Fundamental of distributed system

1. Chapter 1 - Introduction

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1.1 Introduction and Definition
 before the mid-80s, computers were
 Very expensive (hundred of thousands or even millions
of dollars)
 Very slow
 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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 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 (Tanenbaum
& Van Steen)
 this definition has two aspects:
1. hardware: autonomous(independent) machines
2. software: a single system view for the users

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 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
 Inherent distribution, communication
 organizational distribution, e-mail, video

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 Problems of Distribution
 Concurrency, Security
 clients must not disturb each other
 Privacy
 e.g., when building a preference profile
 unwanted communication such as spam
 Partial failure
 we often do not know where the error is (e.g., RPC)
 Location, Migration, Replication
 clients must be able to find their servers
 Heterogeneity
 hardware, platforms, languages, management

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1.2 Organization and Goals 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
a distributed system organized as middleware; note that the middleware
layer extends over multiple machines

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 Goals of a distributed system: a distributed system should
 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
 Transparency in a Distributed System
 a distributed system that is able to present itself to users
and applications as if it were only a single computer
system is said to be transparent

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 different forms of transparency in a distributed system
Transparency Description
Access Hide differences in data representation
(file naming, ...) and how a resource
is accessed
Location Hide where a resource is physically located; where
is http://www.google.com? (naming)
Migration Hide that a resource may move to another location
Relocation Hide that a resource may be moved to another
location while in use; e.g., mobile users using their
wireless laptops
Replication Hide that a resource is replicated
Concurrency Hide that a resource may be shared by several
competitive users; a resource must be left in a
consistent state
Failure Hide the failure and recovery of a resource
Persistence Hide whether a (software) resource is in memory
or on disk

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 Openness in a Distributed System
 A distributed system should be open
 we need well-defined interfaces
 Interoperability
 components of different origin can communicate
 Portability
 components work on different platforms
 Another goal of an open distributed system is that it
should be flexible and extensible;
 easy to configure the system out of different components;
 easy to add new components,
 easy to replace existing ones
 an Open Distributed System is a system that offers
services according to standard rules that describe the
syntax and semantics of those services; e.g., protocols in
networks

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 Scalability in Distributed Systems
 a distributed system should be scalable
 Size: adding more users and resources to the system
 Geographically: users and resources may be far apart
 Administratively: should be easy to manage even if it
spans many administrative organizations

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Concept Example
Centralized services
Single server for all users-mostly for security
reasons
Centralized data A single on-line telephone book
Centralized algorithms Doing routing based on complete information
examples of scalability limitations
 Scalability problems: performance problems caused by
limited capacity of servers and networks
 Scaling Techniques
 how to solve scaling problems
 For geographical scalability: the problem is mainly
performance, due to the limitations in the capacity of
servers and networks
 three possible solutions: hiding communication latencies,
distribution, and replication

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a. Hide Communication Latencies
 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; when a reply arrives the application is
interrupted
 Good for batch processing and parallel applications but
not for interactive applications
 for interactive applications, move part of the job to the
client to reduce communication; e.g. filling a form and
checking the entries

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(a) a server checking the correctness of field entries
(b) a client doing the job

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b. Distribution
 e.g., DNS - Domain Name System
 divide the name space into zones
 for details, see later in Chapter 4 - Naming
an example of dividing the DNS name space into zones

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c. Replication
 Replicate components across a distributed system to
increase availability and for load balancing, leading to
better performance
 decided by the owner of a resource
 caching (a special form of replication) also reduces
communication latency; decided by the user
 but, caching and replication may lead to consistency
problems (see Chapter 6 - Consistency and Replication)

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1.3 Hardware and Software Concepts
 Hardware Concepts
 different classification schemes exist
 multiprocessors - with shared memory
 multicomputers - that do not share memory
 can be homogeneous or heterogeneous

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 a single
backbone
different basic organizations of processors and memories in distributed
systems

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a bus-based multiprocessor
 Multiprocessors - Shared Memory
 the shared memory has to be coherent –
 the same value written by one processor must be read by another
processor
 Performance problem for bus-based organization since the
bus will be overloaded as the number of processors
increases
 The solution is to add a high-speed cache memory
between the processors and the bus to hold the most
recently accessed words; may result in incoherent memory
 Bus-based multiprocessors are difficult to scale even with
caches
 Two possible solutions: crossbar switch and omega
network

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 Crossbar switch
 divide memory into modules and connect them to the
processors with a crossbar switch
 at every intersection, a crosspoint switch is opened and
closed to establish connection
 problem: expensive; with n CPUs and n memories, n2
switches are required

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 Omega network
 use switches with multiple input and output lines
 drawback: high latency because of several switching
stages between the CPU and memory

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 Homogeneous Multicomputer Systems
 also referred to as System Area Networks (SANs)
 the nodes are mounted on a big rack and connected
through a high-performance network
 could be bus-based or switch-based
 bus-based
 shared multiaccess network such as Fast Ethernet can be
used and messages are broadcasted
 Performance drops highly with more than 25-100 nodes
(contention)

