Chapter 1 -_characterization_of_distributed_systems
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The document defines a distributed system and provides examples. It outlines the challenges in designing distributed systems, including heterogeneity, openness, security, scalability, failure handling, concurrency, and transparency. Distributed systems divide tasks across networked computers and aim to appear as a single computer to users.
![Definition of A Distributed System
“A distributed system is a collection of independent
computers that appear to the users of the system as a
single computer.” [Tanenbaum]
“A distributed system is a collection of autonomous
computers linked by a network with software designed
to produce an integrated computing facility.”
[Coulouris, Dollimore, Kindberg]
“A system of multiple autonomous processing
elements, cooperating in a common purpose or to
achieve a common goal.” [Burns & Wellings 1997]](https://image.slidesharecdn.com/chapter1-characterizationofdistributedsystems-130618004821-phpapp02/85/Chapter-1-_characterization_of_distributed_systems-5-320.jpg)
Chapter 1 -_characterization_of_distributed_systems
- 1. chapter 1
- 2. Objectives To define what is a distributed system To know the consequences of the definition To identify the challenges in designing and building a distributed system
- 3. Chapter Outlines Introduction Examples of Distributed Systems Challenges of Distributed Systems
- 4. ♦ Data are Distributed » If data must exist in multiple computers for admin and ownership reasons ♦ Computation is Distributed » Applications taking advantage of parallelism, multiple processors, » particular feature » Scalability and heterogeneity of Distributed System ♦ Users are Distributed » If Users communicate and interact via application (shared objects)
- 5. Definition of A Distributed System “A distributed system is a collection of independent computers that appear to the users of the system as a single computer.” [Tanenbaum] “A distributed system is a collection of autonomous computers linked by a network with software designed to produce an integrated computing facility.” [Coulouris, Dollimore, Kindberg] “A system of multiple autonomous processing elements, cooperating in a common purpose or to achieve a common goal.” [Burns & Wellings 1997]
- 6. ”A system that consists of a collection of two or more independent computers, that are connected by a network, which coordinate their processing through the exchange of synchronous or asynchronous message passing. They may be on separate continents, in the same building or the same room”. Definition from our textbook
- 8. Introduction Motivation for A Distributed System Load balancing / distribution breaking a problem into smaller pieces enables you to solve larger problems without resorting to larger computer MAINFRAME – 10 X faster but 1000 X expensive Increased Processing Power independent processors working on the same task Distributed systems consisting of collections of microcomputers may have processing powers that no single computer will ever achieve 10000 CPUs, each running at 50 MIPS, yields 500000 MIPS instruction to be executed in 0.002 nsec equivalent to light distance of 0.6 mm any processor chip of that size would melt immediately
- 9. Introduction Motivation for A Distributed System Fault tolerance If any of the machine gets down, others can still run Availability Anytime, anywhere access Resource sharing All clients can be server or vice versa to provide resources (data, files, services) The main motivator for DS
- 10. Examples
- 12. Examples Source : http://www.girardin.org/fabien/blog/wp-content/mobile_computing_30s.png Distributed Computing
- 14. Challenges in Distributed System Distributed Computing
- 15. Challenge: Heterogeneity Heterogeneity = variety and difference Heterogeneity of underlying network infrastructure (ethernet, ISDN, token ring etc), computer hardware and software (e.g., operating systems, compare UNIX sockets and Winsock calls), programming languages (java, C, python : in particular, data representations), implementations by different developers Heterogeneity needs to be masked Distributed Computing
- 16. determines whether the system can be extended and re-implemented in various ways Determined primarily by the degree to which new resource-sharing services can be added and be made available for use by variety of client programs Detailed interfaces of components need to be standardized and published. Challenge: Openness Distributed Computing
- 17. Security for information resources has three components: Confidentiality protection against disclosure to unauthorized individuals Integrity protection against alteration or corruption Availability protection against interference with the means of accessing the resources The challenge: sending sensitive information in a network message in a secure manner efficiently Not just to conceal the info but to ensure that the sender and recipients are the rightful owners of the messages Challenge: Security Distributed Computing
- 18. Challenge: Scalability A distributed system is scalable if it remains effective as the number of users and/or resources increase Challenges: Controlling resource costs Controlling performance loss Preventing resources from running out Avoiding performance bottlenecks Distributed Computing
- 19. Challenge: Failure Handling Failures more common than in centralized systems and usually partial Failure handling includes Detection (may be impossible) Masking/hiding Tolerance Recovery Redundancy Distributed Computing
- 20. Challenge: Failure Handling Detection Some possible (e.g., using transmission errors via checksums) Some impossible (crashed remote server vs. slow remote server) Challenge: manage failures that cannot be detected, but suspected Distributed Computing
