Presentation is loading. Please wait.

Presentation is loading. Please wait.

Meng Han Presentation 09/11/2013 CS8320 – Advanced Operating Systems Fall 2013 – Section 2.6 Presentation.

Similar presentations


Presentation on theme: "Meng Han Presentation 09/11/2013 CS8320 – Advanced Operating Systems Fall 2013 – Section 2.6 Presentation."— Presentation transcript:

1 Meng Han Presentation 09/11/2013 CS8320 – Advanced Operating Systems Fall 2013 – Section 2.6 Presentation

2 Outline IIntroduction DDistributed System Design Issues Object Models and Naming Schemes Distributed Coordination Interprocess Communication Distributed Resources Fault Tolerance and Security DDesign for big-data SSummary RReferences

3 Introduction  A distributed system mainly consists[1]:  Coordination of concurrent distributed processes  Management of distributed resources  Functioning of distributed algorithms  However…  Network may beUNRELIABLE  Components may beUNTRUSTED  These raise the design and implementation issues, in particular how to support transparency.

4 Introduction  design and implementation issues: How to model and identify objects in system How to co-ordinate the interaction among objects How to communicate with each other How to shared/replicated objects be managed in controlled fashion How to protect objects and security of system

5 Outline IIntroduction DDistributed System Design Issues Object Models and Naming Schemes Distributed Coordination Interprocess Communication Distributed Resources Fault Tolerance and Security DDesign for big-data SSummary RReferences

6 Object Models and Naming Schemes  Objects in a computer system:  processes, data files, memory, devices, processors, and networks.  Objects are encapsulated in servers  process servers, file servers, memory servers etc.  a client is a null server that accesses object servers.

7 Object Models and Naming Schemes  Identify a server[2]  by name ( name server )  by either physical or logical address ( network server )  by service that the servers provide  Following all depend on the naming scheme for system objects:  Structure of the system, management of name space, name resolution, access methods

8 Outline IIntroduction DDistributed System Design Issues Object Models and Naming Schemes Distributed Coordination Interprocess Communication Distributed Resources Fault Tolerance and Security DDesign for big-data SSummary RReferences

9 Distributed Coordination  Coordination to achieve synchronization  Different types of synchronization:  Barrier synchronization Process must reach a common synchronization point before they can continue  Condition coordination process must wait for a condition that will be set asynchronously by other interacting processes to maintain some ordering of execution  Mutual exclusion Concurrent processes must have mutual exclusion when accessing a critical shared resource

10 Synchronization Issues  State information sent by messages:  Typically only partial state information is known about other processes making synchronization difficult.  Information not current due to transfer time delay.  Decision if process may continue must rely on a message resolution protocol.  Centralized Coordinator: Central point of failure  Deadlocks[3]  Circular Waiting for the other process  Deadlock detection and recovery strategies

11 Synchronization Issues  Deadlocks  Four conditions must hold for deadlock to occur Exclusive use Hold and wait No preemption Cyclical wait  The problem of deadlocks can be handled in following ways  Prevention, avoidance and detection

12 Deadlock Prevention  Schemes that guarantee the deadlocks can never happen because of the way the system is structured.  One of the four conditions is prevented, thus preventing deadlocks.  For example, to impose an order on the resources and require processes to request resources in increasing order. This prevents cyclical wait and thus makes deadlocks impossible.

13 Outline IIntroduction DDistributed System Design Issues Object Models and Naming Schemes Distributed Coordination Interprocess Communication Distributed Resources Fault Tolerance and Security DDesign for big-data SSummary RReferences

14 Interprocess Communication  Lower level:  Interprocess communication can be accomplished by using simple message passing primitives.  Higher level:  logical communication methods provides the transparency:  Hide the physical details of message passing  Two important concepts : The client/server model Remote Procedure Call (RPC)

15 The Client/Server Model  The client/ server model is a programming example for structuring processes in distributed systems[4]. logical communication request reply actual communication network client server kernel

16 The RPC Model  The remote procedure call model is similar to that of the local model:  The caller places arguments to a procedure in a specific location (such as a result register).  The caller temporarily transfers control to the procedure.  When the caller gains control again, it obtains the results of the procedure from the specified location.  The caller then continues program execution.

17 The RPC Model  On the server side, a process is dormant (inactive, sleeping)—  Awaiting the arrival of a call message.  When one arrives, the server process computes a reply that it then sends back to the requesting client.  After this, the server process becomes dormant again.

