Intro ds 1

1
Introduction to
Distributed Systems (DS)
INF5040/9040 autumn 2011
Frank Eliassen, Ifi/UiO 1
lecturer: Frank Eliassen
Outline
What is a distributed system?
What is a distributed system?
Challenges and benefits of distributed
system
Distribution transparencies
Pitfalls when developing distributed
Pitfalls when developing distributed
systems
Types of distributed systems

2
What is a distributed system?
Many definitions
 [Coulouris]
 A distributed system is one in which hardware or software
y
components located at networked computers communicate and
coordinate their actions only by passing messages.
 [Tanenbaum & van Steen]
 A distributed system is a collection of independent computers
that appears to its users as a single coherent system.
 [Lamport]
 A distributed system is a system that prevents you from doing
any work when a computer you have never heard about, fails.
y p y ,
 The above definitions take different perspectives
 Operational perspective
 User perspective
 DS characteristcs perspective
Implications of distributed systems
 Concurrency
– components execute in concurrent processes that read and update
shared resources Requires coordination
shared resources. Requires coordination
 No global clock
– makes coordination difficult (ordering of events)
 Independent failure of components
– “partial failure” & incomplete information
 Unreliable communication
– Loss of connection and messages. Message bit errors
 Unsecure communication
U secu e co u ca o
– Possibility of unauthorised recording and modification of messages
 Expensive communication
– Communication between computers usually has less bandwidth, longer
latency, and costs more, than between independent processes on the
same computer

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Goals of
distributed systems
 resource sharing
the possibility of using available resources any where
– the possibility of using available resources any where
 openness
– an open distributed system can be extended and improved
incrementally
– requires publication of component interfaces and standards
protocols for accessing interfaces
 scalability
– the ability to serve more users, provide acceptable response
y p p p
times with increased amount of data
 fault tolerance
– maintain availability even when individual components fail
 allow heterogeneity
– network and hardware, operating system, programming
languages, implementations by different developers
Examples of distributed
systems
Web search
Web search
 Index the entire contents of the Web.
Massively multiplayer online games
 Very large number of users sharing a virtual
world.
Financial trading
 Real time access and process of a wide rage
of information sources.

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A distributed system organized as
middleware
 Layer of software offering a single-system view
 Offers portability and interoperability
 Offers portability and interoperability
 Simplifies development of distributed applications
and services
Distributed
applications
and services
DISTRIBUTION MIDDEWARE
Platform Independent API
Platform Dependent API
. . .
Local OS
1
Local OS
2
Local OS
n
- transaction oriented (ODTP XA)
- message oriented(IBM MQSeries)
- remote procedure call (X/Open DCE)
- object-based (CORBA, COM, Java)
Resource sharing
 The opportunity to use available hardware,
pp y ,
software or data anywhere in the system
 Resource managers control access, offer a
scheme for naming, and controls concurrency
 A service is a software module that manages a
collection of related resources and presents their
functionality to users
functionality to users.
 A resource sharing model describes how
 resources are made available
 resources can be used
 service provider and user interact with each other

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Models for resource sharing
 Client-server resource model
 Server processes act as resource managers, and offer services
(collection of procedures)
 Client processes send requests to servers
 (HTTP defines a client-server resource model)
 Object-based resource model
 Any entity in a process is modeled as an object with a message
based interface that provides access to its operations
 Any shared resource is modeled as an object
 Object based middlewares (CORBA, Java RMI) defines object-
based resource models
Scalability
 A system is scalable if it remains effective when there is
y
a significant increase in the amount of resources (data)
and number of users
 Internet: number of users and services has grown enormously
 Scalability denotes the ability of a system to handle an
increasing future load
 Requirements of scalability often leads to a distributed
 Requirements of scalability often leads to a distributed
system architecture (several computers)

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Scalability problems (1)
Often caused by centralized solutions
Scalability problems (2)
Characteristics of decentralized algorithms:
 No machine has complete information about
 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
algo ithm
algorithm.
 There is no implicit assumption that a global
clock exists.