- 21. Challenge: Failure Handling Masking/hiding Some failures can be hidden or made less severe Replication in space/time Space: e.g., writing to multiple disks Time: e.g., transmission of multiple messages May not work in worst cases, e.g., all disks may have been corrupted Distributed Computing
- 22. Challenge: Failure Handling Tolerance Sometimes not feasible to hide all failures E.g., user has to tolerate if web service has failed rather than wait until service is up again Only feasible for certain classes of applications/systems, e.g., DNS vs. Internet addresses Recovery Restoring a correct system state Roll back using log files Distributed Computing
- 23. Challenge: Failure Handling Redundancy Tolerate failures by using redundant components Provided through replication E.g., redundant routes in network, replication of name tables in multiple domain name servers Goal of failure handling: high availability availability of a system is a measure of the proportion of time that the system is available for use Distributed Computing
- 24. Challenge: Concurrency Concurrency control Handling several simultaneous requests for a resource Consistent scheduling of concurrent threads (so that dependencies are preserved, e.g., in concurrent transactions) Synchronized operations (semaphores) Safest, but limits throughput Shared objects/resources must guarantee correctness in a concurrent environment Avoidance of deadlocks Distributed Computing
- 25. Challenge: Transparency Concealing the heterogeneous and distributed nature of the system so that it appears to the user like one system Eight types (ANSA/ISO) access, location, concurrency, replication, failure, mobility, performance and scaling transparencies Distributed Computing
- 26. Challenge: Transparency •Access transparency: •enables local and remote resources to be accessed using identical operations. For instance, from a user's point of view, access to a remote service such as a printer should be identical with access to a local printer. From a programmers point of view, the access method to a remote object may be identical to access a local object of the same class. •E.g., Same user interface and operations offered in order to access either local or remote resources Distributed Computing
- 27. Challenge: Transparency •Location transparency: •enables resources to be accessed without knowledge of their location. •The details of the topology of the system should be of no concern to the user. •The location of an object in the system may not be visible to the user or programmer. •This differs from access transparency in that both the naming and access methods may be the same. Names may give no hint as to location. •E.g., URL or e-mail addresses. • www.google.com (IP address is the physical location) Distributed Computing
- 28. Challenge: Transparency •Concurrency transparency: •enables several processes to operate concurrently using shared resources without interference between them. •E.g., no conflict occur when 2 or more users accessing the same system Distributed Computing
- 29. Challenge: Transparency •Replication transparency: •enables multiple instances of resources to be used to increase reliability and performance without knowledge of the replicas by users. •This kind of transparency should be mainly incorporated for the distributed file systems, which replicate the data at two or more sites for more reliability. The client generally should not be aware that a replicated copy of the data exists. The clients should also expect operations to return only one set of values. •The examples are Distributed DBMS and Mirroring of Web pages. •Failure transparency: •enables the concealment of faults, allowing users and application programs to complete their tasks despite the failure of hardware or software components. •E.g., retransmission of e-mail messages •Mobility transparency: •allows the movement of resources and clients within a system without affecting the operation of users or programs.Distributed Computing
- 30. Challenge: Transparency •Mobility transparency: •allows the movement of resources and clients within a system without affecting the operation of users or programs. •E.g., caller and callee undergoing different places while on the phone Distributed Computing
- 31. Challenge: Transparency •Performance transparency: •allows the system to be reconfigured to improve performance as loads vary. •Eg:Video On Demand (VOD) System •Scaling transparency: •allows the system and applications to expand in scale without change to the system structure or the application algorithms. •Eg: P2P apps Distributed Computing
- 32. Transparency Description Access Hide differences in data representation and how a resource is accessed Location Hide where a resource is located Migration Hide that a resource may move to another location Relocation Hide that a resource may be moved to another location while in use Replication Hide that a resource may be replicated Concurrency Hide that a resource may be shared by several competitive users Failure Hide the failure and recovery of a resource Persistence Hide whether a (software) resource is in memory or on disk
- 33. 1. Name a program that is using distributed computing and freely available to the masses 2. Name 1 research field that is relying heavily on distributed computing
- 34. Summary A distributed system is a collection of independent and autonomous computers that appear to the users of the system as a single computer.” Based on the above definition, there are three significant consequences : Concurrency No global clock Independent failures Several challenges need to be addressed in designing and building DS Heterogeneity, openness, security, scalability, failure handling, concurrency and transparency. Distributed Computing