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Distributed system.pptx

Feb. 12, 2023
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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
  2. CONTENTS  Introduction Distributed computing paradigm Cloud computing Jungle Computing Fog computing Summary 2
  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. 3
  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 4
  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
  6. TAXONOMY OF DISTRIBUTED COMPUTING PARADIGM 6
  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. 7
  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
  9. CLOUD COMPUTING ARCHITECTURE 9
  10. ADVANTAGE OF CLOUD COMPUTING 10 • Lower computer costs • Improved performance: • Reduced software costs • Instant software updates • Improved document format compatibility • Unlimited storage capacity • Increased data reliability • Universal document access
  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 11 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. 12 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. 14
  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. 15
  16. JUNGLE COMPUTING ARCHITECTURE 16
  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. 17
  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. 18
  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. 19
  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. 20
  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 . 21
  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: 22
  23. FOG COMPUTING ARCHITECTURE 23
  24. 24 CLOUD COMPUTING VS FOG COMPUTING
  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. 25
  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 26
  27. Thank you for your comment 27
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