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Distributed Systems
Tanenbaum Chapter 1

Outline
• Definition of a Distributed System
• Goals of a Distributed System

What Is A Distributed System?
• A collection of independent computers that
appears to its users as a single coherent system.
• Features:
– No shared memory – message-based communication
– Each runs its own local OS
– Heterogeneity
• Ideal: to present a single-system image:
– The distributed system “looks like” a single
computer rather than a collection of separate
computers.

Distributed System
Characteristics
• To present a single-system image:
– Hide internal organization, communication details
– Provide uniform interface
• Easily expandable
– Adding new computers is hidden from users
• Continuous availability
– Failures in one component can be covered by other
components
• Supported by middleware

Definition of a Distributed System
Figure 1-1. A distributed system organized as middleware. The
middleware layer runs on all machines, and offers a uniform
interface to the system

Role of Middleware (MW)
• In some early research systems: MW tried to
provide the illusion that a collection of separate
machines was a single computer.
– E.g. NOW project: GLUNIX middleware
• Today:
– clustering software allows independent computers to
work together closely
– MW also supports seamless access to remote
services, doesn’t try to look like a general-purpose
OS

Middleware Examples
• CORBA (Common Object Request Broker
Architecture)
• DCOM (Distributed Component Object
Management) – being replaced by .net
• Sun’s ONC RPC (Remote Procedure Call)
• RMI (Remote Method Invocation)
• SOAP (Simple Object Access Protocol)

Middleware Examples
• All of the previous examples support
communication across a network:
• They provide protocols that allow a program
running on one kind of computer, using one
kind of operating system, to call a program
running on another computer with a
different operating system
– The communicating programs must be running
the same middleware.

Distributed System Goals
• Resource Accessibility
• Distribution Transparency
• Openness
• Scalability

Goal 1 – Resource Availability
• Support user access to remote resources (printers,
data files, web pages, CPU cycles) and the fair
sharing of the resources
• Economics of sharing expensive resources
• Performance enhancement – due to multiple
processors; also due to ease of collaboration and
info exchange – access to remote services
– Groupware: tools to support collaboration
• Resource sharing introduces security problems.

Goal 2 – Distribution Transparency
• Software hides some of the details of the
distribution of system resources.
– Makes the system more user friendly.
• A distributed system that appears to its users &
applications to be a single computer system is said
to be transparent.
– Users & apps should be able to access remote
resources in the same way they access local
resources.
• Transparency has several dimensions.

Types of Transparency
Transparency Description
Access Hide differences in data representation &
resource access (enables interoperability)
Location Hide location of resource (can use resource
without knowing its location)
Migration Hide possibility that a system may change
location of resource (no effect on access)
Replication Hide the possibility that multiple copies of the
resource exist (for reliability and/or
availability)
Concurrency Hide the possibility that the resource may be
shared concurrently
Failure Hide failure and recovery of the resource.
How does one differentiate betw. slow and
failed?
Relocation Hide that resource may be moved during use
Figure 1-2. Different forms of transparency in a distributed system
(ISO, 1995)

Goal 2: Degrees of Transparency
• Trade-off: transparency versus other factors
– Reduced performance: multiple attempts to
contact a remote server can slow down the
system – should you report failure and let user
cancel request?
– Convenience: direct the print request to my
local printer, not one on the next floor
• Too much emphasis on transparency may prevent
the user from understanding system behavior.

Goal 3 - Openness
• An open distributed system “…offers services according to
standard rules that describe the syntax and semantics of those
services.” In other words, the interfaces to the system are
clearly specified and freely available.
– Compare to network protocols
– Not proprietary
• Interface Definition/Description Languages (IDL): used to
describe the interfaces between software components, usually
in a distributed system
– Definitions are language & machine independent
– Support communication between systems using different
OS/programming languages; e.g. a C++ program running on Windows
communicates with a Java program running on UNIX
– Communication is usually RPC-based.

Examples of IDLs
Goal 3-Openness
• IDL: Interface Description Language
– The original
• WSDL: Web Services Description Language
– Provides machine-readable descriptions of the
services
• OMG IDL: used for RPC in CORBA
– OMG – Object Management Group
• …

• Interoperability: the ability of two different
systems or applications to work together
– A process that needs a service should be able to
talk to any process that provides the service.
– Multiple implementations of the same service
may be provided, as long as the interface is
maintained
• Portability: an application designed to run
on one distributed system can run on another
system which implements the same interface.
• Extensibility: Easy to add new components,
features
Open Systems Support …

Goal 4 - Scalability
• Dimensions that may scale:
– With respect to size
– With respect to geographical distribution
– With respect to the number of administrative
organizations spanned
• A scalable system still performs well as it
scales up along any of the three dimensions.