18 The RPC Model

19 Outline IIntroduction DDistributed System Design Issues Object Models and Naming Schemes Distributed Coordination Interprocess Communication Distributed Resources Fault Tolerance and Security DDesign for big-data SSummary RReferences

20 Distributed Resources  Load Distribution  multiprocessor scheduling (Static)  load sharing (Dynamic)  Distributed shared memory  Distributed file systems

21 Load Distribution  Multiprocessor scheduling[5]  Minimize communication overhead with efficient scheduling.  Load sharing  Process migration strategy & mechanism

22 Distributed File Systems and Distributed Shared Memory  Distributed file systems  Issues are based on a file point of view  Distributed shared memory  Issues are based on a process perception of the system.  The common issues central to them:  Sharing and replication of data

23 Outline IIntroduction DDistributed System Design Issues Object Models and Naming Schemes Distributed Coordination Interprocess Communication Distributed Resources Fault Tolerance and Security DDesign for big-data SSummary RReferences

24 Fault Tolerance and Security  Security threats and failures are both system faults.  The problem of failures can be alleviated if there is redundancy in the system.  The system should transparently handle failures or removal of machines, network links, and other resources without loss of data or functionality.  This should hold true for both the system itself and for its applications.

25 Fault Tolerance and Security  Security[6]  Authentication -- clients and also servers and messages must be authenticated.  Authorization -- access control has to be performed across a physical network with heterogeneous components under different administrative units using different security models.

26 Outline IIntroduction DDistributed System Design Issues Object Models and Naming Schemes Distributed Coordination Interprocess Communication Distributed Resources Fault Tolerance and Security DDesign for big-data SSummary RReferences

27 Design for BIG-DATA  Emergence of Big Data  Big data is a foundational element of social networking and Web 2.0-based information companies. The enormous amount of data is generated as a result of democratization and ecosystem factors such as the following:  Mobility trends  Data access and consumption  Ecosystem capabilities

28 Design for BIG-DATA  Mobility trends:  Mobile devices, mobile events and sharing, and sensory integration  Data access and consumption:  Internet, interconnected systems, social networking, and convergent interfaces and access models  Ecosystem capabilities:  Major changes in the information processing model and the availability of an open source framework; the general-purpose computing and unified network integration

29 Design for BIG-DATA

30 Outline IIntroduction DDistributed System Design Issues Object Models and Naming Schemes Distributed Coordination Interprocess Communication Distributed Resources Fault Tolerance and Security DDesign for big-data SSummary RReferences

31 Summary  Given the system architectures, we summarized the important design and implementation issues.  These issues include object models and naming schemes, interprocess communication and synchronization, data sharing and replication, and failure and recovery.  These problems are unique to distributed systems.

32 References [1]Randy Chow & Theodore Johnson, 1997, “Distributed Operating Systems & Algorithms”, (Addison-Wesley), p. 45 to 50, 61 to 63. [2] Suresh Sridharan, 2006, “Distributed Operating Systems”, (University of Wisconsin, Madison). 9/Writeups/Survey.pdf [3] Chandy, K. Mani, Jayadev Misra, and Laura M. Haas. “Distributed deadlock detection.” ACM Transactions on Computer Systems (TOCS) 1.2 (1983):

33 References [4] Holliday, J., and Amr El Abbadi. “Distributed deadlock detection.” Encyclopedia of Distributed Computing. Kluwer Academic Publishers, Dordrecht (accepted for publication) (2005). [5] Babaoglu, Ozalp, and Keith Marzullo. “Consistent global states of distributed systems: Fundamental concepts and mechanisms.” Distributed Systems 2 (1993): 12. [6] Krishna Sankar, Andrew Balinsky, Darrin Miller, Sri Sundaralingam. (Feb 18, 2005)“EAP Authentication Protocols for WLANs”.

34 References [7] Bohlouli, Mahdi, et al. “Towards an Integrated Platform for Big Data Analysis.”Integration of Practice-Oriented Knowledge Technology: Trends and Prospectives. Springer Berlin Heidelberg, [8] Wolf, Marilyn. “Computers as components: principles of embedded computing system design.” Access Online via Elsevier, [9] Provost, Foster, and Tom Fawcett. “Data Science and its Relationship to Big Data and Data-Driven Decision Making.” Big Data 1.1 (2013):

35 VISA LEADER


Download ppt "Meng Han Presentation 09/11/2013 CS8320 – Advanced Operating Systems Fall 2013 – Section 2.6 Presentation."

Similar presentations


Ads by Google