Intro to Distributed Systems (By Lasmon Kapota).pptx

Intro to Distributed
Systems
By Lasmon Kapota

What is Distributed System?
A collection of independent computers that appears to its users as a single coherent system.
A system in which components located at networked computers communicate and
coordinate their actions only by passing messages.
• Distributed systems provide a high degree of availability in the face of hardware faults. The
availability of a system is a measure of the proportion of time that it is available for use.
• When one of the components in a distributed system fails, only the work that was using the
failed component is affected. A user may move to another computer if the one that they
were using fails; a server process can be started on another computer.

Characteristics of a Distributed System
1. Composed of autonomous components
• The system components are able to behave independently of each other.
• The system components communicate by exchanging messages with each other.
2. Works as a single coherent system
• The collection of components as a whole operates the same, no matter where, when and how
interaction between a user and the system takes place.
• End users do not even notice that they are dealing with processes, data and control that are
dispersed across a computer network.
Resource sharing is the main motivating factor for constructing distributed systems.

Consequences of the Distributed System
Characteristics
1. Concurrency of components
• The components/nodes can coordinate and execute programs concurrently as they share
resources.
• The capacity of the system to handle shared resources can be increased by adding more
resources (e.g. computers) to the network.
2. Lack of global clock
• There is no single global notion of the correct time.
• When programs need to cooperate they coordinate their actions by exchanging messages.

Consequences of the Distributed System
Characteristics
• Close coordination often depends on a shared idea of the time at which the
programs’ actions occur
3. Independent failures of components
• The failure of a computer, or the unexpected termination of a program
somewhere in the system (a crash), is not immediately made known to the other
components with which it communicates.
• Each component of the system can fail independently, leaving the others still
running.

Examples of a Distributed System
• Local Area Network and Intranet
• Database Management System
• Automatic Teller Machine Network
• Internet/World-Wide Web
• Mobile and Ubiquitous Computing

Network OS vs Distributed OS
Network OS
• Network OS is a system that connects multiple devices and computers on a
network and allows them to share resources on the network.
• E.g. Microsoft Windows Server, Unix, Linux, Novell Netware, Banyan’s VIVES, etc.
• Two basic types are peer-to-peer system & client-server system.
• Primarily concerned with managing resources and communication within a single
network.
• The networked nodes possess their own operating systems.

Distributed OS
• Distributed OS is a system in which two or more systems are connected to each
other and work together to serve real-time applications.
• In other words, it is a system software that manages a network of independent
computers and makes it appear as a single system.
• It uses many central processors to serve multiple real-time applications and users.
• Connects multiple nodes via a communication channel such as high-speed bus or
telephone lines.
• Types include peer-to-peer system, client-server system, 3-tier, middleware, etc.

Network Operating System (OS) Distributed Operating System (OS)
Main objective is to provide the local services to
remote client.
Main objective is to manage the hardware resources.
Communication is file-based or shared folder-
based.
Communication is message-oriented and shared
memory-oriented
Has low fault tolerance. Has high fault tolerance.
Easy to implement and maintain. Difficult to implement and maintain.
All nodes can have different operating systems. All nodes have the same operating system.
Highly scalable. Less scalable.
More centralized (Single point of control) Decentralized (Multiple points of control)

Middleware
• A software that bridges the gap between applications and operating systems by
providing a method for communication and data management.
• The capability is useful for applications that otherwise do not have any way to
exchange data with other software tools or databases.
• Its purpose is to mask heterogeneity and to provide a convenient programming
model to application programmers to promote interoperability and portability.
• It is concerned with providing useful building blocks for the construction of
software components that can work with one another in a distributed system.

Middleware
It sits between an OS and applications to connect and share data between the
applications.

Middleware Components
• Middleware typically consists of these components:
• Management console: Provides an overview of the middleware's activities and
configurations.
• Client interface: Communicates with the involved applications, databases or other services.
• Internal interface: Ensures that components function cohesively.
• Platform interface: Ensures compatibility between software.
• Contract manager: Defines the procedures that applications must follow for data exchange.

