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Distributed (Operating) Systems -Architectures-

Distributed (Operating) Systems -Architectures-. Computer Engineering Department Distributed Systems Course Asst. Prof. Dr. Ahmet Sayar Kocaeli University - Fall 201 2. Outline. Software architecture Layered architectures Object-based architectures Data-centered architectures

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Distributed (Operating) Systems -Architectures-

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  1. Distributed (Operating) Systems -Architectures- Computer Engineering Department Distributed Systems Course Asst. Prof. Dr. AhmetSayar • Kocaeli University - Fall 2012

  2. Outline • Software architecture • Layered architectures • Object-based architectures • Data-centered architectures • Event-based architectures • System Architecture • Centralized, decentralized, hybrid • Middleware (aim is distribution transparency) • Self-managing systems (autonomic systems) • System Monitoring • Taking appropriate measures

  3. A. Software Architectures • Important styles of architecture for distributed systems • Layered architectures • Object-based architectures • Data-centered architectures • Event-based architectures

  4. 1. Layered Design • Each layer uses previous layer to implement new functionality that is exported to the layer above • Example: Multi-tier web apps

  5. 2. Object-based Style • Each object corresponds to a components • Components interact via remote procedure calls • Popular in client-server systems

  6. 3. Shared data-space(combination of event-based and data-centered) • “Bulletin-board” architecture • Decoupled in space and time • Post items to shared space; consumers pick up at a later time

  7. 4. Event-based architecture • Communicate via a common repository • Use a publish-subscribe paradigm • Consumers subscribe to types of events • Events are delivered once published by any publisher

  8. B. System Architectures • Centralized, decentralized, hybrid • Middleware (aim is distribution transparency) • Self-managing systems (autonomic systems) • System Monitoring • Taking appropriate measures

  9. Centralized

  10. Client-Server Architectures • Most common style: client-server architecture • Application layering • User-interface level • Processing level • Data level

  11. Search Engine Example • Search engine architecture with 3 layers

  12. Multitiered Architectures • The simplest organization is to have only two types of machines: • A client machine containing only the programs • implementing (part of) the user interface level • A server machine containing the rest, • the programs implementing the processing and data level • Everything is handled by the server while the client is essentially no more than a dumb terminal, possibly with a graphical interface

  13. A Spectrum of Choices

  14. Three-tier Web Applications • Server itself uses a “client-server” architecture • 3 tiers: HTTP, J2EE and database • Very common in most web-based applications

  15. Decentralized

  16. Distribution • Vertical Distribution • Multi-tiered arch: different tiers assigned to different distributed machines • Logically different components on different machines • Centralized or decentralized • Horizontal Distribution • Example is peer to peer systems • Decentralized • Client or server may be physically split up into logically equivalent parts. But each part is operating on its own share of the complete data set, thus balancing the load.

  17. Peer-to-peer systems • Removes distinction between a client and a server • Each process will act as a client and a server at the same time • Overlay network of nodes • Structured peer-to-peer system • Chord System • CAN System

  18. 1. Chord system • Use a distributed hash table to locate objects • Data item with key k -> smallest node with id >= k • Pears are located logically on the ring • Assume there are 16 nodes • 1,4,7,12 and 15 are given the responsibility • They serve the data items whose ids are lower than their ids • Each node has two-responsibility • Lookup • Serving the content

  19. 2. Content Addressable Network (CAN) • CAN: d-dimensional coordinate system • Partitioned among all nodes in the system • Example: [0,1] x [0,1] space across 6 nodes • Every data item maps to a point • Join: pick a random point, split with node for that point • Leave: harder, since a merge may not give symmetric partitions

  20. Unstructured P2P Systems • Topology based on randomized algorithms • Each node pick a random set of nodes and becomes their neighbors • Gnutella • Choice of degree impacts network dynamics

  21. Structured and Unstructured P2P • Can move from one to another • Carefully exchange and select entries from partial views

  22. SuperPeers • Some nodes become “distinguished” • Take on more responsibilities (need to have or be willing to donate more resources) • Example: Skype super-peer

  23. Hybrid Systems • Client-server solutions are combined with decentralized architectures. • Examples are • Edge-Server Systems • Collaborative Distributed Systems

  24. 1.Edge-Server Systems • Edge servers: from client-server to client-proxy-server • Content distribution networks: proxies cache webcontent near the edge

  25. 2.Collaborative Distributed Systems • BitTorrent: Collaborative P2P downloads • Download chunks of a file from multiple peers • Reassemble file after downloading • Use a global directory (web-site) and download a .torrent • torrent contains info about the file • Tracker: server that maintains active nodes that have requested chunks • Force altruism: • If P sees Q downloads more than uploads, reduce rate of sending to Q

  26. Middleware • Forms a layer between applications and distributed platforms • Aim is distribution transparency • specific solutions should be adaptable to application requirements • Best approach: easy to configure, adapt, and customize as needed by an application • This is the result of separation of policies from mechanisms

  27. Middleware: General Approaches • Interceptors • Nothing but a software construct. That will break the usual flow and allow other code to be executed. • Generality or simplicity (ad-hoc) • Adaptive software • Environments in which dist applications are executed changes continuously • Mobility, failing hardware etc • Rather than making applications responsible for reacting to changes, this task is placed in the middleware • Separation of concerns (Aspect-oriented software) • Computational Reflection • Component-based design

  28. Self-Managing Systems • System is adaptive • Monitors itself and takes action autonomously when needed • Autonomic computing, self-managing systems • Self-*: self-managing, self-healing • Example: automatic capacity provisioning • Vary capacity of a web server based on demand

  29. Feedback Control Model • Use feedback and control theory to design a self-managing system

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