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Distributed system.pptx
1. DILLA
UNIVERSITY
COLLEGE OF ENGINEERING &
TECHNOLOGY
School of Computing &
Course Name Distributed system(CN6122)
Name Hassen Haile
Registration no RPGCSAN-007/20 1
3. ABSTRACT:
• The distributed computing is done on many systems to solve a large scale problem. The
growing of high-speed broadband networks in developed and developing countries.
Historically, the state of computing has gone through a series of platform and environmental
changes. Distributed computing holds great assurance for using computer systems effectively.
to solve large-scale problems over the Internet.
• It becomes data-intensive and network-centric. The applications of distributed computing
have become increasingly wide-spread. In distributed computing, the main stress is on the
large scale resource sharing and always goes for the best performance. In this article, we have
reviewed the work done in the area of distributed computing paradigms.
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4. INTRODUCTION
A distributed system is a collection of independent computers that
appears to the user as a single computer (Tanenbaum & Steen, 2006) and
provides a single system view. The coordinated aggregation of these
distributed computers allows access to a large amount of computing.
We review these two new distributed computing paradigms, Jungle
computing and Fog computing, along with Cloud computing which is
related to them. We name these three as modern distributed computing
paradigms. A review of these models and their characteristics helps to
better understand modern distributed computing paradigms and their
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5. WHAT IS DISTRIBUTED COMPUTING
PARADIGM?
Multiple autonomous computers, which are geographically
distributed are communicated through message passing.
Distributed system components are located on different
networked computers that coordinate their actions by
communicating via pure HTTP,RPC-like connectors, and
message queues.
Characteristics of distributed systems include independent
failure of components and concurrency of components.
Distributed programming is typically categorized as client-
server, three-tier , n-tier, or peer to peer architecture. 5
7. CLOUD COMPUTING
Cloud computing is internet based computing , where by shared resources
software and information are provided to computers and other devices on
demand.
Cloud computing refers to manipulating, configuring, and accessing the
application online. It offers online data storage ,infrastructure and
application.
It is a paradigm in which information is permanently stored in servers on
the internet.
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8. CONT.…
A model for enabling ubiquitous , convenient, on –demand network access to
a shared pool of configurable computing resources (e.g., servers, storage,
networks , applications, and services) that can be rapidly provisioned and
released with minimal management effort of service provider interaction.
These resources can be dynamically provisioned, reconfigured and
exploited by a pay-per-use economic model in which consumer is
charged on the quantity of cloud services usage and provider
guarantees Service Level Agreements (SLA) through negotiations with
consumers. In addition, resources can be rapidly leased and released
with minimal management effort or service provider interaction. it is
both a combination of software and hardware based computing8
11. Requires a constant internet connections
Does not work well with low-speed connections
Features might be limited
Can be slow
Stored data can be lost
Stored data might not be secure
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DISADVANTAGE OF CLOUD COMPUTING
12. MODELS FOR CLOUD COMPUTING
1. Deployment Models
Is the type of access to the cloud, i.e., how the cloud is located ?cloud can
have any of the four types of access: Public , Private, Hybrid and community.
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Public
cloud
Private cloud
Hybrid
Cloud
Community
Cloud
13. DEPLOYMENT MODELS
• Four general Cloud deployment models known as private, public, community, and
hybrid Cloud.
Public cloud: system and services to be easily accessible to the general public
cloud may be less secure because of its openness, e.g.., e-mail.
Private cloud: system and services to be easily accessible with in an
organization. It offers increased security because of its private nature.
Community cloud: the community cloud allows systems and services to be
accessible by group of organizations.
Hybrid (combined) cloud: the hybrid cloud is a mixture of public and private
cloud. However, the critical activities are performed using private cloud while the
non-critical activities are performed using public cloud. 13
14. 2. Service Model
Service Model are the reference models on which the cloud computing is based.
These can be categorized in to three basic service models.
1. Infrastructure as a service (IaaS): is the delivery of technology infrastructure as
an on demand scalable service. Operating system and network is provided.
2. Platform as a Service (PaaS): provides the runtime environment for applications
, development and deployment tools, etc. Operating system and network is
provided.
3. Software as a Service (SaaS) : is a software delivery methodology that provides
licensed multi-tenant access to software and its functions remotely as a web
based service. Just network is provided.
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15. JUNGLE COMPUTING
Jungle computing is a simultaneous combination of several distributed
and high performance computing systems to achieve peak performance
as well as reduce programming complexity.