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Scaling techniques
 Distribution
 splitting a resource (such as data) into smaller parts,
p g ( ) p ,
and spreading the parts across the system (cf DNS)
 Replication
 replicate resources (services, data) across the system
 increases availability, helps to balance load
 caching (special form of replication)
 Hiding communication latencies
 Hiding communication latencies
 avoid waiting for responses to remote service requests
(use asynchronous communication or design to reduce
the amount of remote requests)
Failure handling
 Hardware, software and network fail!!
 DS must maintain availability even in cases where
hardware/software/network have low reliability
 Failures in distributed systems are partial
 makes error handling particularly difficult
 Many techniques for handling failures
 Detecting failures (checksum a.o.)
M ki f il ( i i i l )
 Masking failures (retransmission in protocols)
 Tolerating failures (as in web-browsers)
 Recovery from failures (roll back)
 Redundancy (replicate servers in failure-independent ways)

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Example: Google File-System
Early days…
…today
Challenges:
- Scalability
- Reliability
- Performance
Performance
- Openness
Distribution transparency
An important goal of a distributed system
An important goal of a distributed system
is to hide the fact that its processes and
resources are physically distributed across
multiple computers
A distributed system that is able to present
lf d l f
itself to its users and applications as if it
were only a single computer system is said
to be transparent

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Transparency in a distributed
system
Different forms of transparency in a distributed system (ISO, 1995).
Trade-off between degree of transparency and performance of a system
Pitfalls when Developing
Distributed Systems
False assumptions made by first time
p y
developer:
 The network is reliable.
 The network is secure.
 The network is homogeneous.
 The topology does not change.
L t i
 Latency is zero.
 Bandwidth is infinite.
 Transport cost is zero.
 There is one administrator.

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Quality of Service (QoS)
Nonfunctional properties of the system:
Nonfunctional properties of the system:
 Reliability
 Security
 Performance (Responsiveness and
throughput)
Adaptability to meet changes is an
important aspect of QoS
Types of distributed system
 Distributed Computing Systems
 Used for high performance computing tasks
Used for high performance computing tasks
 Cluster and Cloud computing systems
 Grid computing systems
 Distributed Information Systems
 Systems mainly for management and integration of
business functions
 Transaction processing systems
 Enterprise Application Integration
 Distributed Pervasive (or Ubiquitous) Systems
 Mobile and embedded systems
 Home systems
 Sensor networks

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Cluster Computing Systems
Collection of similar PCs, closely connected, all run same OS
An example of a cluster computing system.
Grid Computing Systems
Federation of autonomous and heterogeneous
computer systems (HW OS ) several adm domains
computer systems (HW,OS,...), several adm domains
A layered architecture for grid computing systems.

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Enterprise Application Integration
Allowing existing applications to directly exchange
information using communication middleware
information using communication middleware
Middleware as a communication facilitator in enterprise
application integration
Example communcation
middleware: CORBA
Clients may invoke methods of remote objects without worrying about:
bj t l ti i l
Z
foo()
object location, programming language,
operating system platform, communcation
protocols or hardware.
Different
programming languages
(or object models)
X
invoke Z’s
method
foo()
Y
IDL
Object Request Broker (ORB)
Common object model
IDL IDL
RMI over IIOP

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Distributed Pervasive
Systems
Devices in distributed pervasive systems
Devices in distributed pervasive systems
discovers the environment and establishes
themselves in this environment as best as
possible.
 Requirements for pervasive applications
 Embrace contextual changes.
Embrace contextual changes.
 Encourage ad hoc and dynamic composition.
 Recognize sharing as the default.
QUA/MUSIC context-aware adaptation
middleware for distributed pervasive systems
http://www.euronews.net/2010/06/16/music-to-you-mobile-s-ears/
device
user
context
environment
context user
context-aware,
self-adaptive
applications
provided utility
temperature
light
adapts
optimizes
monitors
varying context
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device
context
battery
memory use
CPU use
position
activity
(e.g., driving)
MUSIC Middleware
http://ist-music.berlios.de/

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Summary
 Distributed systems:
 components located in a network that communicates and
p
coordinates their actions exclusively by sending messages.
 Consequences of distributed systems
 Independent failure of components
 Unsecure communication
 No global clock
 Distribution transparency: providing a single computer
system view
system view
 Requirements like resource sharing, openness,
scalability, fault tolerance and heterogeneity can be
satisfied by distributed systems
 Many pitfalls when developing distributed systems

Intro ds 1

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