Middleware Components
• Contract manager: Defines the procedures that applications must follow
for data exchange.
• Session manager: Creates secure communication channels between the
middleware and applications.
• Database manager: Integrates with different databases.
• Runtime monitor: Continuously monitors middleware data movements and
generates reports for developers.

Middleware Categories
• Most middleware falls into one of two categories:
 Enterprise application integration middleware
• Enables programmers to create business applications without having to customize integrations for each
new application.
• Provides a functionality for data consistency and business to business (B2B) integration so the two
software applications can work together.
 Platform middleware
• Provides a runtime hosting environment for software development and delivery.
• May provide a container for application program logic, as well as tools like web servers, application servers
and content management systems.

Types of Middleware
• There are many types of middleware, each with specific functions and uses. Common types include
the following:
• Messaging middleware, also known as message-oriented middleware, facilitates communications
between distributed applications and services.
• Object or Object Request Broker (ORB) middleware enables software components or objects to
communicate and interact with a program, such as containers, across distributed systems.
• Remote Procedure Call (RPC) middleware provides a protocol that enables a program to request
a service from another program located on a separate computer or network.
• Data or database middleware enables direct access to, and interaction with, databases; it typically
includes SQL database software and its own data store.

Types of Middleware
• Transaction or transactional middleware ensures transactions move from one phase to
the next via transaction process monitoring.
• Content-centric middleware enables client-side requests for specific content and abstracts
and delivers it.
• Embedded middleware facilitates communication and integration between embedded
apps and real-time operating systems.
• API middleware enables developers to create and manage APIs and, in some cases, to
monetize APIs.
• Asynchronous data streaming middleware enables data sharing between applications.

Why Middleware
It is used in software development.
o Enables organizations and developers to build apps more efficiently.
o Used in data handling, API management and in many authentication & messaging services.
It manages connectivity to various back-end resources.
o Might create a connection pool to provide fast and efficient access to back-end database.
o Also create connections to message queues & topics and manage connections to cloud-
based resources.

Why Middleware
It implements logic based on client requests.
o Can take a user request, implement logic and customize the results to meet the client’s
preferences.
It handles concurrent processing, load balancing and transaction management.
o Can scale typically vertically and horizontally to distribute incoming client requests over
multiple cloud servers. This is called load balancing.
o Can also handle concurrency and transaction management issues. E.g. problems that arise
when multiple clients attempt to simultaneously access or update a back-end resource.

Why Middleware
It secures access to back-end resources.
o Usually require both a secure connection using a technology like Secure Sockets Layer
and authentication using either a username and password combination or a digital
certificate.
o Sends data to a requesting client only if the client has the authority to access the data. It
does so using secure and encrypted connection.

Design Issues of a Distributed System
Heterogeneity
• They must be constructed from a variety of different networks, computer
hardware, operating systems, programming languages, and implementations
by different developers.
• The differences in programming languages must be addressed if programs
written in different languages are to be able to communicate with one
another.
• Programs written by different developers cannot communicate with one
another unless they use common standards.

Heterogeneity and Middleware
• A separate layer of software that is logically placed between a higher-level layer consisting of
users and applications, and a layer underneath consisting of operating systems and basic
communication facilities.
• A software layer that provides a programming abstraction as well as masking the heterogeneity
of the underlying networks, hardware, operating systems and programming languages.
• The distributed system provides the means for components of a single distributed application
to communicate with each other, but also to let different applications communicate. At the
same time, it hides, as best and reasonable as possible, the differences in hardware and
operating systems from each application.

Heterogeneity and Middleware
• Middleware is the same to a distributed system as what an operating system is to a
computer. A manager of resources that offers its applications ability to efficiently
share and deploy those resources across a network.
• Apart from resource management, it offers services that can also be found in most
operating systems, including: security services, inter-application communication
facilities, accounting services, and masking of and recovery from failures.
• The main difference with a operating system is that a middleware services are
offered in a networked environment.