Jungle computing system is highly heterogeneous. It may include
clusters, grids, clouds, supercomputers, and even mobile devices,
possibly with accelerators such as GPUs and FPGAs
The Ibis high-performance distributed programming framework is an
example of software platforms designed to assist Jungle computing. It has
become exceedingly difficult to write applications for such Jungle
Computing Systems, particularly with the introduction of multi-core
hardware technologies.
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17. ADVANTAGES OF JUNGLE COMPUTING
Fog can be distinguished from cloud by its proximity to end
users.
The dense geographical distribution and its support for mobility.
It provides low latency, location awareness, and improves
quality of service(QoS) and real time applications.
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18. CHALLENGE OF JUNGLE COMPUTING
There are often several kernels with the same features but aimed at
various platforms (referred to as equi-kernels). All of these kernels are
beneficial, e.g. due to various scalability features or availability of ad
hoc hardware. The challenge is to transparently integrate (multiple)
domain-specific kernels with Jungle Computing programming models
and applications. More approaches should be explored, including those
that take into consideration the major advantages of coordinating
several sub- sequent kernels, and scheduling these as a single kernel.
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19. CONT…
• Kernels mapping to resources is a dynamic issue. It is due to the
possibility of adding or removing resources and the computational
requirements of kernels that vary over time. In addition, the mapping
can take into consideration optimization under several, probably
overlapping, goals (e.g., speed, energy use, financial costs and
productivity). The problem is to what degree the transparent and
dynamic migration of compute kernels in Jungle Computing Systems
can be enabled with run- time support.
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20. FOG COMPUTING
• Fog computing is the expansion of the cloud to the network edge. Fog computing
enables decentralized computing through processing data at the fog node. Any
computer capable of storing, computing, and connecting to the network can be used
as a fog node. Fog computing also enables mobility support, location awareness,
real-time interactions, interoperability and scalability . A Fog computing system
essentially composed of traditional networking equipments such as switches,
routers, proxy servers and Base Stations (BS), etc. and may be positioned nearer to
the proximity of IoT devices/sensors.
• Fog computing has a significant benefit to smart cities, since many devices utilize
real time data to handle different tasks. Fog computing is utilized also in
autonomous vehicles as data processing needs to be done in real time.
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21. CHARACTERIZATION OF FOG COMPUTING
• Fog Computing is a highly virtualized platform that provides compute,
storage, and networking services between end devices and traditional
Cloud Computing Data Centers, typically, but not exclusively located
at the edge of network. The next Figure presents the idealized
information and computing architecture supporting the future IoT
applications, and illustrates the role of Fog Computing.
• Compute, storage, and networking resources are the building blocks
of both the Cloud and the Fog .
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22. ADVANTAGE AND DISADVANTAGES OF FOG
• The advantages of fog computing are:
• Fog computing enables real time data analysis that allows IoT applications
work faster.
• Businesses decrease storage and computational expenses by processing data
at fog nodes. Moreover, confidential data will be secured since it is stored at the
fog node.
• Fog computing are used to improve low latency networks among analytics
endpoints and devices. Compared to cloud computing, using such net- works
will lead to reduction of bandwidth requirements.
• Fog computing can process greater volumes of data compared to edge
computing because it can manage requests in real time.
• The disadvantage of fog computing is that:
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25. SUMMERY
The future of computing is heading toward using shared
heterogeneous resources and is concerned about Big Data. These
requirements result in emerging new distributed computing paradigms.
In this article, we have strived to clarify modern distributed computing
paradigms, namely Cloud, Jungle and Fog computing.
In Cloud computing, resources a removing away from end-users
towards centralized systems that possess huge processing power and
storage capacities. It is obvious that Cloud computing is used in Fog
computing and may or should be used in Jungle computing. Therefore,
bear in mind that knowing Cloud computing is essential in distributed
computing.
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26. REFERENCES
Aazam, Mohammad, and Eui-Nam Huh. “ Dynamic resource
provisioning through Fog micro datacenter.” 2015 IEEE International
Conference on Pervasive Computing and Communication
Workshops St. Louis, MO: IEEE, 2015.
Chiang, Mung, and Tao Zhang. “ Fog and IoT: an overview of
research opportunities.” IEEE Internet Things J 3 (6) (2016): 854– 864.
• D. Evans The internet of things: how the next evolution of the
internet is changing everything CISCO white paper, 1 (2011) (2011),
pp. 1-11
• F. Bonomi. Connected vehicles, the internet of things, and fog
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