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University of Pennsylvania

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Introduction to Distributed Systems

Why do we develop distributed systems?

Availability of powerful yet cheap microprocessors (PCs,workstations), continuing advances in communicationtechnology,

What is a distributed system?A distributed system is a collection of independent computers thatappear to the users of the system as a single system.

Examples:

Network of workstations

Distributed manufacturing system (e.g., automated assemblyline)

Network of branch office computers


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Advantages of Distributed Systemsover Centralized Systems

Economics: A collection of microprocessors offer a betterprice/performance than mainframes. Low price/performance ratio:cost effective way to increase computing power.

Speed: A distributed system may have more total computing powerthan 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 0.002 nsec instruction cycle. Enhanced performance throughload distributing.

Inherent distribution: Some applications are inherentlydistributed. 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 personalcomputers, the need for people to collaborate and share information.


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Advantages of Distributed Systemsover Independent PCs

Data sharing: Allow many users to access to acommon data base

Resource Sharing: Expensive peripherals like color

printers

Communication: Enhance human-to-humancommunication, e.g., email, chat

Flexibility: Spread the workload over the available

machines


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Disadvantages of Distributed Systems

Software: Difficult to develop software fordistributed systems

Network: The network can saturate or

cause other problems Security: Easy access also applies to

secrete data


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Hardware Concepts

All distributed systems consist of multiple CPUs, there are several differentways the hardware can be organized interms of how they are interconnectedand how they communicate.

Flynn picked two characterstics they are the number of instructions streamand the number of data streams.

A computer with a Single instruction and single data stream is called SISD.All traditional uniprocessor computers.

The next category is SIMD, single instruction stream, multiple data stream.This type refers to array processors with one instruction unit that fetches aninstruction, and then commands many data units to carry it out in parallel, each

with its own data. Some supercomputers are SIMD.The next category is MISD, multiple instruction stream, single data stream.No known computers fit this mode.

Next comes MIMD, we find multiple instruction stream, multiple data stream.Which essentially means a group of independent computers, each with its ownprogram counter, program, and data. All distributed systems are MIMD.


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Hardware Concepts

ATaxonomy of parallel and distributed computer systems.


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MIMD (Multiple-InstructionMultiple-Data)

Tightly Coupled versus Loosely Coupled

y Tightly coupled systems (multiprocessors)

o shared memory

o intermachine delay short, data rate high

y Loosely coupled systems (multicomputers)

o private memory

o intermachine delay long, data rate low

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Bus versus Switched MIMD

Bus: a single network, backplane, bus, cable or other mediumthat connects all machines. E.g., cable TV

Switched: individual wires from machine to machine, withmany different wiring patterns in use.

Multiprocessors (shared memory) Bus

Switched

Multicomputers (private memory)

Bus Switched


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Bus-based Multiprocessors

Bus-based multiprocessors

y cache memory

y hit rate

y cache coherence

y write-through cache: propagate write immediately

y snoopy cache: monitor when its entry becomes obsolete


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Switched Multiprocessors

A crossbar switch An Omega switching network


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Switched Multiprocessorsy for connecting large number (say over 64) of processorsy crossbar switch: n**2 switch pointsy omega network: 2x2 switches for n CPUs and n memories,

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

CPU to memory. a total of 20 switching stages. 100MIPS 10nsec instruction execution time need 0.5 nsecswitching time

y

NUMA

(Non-Uniform MemoryA

ccess): placement ofprogram and datay building a large, tightly-coupled, shared memory

multiprocessor is possible, but is difficult and expensive


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Multicomputers

y easy to buildy communication volume much smallery relatively slow speed LAN (10-100MIPS, compared to

300MIPS and up for a backplane bus)

Bus-Based Multicomputers

AMulticomputer consisting of workstations on a LAN


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y interconnectionnetworks: E.g., grid, hypercubey hypercube: n-dimensional cube

Switched Multicomputers


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Software Concepts

Software more important for users

Three types:

1. Network Operating Systems

2. (True) Distributed Systems

3.Multiprocessor Time Sharing


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Network Operating Systems

y loosely-coupled software on loosely-coupled hardwarey Anetwork of workstations connected by LAN

y each machine has a high degree of autonomy

o rlogin machine

o rcp machine1:file1 machine2:file2

y Files servers: client and server model

y Clients mount directories on file servers

y Best knownnetwork OS:

o Suns NFS (network file servers) for shared file

systemsy a few system-wide requirements: format and meaning of

all the messages exchanged


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NFS

NFS Architecture

Server exports directories

Clients mount exported directories

NSF Protocols

For handling mounting

For read/write: no open/close, stateless

NSF Implementation


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(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 callinterface everywhere

Ideal definition:

A distributed system runs on a collection ofcomputers that do not have shared memory, yet looks

like a single computer to its users.


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Multiprocessor Operating Systems

Tightly-coupled software on tightly-coupled hardware

y

Examples: high-performance serversy shared memory

y single run queue

y traditional file system as on a single-processor system: centralblock cache


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DesignIssues of Distributed Systems

Transparency

Flexibility

Reliability

Performance

Scalability


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1. Transparency

How to achieve the single-system image, i.e., how to make acollection of computers appear as a single computer.

Hiding all the distribution from the users as well as theapplication programs can be achieved at two levels:

1) hide the distribution from users

2) at a lower level, make the system look transparent toprograms.

1) and 2) requires uniform interfaces such as access tofiles, communication.


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Types of transparency

Location Transparency: users cannot tell where hardware andsoftware resources such as CPUs, printers, files, data bases arelocated.

Migration Transparency: resources must be free to move fromone location to another without their names changed.E.g.,/usr/lee,/central/usr/lee

Replication Transparency: OS can make additional copies offiles and resources without users noticing.

Concurrency Transparency: The users are not aware of theexistence of other users. Need to allow multiple users toconcurrently access the same resource. Lock and unlock formutual exclusion.

Parallelism Transparency: Automatic use of parallelism withouthaving to program explicitly. The holy grail for distributed andparallel system designers.

Users do not always want complete transparency: a fancy printer1000 miles away


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2. Flexibility

Make it easier to change

Monolithic Kernel: systems calls are trapped and executed by the kernel. Allsystem calls are served by the kernel, e.g., UNIX.

Microkernel: provides minimal services. Shown in above Fig.1) IPC2) some memory management3) some low-level process management and scheduling4) low-level i/o

E.g.,Mach can support multiple file systems, multiple system interfaces.


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3. Reliability

Distributed system should be more reliable than singlesystem. Example: 3 machines with .95 probability of beingup. 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 fromerrors.


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5. Scalability

Systems grow with time or become obsolete.Techniques that require resources linearly interms 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 completeinformation


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Communication Networks

Computers are connected through a communicationnetwork

Wide Area Networks (WAN)connect computers spread over a wide geographic areapoint-to-point or store-and-forward -- data is

transferred betwee

ncomputers through a series ofswitches

switch -- a special purpose computer responsible forrouting data (to avoid network congestion)data can be lost due to: switch crashes, communicationlink failures, limited buffers at switches, transmission

errors, etc.


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