multiprocessor Operating Systems (Fig. 9 12) Tightly coupled software on tightly coupled hardware Examples: high performance servers shared memory single run queue traditional file system as on a single processor system: central block cache Fig for comparisons 15

Examples: high performance servers shared memory single run queue

15 Design Issues of Distributed Systems Transparency Flexibility Reliability Performance Scalability 16

16 1. Transparency How to achieve the single system image, i.e., how to make a collection of computers appear as a single computer. Hiding all the distribution from the users as well as the application programs can be achieved at two levels: 1) hide the distribution from users 2) at a lower level, make the system look transparent to programs. 1) and 2) requires uniform interfaces such as access to files, communication. 17

levels: 1) hide the distribution from users 2) at a lower level, make the system look transparent to

17 Types of transparency Location Transparency: users cannot tell where hardware and software resources such as CPUs, printers, files, data bases are located. Migration Transparency: resources must be free to move from one location to another without their names changed. E.g., /usr/lee, /central/usr/lee Replication Transparency: OS can make additional copies of files and resources without users noticing. Concurrency Transparency: The users are not aware of the existence of other users. Need to allow multiple users to concurrently access the same resource. Lock and unlock for mutual exclusion. Parallelism Transparency: Automatic use of parallelism without having to program explicitly. The holy grail for distributed and parallel system designers. Users do not always want complete transparency: a fancy printer 1000 miles away 18

Concurrency Transparency: The users are not aware of the existence of other users. Need to allow multiple users to concurrently access the same resource. Lock and unlock for mutual exclusion.

18 2. Flexibility Make it easier to change Monolithic Kernel: systems calls are trapped and executed by the kernel. All system calls are served by the kernel, e.g., UNIX. Microkernel: provides minimal services. (Fig 9 15) 1) IPC 2) some memory management 3) some low level process management and scheduling 4) low level i/o E.g., Mach can support multiple file systems, multiple system interfaces. 19

19 3. Reliability Distributed system should be more reliable than single system. Example: 3 machines with.95 probability of being up. 1.05**3 probability of being up. Availability: fraction of time the system is usable. Redundancy improves it. Need to maintain consistency Need to be secure Fault tolerance: need to mask failures, recover from errors. 20

$Availability: fraction of time the system is usable. Redundancy improves it.$

20 4. Performance Without gain on this, why bother with distributed systems. Performance loss due to communication delays: fine grain parallelism: high degree of interaction coarse grain parallelism Performance loss due to making the system fault tolerant. 21

21 5. Scalability Systems grow with time or become obsolete. Techniques that require resources linearly in terms of the size of the system are not scalable. e.g., broadcast based query won't work for large distributed systems. Examples of bottlenecks o Centralized components: a single mail server o Centralized tables: a single URL address book o Centralized algorithms: routing based on complete information 22

Virtual machine interface. Operating system. Physical machine interface

Virtual machine interface. Operating system. Physical machine interface Software Concepts User applications Operating system Hardware Virtual machine interface Physical machine interface Operating system: Interface between users and hardware Implements a virtual machine that