1. Distributed (Operating) Systems -Architectures- Computer Engineering Department Distributed Systems Course Assoc. Prof. Dr. Ahmet Sayar Kocaeli University - Fall 2015

2. Outline A.Software architecture 1.Layered architectures 2.Object-based architectures 3.Data-centered architectures 4.Event-based architectures B. System Architecture 1.Centralized, decentralized, hybrid 2.Middleware (aim is distribution transparency) 3.Self-managing systems (autonomic systems) System Monitoring Taking appropriate measures

3. A. Software Architectures Important styles of architecture for distributed systems 1.Layered architectures 2.Object-based architectures 3.Data-centered architectures 4.Event-based architectures

4. A1. Layered Design Each layer uses previous layer to implement new functionality that is exported to the layer above Example: Multi-tier web apps

5. A2. Object-based Style Each object corresponds to a components Components interact via remote procedure calls – Popular in client-server systems

6. A3. Shared data-space (data-centered) “Bulletin-board” architecture – Decoupled in space and time – Post items to shared space; consumers pick up at a later time

7. A4. 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 (1)Centralized, (2)decentralized, (3)hybrid (4)Middleware (aim is distribution transparency) (5)Self-managing systems (autonomic systems) – System Monitoring – Taking appropriate measures

9. B1. Centralized

10. Client-Server Architectures Most common style: Client-server architecture – Request x Response 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 Two tiered architecture: Only two kinds of machines, - Client and server Fat Client vs. Thin Client

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. B2.Decentralized

16. Distribution 1.Vertical Distribution – Multi-tiered arch: Different tiers assigned to different distributed machines – Logically different components on different machines – Centralized or decentralized 2.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 – Nodes use their own addressing – Nodes can route requests to locations that may not be known by the requester

18. Overlay Network Example Circles represent nodes in the network. Blue nodes are also part of the overlay network. Dotted lines represent virtual links. Actual routing is based on TCP/IP protocols

19. Overlay Networks Are logical or virtual networks, built on top of a physical network A link between two nodes in the overlay may consist of several physical links. Messages in the overlay are sent to logical addresses, not physical (IP) addresses Various approaches used to resolve logical addresses to physical.

20. Types of P2P Systems The overlay network may be – Structured: Nodes and content are connected according to some design that simplifies later lookups – Unstructured: Content is assigned to nodes regardless of network topology Structured peer-to-peer system 1.Chord System 2.CAN System

21. 1. Chord system Assume there are 16 nodes Pears are located logically on the ring Use a distributed hash table to locate objects – Data item with key k goes to the node with the smallest id, id >= k 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

22. 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

23. Unstructured P2P Systems Unstructured P2P organizes the overlay network as a random graph. Topology is based on randomized algorithms – Each node pick a random set of nodes and becomes their neighbors Gnutella – Each node knows about a subset of nodes, its “neighbors” – Neighbors are chosen in different ways: physically close nodes, nodes that joined at about the same time, etc.

24. Locating a Data Object by Flooding Send a request to all known neighbors – If not found, neighbors forward the request to their neighbors Works well in small to medium sized networks, doesn’t scale well “Time-to-live” counter can be used to control number of hops Example system: Gnutella & Freenet (Freenet uses a caching system to improve performance)

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

26. Structured vs Unstructured Structured networks typically guarantee that if an object is in the network it will be located in a bounded amount of time – usually O(log(N)) Unstructured networks offer no guarantees. – For example, some will only forward search requests a specific number of hops – Random graph approach means there may be loops – Graph may become disconnected

27. B. System Architectures (1)Centralized, (2)decentralized, (3)hybrid (4)Middleware (aim is distribution transparency) (5)Self-managing systems (autonomic systems) – System Monitoring – Taking appropriate measures

28. B3. Hybrid Systems Client-server solutions are combined with decentralized architectures. Examples are 1.Edge-Server Systems 2.Collaborative Distributed Systems

29. 1.Edge-Server Systems Edge servers: From client-server to client-proxy-server Content distribution networks: Proxies cache web content near the edge

30. 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

31. B. System Architectures (1)Centralized, (2)decentralized, (3)hybrid (4) Middleware (aim is distribution transparency) (5)Self-managing systems (autonomic systems) – System Monitoring – Taking appropriate measures

32. B4. 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 Interceptors – Nothing but a software construct. That will break the usual flow and allow other code to be executed. – Generality or simplicity (ad-hoc)

33. Ex: Middleware for Object-based Appl

34. Adaptive Software/Computing Realized by using Middleware systems. 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 Supporting Adaptive Computing: 1.Separation of concerns (Aspect-oriented software/comp) 2.Computational Reflection (self inspection – ex: garbage collection in Java) 3.Component-based design (dynamic component composition – ex: late binding in programming languages)

35. B. System Architectures (1)Centralized, (2)decentralized, (3)hybrid (4) Middleware (aim is distribution transparency) (5)Self-managing systems (autonomic systems) – System Monitoring – Taking appropriate measures

36. B5. Self-Managing Systems Autonomic computing System is adaptive – Monitors itself and takes action autonomously when needed Self-*: self-managing, self-healing Example: automatic capacity provisioning – Vary capacity of a web server based on demand

37. Autonomic Computing: Self-* systems Examples: – Defining how many CPU cycles to which tasks – What is the right allocation of the resources – Monitor the system and if the workload start increasing add more server from the server pool If workload is decreasing, then shut some of them up On the fly system keeps changes and act accordingly Realization with Feedback control system

38. Summary Autonomic computing: – Self-managing systems Adaptive computing: – Adapting to continuously changing environments in which dist applications are executed. Aspect-oriented computing: – Separation of concerns

39. Back Up

40. Key of the concept is the separation of the infrastructure into building blocks (component-based design) Have dedicated resources for computing, storage, network and control – Aspect-oriented helps here Pool them and share them – if appropriate Adaptive Software/Computing

41. Autonomic computing

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