This document provides an introduction to distributed systems. It begins by defining a distributed system as a collection of independent computers that appear as a single coherent system to users. It then discusses the history of distributed systems and provides examples like the web, mobile networks, and banking systems. Finally, it covers key characteristics of distributed systems such as transparency, openness, and scalability.

1. DADIMOS College
Department of Computer Science
Introduction to Distributed System
Chapter One
Introduction
By Kelil Mohammed

2. Introduction
 Before the mid-80s, computers were
• very expensive (hundred of thousands or even millions of dollars)
• very slow (a few thousand instructions per second)
• not connected among themselves
 After the mid-80s: two major developments
• cheap and powerful microprocessor-based computers appeared
• computer networks
LANs at speeds ranging from 10 to 1000 Mbps
WANs at speed ranging from 64 Kbps to gigabits/sec
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3. Consequence
Feasibility of using a large network of computers to
work for the same application; this is in contrast to the
old centralized systems where there was a single
computer with its peripherals.
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Introduction…

4. Definition of a Distributed System
 A distributed system is: a collection of independent
computers that appears to its users as a single
coherent system - computer
 This definition has two aspects:
– hardware: autonomous machines
– software: a single system view for the users
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5.  A distributed system is a system designed to support the
development of applications and services which can exploit a
physical architecture consisting of multiple, autonomous
processing elements that do not share primary memory but
cooperate by sending asynchronous messages over a
communication network .
 Distributed system is one that stops you getting any work done
when a machine you’ve never even heard of crashes
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Other Definitions

6. Why Distributed?
 Resource and Data Sharing
 printers, databases, multimedia servers, ...
 Availability, Reliability
 the loss of some instances can be hidden
 Scalability, Extensibility
 the system grows with demand (e.g., extra servers)
 Performance
 huge power (CPU, memory, ...) available
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7. Examples of distributed Systems
 The Web over the Internet.
 Mobile telephony over cellular networks.
 Electronic funds transfer systems over special
purpose networks
– For example, between bank accounts, on credit card
purchases, via cash machines.
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8. Other Examples …
rlogin or telnet (for remote access)
network file system, network printer, etc.
ATM (cash machine)
Distributed databases
Network computing
Retail point-of-sale terminals
Air-traffic control
Enterprise computing etc., ….
Can you mention any other examples?
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9. Characteristics of Distributed Systems
 differences between the computers and the ways they
communicate are hidden from users
 users and applications can interact with a distributed
system in a consistent and uniform way regardless of
location
 distributed systems should be easy to expand and scale
 a distributed system is normally continuously available,
even if there may be partial failures
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10. Organization of a Distributed System
 To support heterogeneous computers and networks and to
provide a single-system view, a distributed system is often
organized by means of a layer of software called middleware
that extends over multiple machines.
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11. Organization of a distr…
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A distributed system organized as middleware;
note that the middleware layer extends over
multiple machines, and offers each application
the same interface

12. Goals of a distributed system
Supporting resource sharing
Making distribution transparent
Openness (being Open)
Scalability (Being Scalable)
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13. A distributed system should :
Be easily connect users with resources (printers,
computers, storage facilities, data, files, Web pages, ...)
 reasons: economics, to collaborate and exchange
information
be transparent: hide the fact that the resources and
processes are distributed across multiple computers
be open
be scalable
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Goals of a distributed system

14. Transparency in a Distributed System
 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.
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15.  Access transparency: hide differences in data
representation and the way that resources can be
accessed by users.
 Location transparency: hide where a resource is
physically located; where is
http://www.prenhall.com/index.html? (naming)
 Migration transparency : hide that a resource may move
to another location
 Relocation transparency: hide that a resource may be
moved to another location while in use;
• e.g., mobile users using their wireless laptops
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Different forms of transparency in a distributed system

16. Different forms of transparency…
Replication transparency: hide that a resource is
replicated
Concurrency transparency: hide that a resource
may be shared by several competitive users; a
resource must be left in a consistent state
Failure transparency: hide the failure and recovery
of a resource
Note: trying to achieve all distribution transparency
may be impossible or may not be a good
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17. Transparency Description
Access
Hide differences in data representation and how a
resource is accessed
Location Hide where an 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 is replicated
Concurrency
Hide that a resource may be shared by several
independent users
Failure Hide the failure and recovery of a resource
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Distribution transparency summary

18.  An Open Distributed System is a system that offers services
according to standard rules that describe the syntax and
semantics of those services.
 For example, in computer networks, standard rules govern
the format, contents, and meaning of messages sent and
received.
 Such rules are formalized in protocols.
 In distributed systems, such services are often specified
through interfaces often described using an Interface
Definition Language (IDL)
 Syntax specifies the names of the functions, types of
parameters, return values, possible exceptions, ...
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Openness in a Distributed System