Size Scalability
• Scalability is negatively affected when the system is
based on
– Centralized server: one for all users
– Centralized data: a single data base for all users
– Centralized algorithms: one site collects all information,
processes it, distributes the results to all sites.
• Complete knowledge: good
• Time and network traffic: bad

Decentralized Algorithms
• No machine has complete information
about the system state
• Machines make decisions based only on
local information
• Failure of a single machine doesn’t ruin the
algorithm
• There is no assumption that a global clock
exists.

Geographic Scalability
• Early distributed systems ran on LANs, relied on
synchronous communication.
– May be too slow for wide-area networks
– Wide-area communication is unreliable, point-to-point;
– Unpredictable time delays may even affect correctness
• LAN communication is based on broadcast.
– Consider how this affects an attempt to locate a
particular kind of service
• Centralized components + wide-area
communication: waste of network bandwidth

Scalability - Administrative
• Different domains may have different
policies about resource usage, management,
security, etc.
• Trust often stops at administrative
boundaries
– Requires protection from malicious attacks

Scaling Techniques
• Scalability affects performance more than
anything else.
• Three techniques to improve scalability:
– Hiding communication latencies
– Distribution
– Replication

Hiding Communication Delays
• Structure applications to use asynchronous
communication (no blocking for replies)
– While waiting for one answer, do something else; e.g.,
create one thread to wait for the reply and let other
threads continue to process or schedule another task
• Download part of the computation to the
requesting platform to speed up processing
– Filling in forms to access a DB: send a separate
message for each field, or download form/code and
submit finished version.
– i.e., shorten the wait times

Scaling Techniques
Figure 1-4. The difference between letting (a) a server
or (b) a client check forms as they are being filled.

Distribution
• Instead of one centralized service, divide
into parts and distribute geographically
• Each part handles one aspect of the job
– Example: DNS namespace is organized as a
tree of domains; each domain is divided into
zones; names in each zone are handled by a
different name server
– WWW consists of many (millions?) of servers

Scaling Techniques (2)
Figure 1-5. An example of dividing the DNS
name space into zones.

Third Scaling Technique -
Replication
• Replication: multiple identical copies of
something
– Replicated objects may also be distributed, but
aren’t necessarily.
• Replication
– Increases availability
– Improves performance through load balancing
– May avoid latency by improving proximity of
resource

Caching
• Caching is a form of replication
– Normally creates a (temporary) replica of
something closer to the user
• Replication is often more permanent
• User (client system) decides to cache,
server system decides to replicate
• Both lead to consistency problems

Summary
Goals for Distribution
• Resource accessibility
– For sharing and enhanced performance
• Distribution transparency
– For easier use
• Openness
– To support interoperability, portability, extensibility
• Scalability
– With respect to size (number of users), geographic
distribution, administrative domains

Issues/Pitfalls of Distribution
• Requirement for advanced software to realize the
potential benefits.
• Security and privacy concerns regarding network
communication
• Replication of data and services provides fault
tolerance and availability, but at a cost.
• Network reliability, security, heterogeneity,
topology
• Latency and bandwidth
• Administrative domains

Distributed Systems
• Early distributed systems emphasized the
single system image – often tried to make a
networked set of computers look like an
ordinary general purpose computer
• Examples: Amoeba, Sprite, NOW, Condor
(distributed batch system), …

Distributed systems run distributed
applications, from file sharing to large scale
projects like SETI@Home
http://setiathome.ssl.berkeley.edu/

Additional �ݺ�ߣs
• Middleware: CORBA, ONC RPC, SOAP

CORBA
• “CORBA is the acronym for Common Object
Request Broker Architecture, OMG's open,
vendor-independent architecture and infrastructure
that computer applications use to work together
over networks. Using the standard protocol IIOP,
a CORBA-based program from any vendor, on
almost any computer, operating system,
programming language, and network, can
interoperate with a CORBA-based program from
the same or another vendor, on almost any other
computer, operating system, programming
language, and network.”
http://www.omg.org/gettingstarted/corbafaq.htm

ONC RPC
• “ONC RPC, short for Open Network
Computing Remote Procedure Call, is a
widely deployed remote procedure call
system. ONC was originally developed by
Sun Microsystems as part of their Network
File System project, and is sometimes
referred to as Sun ONC or Sun RPC.”
http://en.wikipedia.org/wiki/Open_Network_Computing_Remote_Procedure_Call

Simple Object Access Protocol
• SOAP is a lightweight protocol for exchange of
information in a decentralized, distributed environment. It
is an XML based protocol that consists of three parts: an
envelope that defines a framework for describing what is
in a message and how to process it, a set of encoding rules
for expressing instances of application-defined datatypes,
and a convention for representing remote procedure calls
and responses. SOAP can potentially be used in
combination with a variety of other protocols; however,
the only bindings defined in this document describe how to
use SOAP in combination with HTTP and HTTP
Extension Framework.
• http://www.w3.org/TR/2000/NOTE-SOAP-20000508/

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