Examples of Typical Middleware Services
• Communication e.g. remote procedure call.
• Transactions e.g. atomic transaction.
• Service composition e.g. Mashups.
• Reliability e.g. Use of Horus toolkit.
• Middleware can also be viewed as a container of commonly used
components and functions that no longer have to be implemented by
applications separately.

Heterogeneity and Mobile Code
• A program code that can be transferred from one computer to another and
run at the destination e.g. Java applets.
• Code suitable for running on one computer is not necessarily suitable for
running on another because executable programs are normally specific both
to the instruction set and to the host operating system.
• The virtual machine approach provides a way of making code executable on
a variety of host computers: the compiler for a particular language generates
code for a virtual machine instead of a particular hardware order code.

Heterogeneity and Mobile Code
• For example, the Java compiler produces code for a Java virtual machine,
which executes it by interpretation. The Java virtual machine needs to be
implemented once for each type of computer to enable Java programs to
run.
• Today, the most commonly used form of mobile code is the inclusion
Javascript programs in some web pages loaded into client browsers.

Openness
• A characteristic that determines whether the system can be extended and reimplemented in
various ways.
• The openness of distributed systems is determined primarily by the degree to which new
resource-sharing services can be added and be made available for use by a variety of client
programs.
• May be extended at the hardware level by the addition of computers to the network and at the
software level by the introduction of new services and the reimplementation of old ones,
enabling application programs to share resources.
• A further benefit that is often cited for open systems is their independence from individual
vendors.

Openness
• To summarize, open distributed systems:
 Are characterized by the fact that their key interfaces are published.
 Are based on the provision of a uniform communication mechanism and
published interfaces for access to shared resources.
 Can be constructed from heterogeneous hardware and software, possibly from
different vendors.
o But the conformance of each component to the published standard must be carefully
tested and verified if the system is to work correctly.

Security
• Security for information resources has three components: confidentiality (protection
against disclosure to unauthorized individuals), integrity (protection against alteration
or corruption), and availability (protection against interference with the means to
access the resources).
• Issues like sending sensitive information in a message over a network in a secure
manner and identifying a remote user or other agent correctly are met by the use of
encryption techniques.
• However, the following two security challenges have not yet been fully met: denial of
service attacks and security of mobile code.

Scalability
• Distributed systems operate effectively and efficiently at many different scales, ranging
from a small intranet to the Internet.
• A system is described as scalable if it will remain effective when there is a significant
increase in the number of resources and the number of users.
• The design of scalable distributed systems presents the following challenges:
Controlling the cost of physical resources: As the demand for a resource grows, it
should be possible to extend the system, at reasonable cost, to meet it.
 In general, for a system with n users to be scalable, the quantity of physical resources required to
support them should be at most O(n).

Scalability
Controlling the performance loss: Consider the management of a set of data
whose size is proportional to the number of users or resources in the system.
 Algorithms that use hierarchic structures scale better than those that use linear
structures.
 But even with hierarchic structures an increase in size will result in some loss in
performance: the time taken to access hierarchically structured data is O(log n), where n
is the size of the set of data.
 For a system to be scalable, the maximum performance loss should be no worse than
this.

Scalability
Preventing software resources running out: A good example is the adoption
of 128-bit Internet addresses as the supply of available 32-bit Internet
addresses was running out. This requires modifications to many software
components.
Avoiding performance bottlenecks: In general, algorithms should be
decentralized to avoid having performance bottlenecks. Caching and
replication may be used to improve the performance of resources that are
very heavily used.

Failure Handling
Computer systems sometimes fail. When faults occur in hardware or
software, programs may produce incorrect results or may stop before they
have completed the intended computation.
Failures in a distributed system are partial – that is, some components fail
while others continue to function. Therefore the handling of failures is
particularly difficult.
The following techniques are used for dealing with failures:

Failure Handling
Detecting failures: Some failures can be detected. E.g. checksums can be used to
detect corrupted data in a message or a file.
o However, it is difficult or even impossible to detect some other failures, such as a remote
crashed server in the Internet.
Masking failures: Some failures that have been detected can be hidden or made less
severe. Two examples of hiding failures:
1. Messages can be retransmitted when they fail to arrive.
2. File data can be written to a pair of disks so that if one is corrupted, the other may still be
correct.