19.  Semantics are given in an informal way by means of natural
languages.(specifying precisely what those service do)
 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.
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20. Openness …
An open distributed system has the following goals:
well-defined interfaces
Interoperability
portability
it should be extensible
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21. Openness …
Interoperability
components of different origin can communicate
characterizes the extent by which two systems or
components from different manufacturers can co-exist
and work together as specified by a common
standard.
Portability
characterizes to what extent an application developed
for a distributed system A can be executed, without
modification, on a different distributed system B that
implements the same interfaces as A
components work on different platforms
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22. Openness …
 An open distributed system should also be extensible.
it should be easy to add new components ;
replace existing ones without affecting those
components that stay in place;
easy to configure the system out of different
components.
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23. Achieving openness
 At least make the distributed system independent from
heterogeneity of the underlying environment:
Hardware
Platforms
Languages
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24. Scalability in Distributed Systems
 Scalability of a distributed system can be
measured in three different dimensions:
i. scalable with respect to its size,
A system can be scalable with respect to its size,
meaning that we can easily add more users and
resources to the system without any noticeable loss of
performance.
ii. Geographical scalability:
 A geographically scalable system is one in which
the users and resources may lie far apart, but the fact
that communication delays may not be significantly
noticed.
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25. Scalability…
iii. Administrative scalability:
An administratively scalable system is one that
can still be easily managed even if it spans many
independent administrative organizations.
 but a scalable system may exhibit performance problems
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26. Scaling Techniques
 how to solve scaling problems?
 the problem is mainly performance, and arises as a
result of limitations in the capacity of servers and
networks (for geographical scalability)
 three possible solutions:
 hiding communication latencies,
 distribution, and
 replication
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27. scalability problems
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28. Hide Communication Latencies
 Hiding communication latencies is applicable in the case
of geographical scalability ;
 try to avoid waiting for responses to remote service
requests
 let the requester do other useful job
 i.e., construct requesting applications that use only
asynchronous communication instead of synchronous
communication;
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29. Hide Com….
When a reply comes in, the application is
interrupted and a special handler is called to
complete the previously-issued request.
Asynchronous communication can often be used in
batch-processing systems and parallel applications,
in which more or less independent tasks can be
scheduled for execution while another task is
waiting for communication to complete
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30. (a) server checking the correctness of field entries
(b) a client doing the job
e.g., checking the completeness of mandatory fields
– shipping code is now supported in Web applications using
Java Applets and Javascript
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31. Distribution
 Distribution involves taking a component, splitting it into
smaller parts, and subsequently spreading those parts
across the system.
 Partition data and computations across multiple machines:
Move computations to clients (Java applets)
Decentralized naming services (DNS)
Decentralized information systems (WWW)
 Example: DNS - Domain Name System
(xx@cs.aau.edu.et)
divide the name space into non-overlapping zones
More on chapter 5: Naming
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32. Distribution…
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an example of dividing the DNS name space into zones

33. 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
 lead to better performance
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34. Replication…
Caching
 caching is a special form of replication
 Reduce communication latency
 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 caching and replication lead to consistency problems
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35. Pitfalls when Developing Distributed Systems
 False assumptions made by first time developers
 The network is reliable
 The network is secure
 The network is homogeneous
 The topology does not change
 Latency is zero
 Bandwidth is infinite
 Transport cost is zero
 There is one administrator
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36. Types of Distributed Systems
Three types:
distributed computing systems,
distributed information systems
distributed pervasive systems
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37.  Used for high-performance computing tasks
 There are two types of distributed computing system:
cluster computing and grid computing
Cluster Computing
 a collection of similar workstations or PCs closely connected
by means of a high-speed LAN
 each node runs the same operating system
 Its characteristic feature is its homogeneity.
 is used for parallel programming in which a single compute
intensive program is run in parallel on multiple machines
 Each cluster consists of a collection of compute nodes that are
controlled and accessed by means of a single master node.
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Distributed Computing Systems

38. Cont’d…
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An example of a cluster computing system

39. Grid Computing
 “Resource sharing and coordinated problem solving in dynamic,
multi-institutional virtual organizations”.
 It is done by joining forces despite the geographical distance,
the distributed teams are able to contribute their own
resources so as to achieve a bigger effort.
 highly heterogeneous with respect to hardware, software (OS) ,
networks, administrative domains and security policies.
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40.  all computing resources do not have to work on the same
specific task, but can work on sub-tasks that collectively
make up the end goal.
 For example, a research team might analyse weather
patterns in the North Atlantic region, while another
team analyses the south Atlantic region, and both results
can be combined to deliver a complete picture of
Atlantic weather patterns.
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41. Distributed Information Systems
 a networked application simply consisted of a server
running that application and making it available to remote
programs, called clients.
 clients could send a request to the server for executing a
specific operation, after which a response would be sent
back.
 Integration at the lowest level would allow clients to wrap
a number of requests, possibly for different servers, into a
single larger request and have it executed as a distributed
transaction.
 The key idea was that all, or none of the requests would
be executed.
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42. Cont’d…
 As applications became more sophisticated and were
gradually separated into Independent components
(database components from processing components), it
became clear that integration should also take place by
letting applications communicate directly with each other.
 This has now led to a huge industry that concentrates on
enterprise application integration (EAl).
 Distributed Information System has two categories
 Transaction Processing Systems and
 Enterprise Application Integration
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43. Transaction Processing Systems
 Operations on a database are usually carried out in the
form of transactions.
 Programming using transactions requires special primitives
that must either be supplied by the underlying distributed
system or by the language runtime system.
 The exact list of primitives depends on what kinds of
objects are being used in the transaction.
 In a mail system, there might be primitives to send, receive,
and forward mail.
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44.  Typical examples of primitives for transaction are shown
in table below.
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Cont’d…

