1. D ISTRIBUTED S YSTEMS – A RCHITECTURE M ODELS Janani C Krishnamani CSC 8320 Fall 2011

2. O UTLINE Introduction Architecture models System architectures Communication Network architectures Examples Future Ideas

3. I NTRODUCTION

4. W HAT ARE DISTRIBUTED SYSTEMS ? Collection of independent computers that appear to the user as one single entity Examples Systems in a LAN, WAN, MAN World Wide Web Torrent networks Clusters Cloud servers

5. W HY INTERCONNECT SYSTEMS ? [1] To pass a message from one system to another Share common resources Beneficial to use multiple low end processors than one high end processor Fault tolerance through redundancy

6. C LASSIFICATION

7. C LASSIFICATION [2] Based on system architecture Client – Server model Peer – Peer model Based on communication network Bus Switched Based on level of coupling Tightly coupled (parallel) Loosely coupled (distributed)

8. B ASED ON S YSTEM A RCHITECTURE : C LIENT S ERVER M ODEL One server acts as the principal control agent Several nodes report to the server Advantages: Better control and security Concentration of functions in high performance servers Disadvantages: Not robust due to lack of redundancy Performance suffers if the number of clients increases Examples: Workstation – Server Model Processor Pool Model

9. B ASED ON S YSTEM A RCHITECTURE : W ORKSTATION – S ERVER M ODEL Many workstations connect to the network. Workstations provide local processing and an interface to the network. Consist of one or more client workstations connected to one or more server workstations using a communication network. Mainly used for resource sharing

10. B ASED ON S YSTEM A RCHITECTURE : P ROCESSOR P OOL M ODEL All the processing is moved to a pool of processors No concept of a home machine Workstations are dummy terminals with good graphical display Terminals have minimum intelligence like remote booting, remote mounting of file systems, virtual terminal handling and packet assembly and disassembly services

11. B ASED ON S YSTEM A RCHITECTURE : P EER – P EER M ODEL All the nodes in the network have equal privilege No special routing server required. The nodes themselves take care of routing the data Peers – both suppliers and consumers As the number of nodes increases, the bandwidth increases Reduces single point failures It is less secure Usually used for sharing of resources – files, audio - visual media

12. B ASED ON C OMMUNICATION N ETWORK : B US – B ASED I NTERCONNECTION Usually used in Point – Point connection systems System connected by computer bus The access to communication media is time shared IEEE 802 LAN Standard Ethernet, Token Bus, Token Ring, Fiber Distributed data Interface (FDDI), Fiber Queue Dual Buses (FQDB)

13. B ASED ON C OMMUNICATION N ETWORK : S WITCH – B ASED I NTERCONNECTION Usually used in multi point connection systems Systems connected by network switches The access to communication media is both time and space shared – but cost equally higher than bus Private switches – Crossbar, multistage switch Public switch systems – Integrated Services Digital Network (ISDN), Asynchronous Transfer Mode (ATM Switches in public networks also perform routing

14. B ASED ON L EVEL OF C OUPLING : L OOSELY C OUPLED S YSTEMS Each processor has its own memory Runs its own OS Do not communicate frequently Can be placed in geographically separate regions Also called distributed computing

15. B ASED ON L EVEL OF C OUPLING : T IGHTLY C OUPLED S YSTEMS Processors share a common memory Run on a single OS Communicate very frequently Usually connected through high speed connection methods Also called parallel computing

16. L EVEL OF C OUPLING Microprocessors ClustersLANGlobal Internet Small Fast Large Slow More Tightly CoupledMore Loosely Coupled Closer in physical proximityFarther in physical proximity

17. G RID C OMPUTING [3] Complete nodes connected by a conventional network interface like Ethernet. Not tightly coupled. Can be geographically diverse. The communication is not high speed - works fine in environments that require less communication. A single task is adequately parallelized and each part is given to a different node that computes it independently - so no concurrency issues involved.

18. C LOUD C OMPUTING

19. W HAT IS C LOUD C OMPUTING [4] Parallel and distributed system consisting of a collection of inter-connected and virtualized computers Presented to the user as a single computer Services provided: Software as service Platform as service Infrastructure as service Advantages Speed of Operation Power saving Abstraction Virtualization

20. E XAMPLES

21. F OLDING @H OME [6] Grid computing project designed to perform computationally intensive simulations of protein folding and other molecular dynamics The most powerful distributed computing cluster in the world – Guinness 2007 Primary contributors – thousands of everyday personal computers Processes run in the background utilizing cpu idle time In late March 2011 Folding@home briefly peaked above the 7 native petaFLOP barrier.

22. W INDOWS A ZURE P LATFORM [7] On demand platform used to build, host and scale web applications through windows datacenter. Platform as a service Build, host and maintain web applications running on Microsoft Datacenter OS – Windows Azure Services Live Services SQL Azure AppFabric SharePoint Services Dynamic CRM Services

23. F UTURE …

24. F UTURE OF D ISTRIBUTED C OMPUTING … An expanded peer - peer network with every personal computer interconnected with every other. Utilization of CPU cycles and hard disks during idle time Improvements in security and performance that void the need for a centralized control server and a data center

25. R EFERENCES [1] http://en.wikipedia.org/wiki/Distributed_computi ng#Architectures http://en.wikipedia.org/wiki/Distributed_computi ng#Architectures [2] http://en.wikipedia.org/wiki/Grid_computinghttp://en.wikipedia.org/wiki/Grid_computing [3] http://en.wikipedia.org/wiki/Cloud_computinghttp://en.wikipedia.org/wiki/Cloud_computing [4] Ghosh, Anup; Arce, Ivan;, "Guest Editors' Introduction: In Cloud Computing We Trust - But Should We?," Security & Privacy, IEEE, vol.8, no.6, pp.14-16, Nov.-Dec. 2010 doi: 10.1109/MSP.2010.177 [5] http://en.wikipedia.org/wiki/Folding@Homehttp://en.wikipedia.org/wiki/Folding@Home [6] http://en.wikipedia.org/wiki/Blue_Gene/http://en.wikipedia.org/wiki/Blue_Gene/ [7] http://en.wikipedia.org/wiki/Windows_Azurehttp://en.wikipedia.org/wiki/Windows_Azure

26. T HANK Y OU !