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Grid
Hypercube
 switch-based
 messages are routed through an interconnection network
 two popular topologies: meshes (or grids) and
hypercubes

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 Heterogeneous Multi-Computer Systems (HMCS)
 most distributed systems are built on heterogeneous
multicomputer systems
 the computers could be different in processor type,
memory size, architecture, power, operating system, etc.
and
 I/O bandwidth and the interconnection network may be
highly are different
 the distributed system provides a software layer to hide
the heterogeneity at the hardware level; i.e., provides
transparency

24. Software Concepts
 Distributed OS (DOS)
 Network OS (NOS)
 Middleware
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 Operating systems for distributed computers can be
roughly divided into two categories:
 Tightly-coupled systems:
 The OS tries to maintain a single, global view of the resources
 Generally, referred to as distributed OSs (DOS)
 Used for multiprocessors and homogeneous multi-computers
 Each component dependent on the others
 Manages all the resources in a distributed system,
 Provides transparency (location, migration, concurrency,
replication)
 Loosely-coupled systems, referred to as network OSs
(NOS)
 In which, there are a collection of computers each running their
own operating system;
 However, these OS work together to make their services and
resources available to others
 Used for heterogeneous multi-computers
Software Concepts…….

26.  Middleware:
 To enhance the services of network operating
system (NOS)
 To provide distribution transparency
 To actually come to a distributed system
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Software Concepts……

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System Description Main Goal
DOS
Tightly-coupled operating system for multi-
processors and homogeneous
multicomputers
Hide and manage
hardware
resources
NOS
Loosely-coupled operating system for
heterogeneous multicomputers (LAN and
WAN)
Offer local
services to remote
clients
Middleware
Additional layer atop of NOS implementing
general-purpose services
Provide
distribution
transparency
 Summary of main issues
an overview of DOSs, NOSs, and middleware

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 Distributed Operating Systems
 Two types of Distributed systems
 Multiprocessor operating system:
 Manages the resources of a multiprocessor
 Multicomputer operating system:
 An operating system that is developed for
homogeneous multi-computers

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Uniprocessor Operating Systems:
 One large kernel that handles everything (e.g., MS-
DOS, early UNIX).
 Microkernel architecture: The OS kernel is
decomposed into micro kernels,
 Separating applications from operating system code
through a microkernel

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 More on Multiprocessor Operating Systems
 Extended from uniprocessor operating systems to support
multiple processors having access to a shared memory
 Problem: Consistency
 Solution: using a protection mechanism (or two
synchronization mechanisms): semaphores and monitors
 Semaphore: an integer with two atomic operations down
and up
 Monitor: a programming language construct consisting
of procedures and variables that can be accessed only
by the procedures of the monitor;
 only a single process at a time is allowed to execute
a procedure

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 Multicomputer Operating Systems
general structure of a multicomputer operating system
 Processors can not share memory; instead communication
is through message passing
 Each node has its own
 kernel for managing local resources
 separate module for handling interprocessor
communication

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 Distributed Shared Memory Systems
 how to emulate shared memories on distributed systems to
provide a virtual shared memory
 page-based distributed shared memory (DSM) - use the
virtual memory capabilities of each individual node
pages of address space distributed among four machines

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situation if page 10 is read only and replication is used
situation after CPU 1 references page 10
 read-only pages can be easily replicated

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 Network Operating Systems
 possibly heterogeneous underlying hardware
 constructed from a collection of uniprocessor systems, each
with its own operating system and connected to each other
in a computer network
general structure of a network operating system

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 Services offered by network operating systems
 remote login (rlogin)
 remote file copy (rcp)
 shared file systems through file servers
two clients and a server in a network operating system

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 Middleware
 A distributed operating system is not intended to handle a
collection of independent computers but provides
transparency and ease of use
 A network operating system does not provide a view of a
single coherent system but is scalable and open
 Combine the scalability and openness of network operating
systems and the transparency and ease of use of distributed
operating systems
 this is achieved through a middleware, another layer of
software

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general structure of a distributed system as middleware

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Item
Distributed OS Network
OS
Middleware
-based OS
Multiproc Multicomp
Degree of
transparency
Very High High Low High
Same OS on all nodes Yes Yes No No
Number of copies of
OS
1 N N N
Basis for
communication
Shared
memory
Messages Files
Model
specific
Resource management
Global,
central
Global,
distributed
Per node Per node
Scalability No Moderately Yes Varies
Openness Closed Closed Open Open
 a comparison between multiprocessor operating systems,
multicomputer operating systems, network operating
systems, and middleware-based distributed systems

39.  Networks
 Started in 1070s
 Ethernet and LAN were evented
 The internet continue to be the biggest examples of distributed
systems.
 Distributed systems have evolved from “LAN” based to
“Internet” based.
 Telecommunication networks
 Real-time systems
 Flight control systems
 Uber and Ride
 Manufacturing automation control systems
 Parallel Processing
 Distributed artificial intelligence
 Distributed Database Systems 39
Examples of Distributed Systems

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