45. The Transaction Model
 The model for transactions comes from the world of
business
 A supplier and a retailer negotiate on
 Price
 delivery date
 Quality, etc.
 until the deal is concluded they can continue negotiating
or one of them can terminate
 but once they have reached an agreement they are bound
by law to carry out their part of the deal
 transactions between processes is similar with this
scenario
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46. e.g., assume the following banking operation
– withdraw an amount x from account 1
– deposit the amount x to account 2
 what happens if there is a problem after the first activity is
carried out?
 group the two operations into one transaction; either
both are carried out or neither
 we need a way to roll back when a transaction is not
completed
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The Transaction Model …

47. The Transaction Model…
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e.g. reserving a seat from White Plains to Malindi
through JFK and Nairobi airports
(a)transaction to reserve three flights commits
(b)transaction aborts when third flight is unavailable

48.  Properties of transactions, often referred to as ACID
Atomic: to the outside world, the transaction happens
indivisibly;
 a transaction either happens completely or not at all;
 intermediate states are not seen by other processes
Consistent: the transaction does not violate system invariants;
 invariants are preserved
 e.g., in an internal transfer in a bank, the amount of
money in the bank must be the same as it was before the
transfer (the law of conservation of money); this may be
violated for a brief period of time, but not seen to other
processes
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Properties of transactions

49. Properties of …
Isolated or Serializable: concurrent transactions do not
interfere with each other;
 if two or more transactions are running at the same
time, the final result must look as though all
transactions run sequentially in some order
Durable: once a transaction commits, the changes are
permanent.
 committed operations can’t be undone
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50.  a transaction could be flat, nested or distributed
Flat Transaction
 consists of a series of operations that satisfy the ACID
properties
 simple and widely used but with some limitations
 do not allow partial results to be committed or aborted
 i.e., atomicity is also partly a weakness
 some transactions may take too much time
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Classification of Transactions

51. Nested Transaction
 constructed from a number of sub-transactions; it is
logically decomposed into a hierarchy of sub-
transactions
 the top-level transaction forks off children that run in
parallel, on different machines; to gain performance or
for programming simplicity
 each may also execute one or more sub-transactions
 permanence (durability) applies only to the top-level
transaction; commits by children should be undone
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Classification of Transactions …

52. Classification of Transactions …
 Distributed Transaction
 a flat transaction that operates on data that are
distributed across multiple machines
 problem: separate algorithms are needed to handle the
locking of data and committing the entire transaction;
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53. (a) a nested transaction
(b) distributed transaction
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Cont’d…

54. • Enterprise Application Integration
• how to integrate applications independent from their databases
• transaction systems rely on request/reply
• how can applications communicate with each other
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middleware as a communication facilitator in enterprise
application integration

55. there are different communication models
– RPC (Remote procedure Call)
– RMI (Remote Method Invocation)
– MOM (Message-Oriented Communication)
 We will see later in Chapter 4
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56. Distributed Pervasive Systems
 the distributed systems discussed so far are characterized
by their stability; fixed nodes having high-quality
connection to a network
 there are also mobile and embedded computing devices
with wireless connections
 Distributed Pervasive System is likely to incorporate small,
battery-powered, mobile devices
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57. Distributed Pervasive ….
three requirements for pervasive applications
 embrace contextual changes:
 a device is aware that its environment may change all the time
 encourage ad hoc composition:
 devices are used in different ways by different users
 recognize sharing as the default:
 devices join a system to access or provide information
 Examples of pervasive system are:
 Home systems
 Electronic health care systems – patient monitoring
 Sensor networks – data collection, surveillance
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58. Home System
Built around one or more PCs, but can also
include other electronic devices:
– Automatic control of lighting, sprinkler systems,
alarm systems, etc.
– Network enabled appliances
– PDAs and smart phones, etc.
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59. Electronic Health Care Systems
Figure .Monitoring a person in a pervasive electronic health
care system, using
(a) a local hub or
(b) a continuous wireless connection.
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60. Sensor Networks
 A collection of geographically distributed nodes consisting
of a comm. device, a power source, some kind of sensor, a
small processor…
 Purpose: to collectively monitor sensory data
(temperature, sound, moisture etc.,) and transmit the data
to a base station
 “smart environment” – the nodes may do some
rudimentary processing of the data in addition to their
communication responsibilities.
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61. Sensor Networks …
Figure .Organizing a sensor network database, while storing and
processing data (a) only at the operator’s site or …
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62. Sensor Networks ….
Figure. Organizing a sensor network database, while storing and
processing data … or (b) only at the sensors.
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63. ===End of chapter One===
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