Failure Handling
 Tolerating failures: Most of the services in the Internet do exhibit failures; it would not be practical
for them to attempt to detect and hide all of the failures that might occur in such a large network
with so many components. Their clients can be designed to tolerate failures, which generally
involves the users tolerating them as well.
o For example, when a web browser cannot contact a web server, it does not make the user wait for ever while it
keeps on trying; it informs the user about the problem, leaving them free to try again later.
 Recovery from failures: Recovery involves the design of software so that the state of permanent
data can be recovered or ‘rolled back’ after a server has crashed.
o In general, the computations performed by some programs will be incomplete when a fault occurs, and the
permanent data that they update (files and other material stored in permanent storage) may not be in a consistent
state.

Failure Handling
 Redundancy: Services can be made to tolerate failures by the use of redundant components.
 Consider the following examples:
There should always be at least two different routes between any two routers in the
Internet.
In the Domain Name System, every name table is replicated in at least two different servers.
A database may be replicated in several servers to ensure that the data remains accessible
after the failure of any single server.
o The servers can be designed to detect faults in their peers; when a fault is detected in one server, clients
are redirected to the remaining servers.

Concurrency
Both services and applications provide resources that can be shared by clients in
a distributed system.
There is therefore a possibility that several clients will attempt to access a shared
resource at the same time.
The process that manages a shared resource could take one client request at a
time. But that approach limits throughput.
Therefore services and applications generally allow multiple client requests to be
processed concurrently.

Concurrency
Any object that represents a shared resource in a distributed system must be
responsible for ensuring that it operates correctly in a concurrent
environment.
o This applies not only to servers but also to objects in applications.
For an object to be safe in a concurrent environment, its operations must be
synchronized in such a way that its data remains consistent.
o This can be achieved by standard techniques such as semaphores, which are used in
most operating systems.

Transparency
The concealment from the user and the application programmer of the separation of
components in a distributed system, so that the system is perceived as a whole rather
than as a collection of independent components.
Transparency hides and renders anonymous the resources that are not of direct
relevance to the task in hand for users and application programmers.
For example, it is generally desirable for similar hardware resources to be allocated
interchangeably to perform a task; the identity of a processor used to execute a process
is generally hidden from the user and remains anonymous.

Eight Forms of Transparency
Access transparency enables local and remote resources to be accessed using identical
operations.
Location transparency enables resources to be accessed without knowledge of their
physical or network location (e.g. which building or IP address).
Concurrency transparency enables several processes to operate concurrently using shared
resources without interference between them.
Replication transparency enables multiple instances of resources to be used to increase
reliability and performance without knowledge of the replicas by users or application
programmers.

Eight Forms of Transparency
Failure transparency enables the concealment of faults, allowing users and application
programs to complete their tasks despite the failure of hardware or software
components.
Mobility transparency allows the movement of resources and clients within a system
without affecting the operation of users or programs.
Performance transparency allows the system to be reconfigured to improve performance
as loads vary.
Scaling transparency allows the system and applications to expand in scale without
change to the system structure or the application algorithms.

Transparency
The two most important transparencies are access and location transparency;
their presence or absence most strongly affects the utilization of distributed
resources.
They are sometimes referred to together as network transparency.

Quality of Service
Once users are provided with the functionality that they require of a service, such as the file
service in a distributed system, they then think about the quality of the service provided.
The main nonfunctional properties of systems that affect the quality of the service
experienced by clients and users are reliability, security and performance.
Adaptability to meet changing system configurations and resource availability has been
recognized as a further important aspect of service quality.
The performance aspect of quality of service was originally defined in terms of
responsiveness and computational throughput, but it has been redefined in terms of ability
to meet timeliness guarantees.

Recap on Key Characteristics of a
Distributed System
Heterogeneity
Openness
Security
Scalability
Failure Handling
Concurrency
Transparency
Quality of service

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