Introduction to distributed system
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A distributed system is a collection of independent computers that appears to users as a single coherent system. The document defines a distributed system and discusses its goals, including making resources accessible, achieving distribution transparency, openness, scalability, fault tolerance, concurrency, and security. Examples of distributed systems include distributed computing systems like cluster and cloud computing, distributed information systems, and distributed pervasive systems.
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Distributed system notes unit I
Distributed computing system is a collection of interconnected computers that appear as a single system. There are two types of computer architectures for distributed systems - tightly coupled and loosely coupled. In tightly coupled systems, processors share a single memory while in loosely coupled systems, processors have their own local memory and communicate through message passing. Distributed systems provide advantages like better price-performance ratio, resource sharing, reliability, and scalability but also introduce challenges around transparency, communication, performance, heterogeneity, and fault tolerance.
distributed shared memory
Distributed shared memory (DSM) provides processes with a shared address space across distributed memory systems. DSM exists only virtually through primitives like read and write operations. It gives the illusion of physically shared memory while allowing loosely coupled distributed systems to share memory. DSM refers to applying this shared memory paradigm using distributed memory systems connected by a communication network. Each node has CPUs, memory, and blocks of shared memory can be cached locally but migrated on demand between nodes to maintain consistency.
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This document provides an introduction to distributed systems, including definitions, goals, challenges, and examples. It defines a distributed system as a collection of independent computers that appear as a single system to users. The main goals are resource sharing, transparency, openness, and scalability. Some challenges include unreliable networks and false assumptions about network properties. Examples discussed include cluster computing, grid computing, transaction processing systems, sensor networks, and electronic health care systems.
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This document discusses distributed operating systems. A distributed OS connects multiple computers via communication channels to distribute processing jobs between central processors. It consists of nodes joined by networks that enable sharing of computing resources and files while providing users with virtual machines. The document describes types of distributed OS like client-server and peer-to-peer, and features like openness, resource sharing, transparency, and flexibility. Examples of distributed OS mentioned are Solaris, OSF/1, Micros, and DYNIX.
Chapter 1 introduction
The document introduces distributed systems, defining them as collections of independent computers that appear as a single system to users, discusses the goals of transparency, openness, and scalability in distributed systems, and describes three main types - distributed computing systems for tasks like clustering and grids, distributed information systems for integrating applications, and distributed pervasive systems for mobile and embedded devices.
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Introduction to distributed system
- 1. Definition of a Distributed System • A distributed system is: A collection of independent computers that appears to its users as a single coherent system. • User Programmer User Application Program Isha Padhy, Department of CSE
- 2. Definition of a Distributed System A distributed system organized as middleware. The middleware layer extends over multiple machines, and offers each application the same interface. Isha Padhy, Department of CSE
- 3. 2.2 Examples of distributed systems Isha Padhy, Department of CSE
- 4. GOALS • Making Resources accessible • Distribution Transparency • Openness • Scalability • Fault Tolerance • Concurrency • Security Isha Padhy, Department of CSE
- 5. Making Resources Available • Positivity: Allow user to access remote resources in controlled and efficient way. - Save high cost - Connecting users and resources whether existing or virtually - Easy availability of products. • Negativity: Intrusion Security Encrypted Passwords Tracking communications Isha Padhy, Department of CSE
- 6. Distributed Transparency 2. Degree of Transparency 1. Type of Transparency Isha Padhy, Department of CSE
- 7. Openness - Easy to add new components or replace existing ones - Portability of applications - Component should provide optimal policy for a user Isha Padhy, Department of CSE
- 8. Scalability • Adapted to change in components • Two types - Vertical - Horizontal • Measured in 3 ways - w.r.t. size - Geographically - Administrative Isha Padhy, Department of CSE
- 9. Scalibilty Problems • W.r.t. size: - services are centralized • Geographically: - Communication in LAN, WAN • Administrative: - Conflict in policies - DS has to protect against malicious attacks from new domain - New domain has to protect itself against DS. Isha Padhy, Department of CSE
- 10. Scaling Techniques • Hiding Communication latencies • Distribution: split the components • Replication: helps to balance the loadIsha Padhy, Department of CSE
- 11. Fault Tolerance • 3 kinds of problems (fault, errors, failures) • Types of faults(Transient, Intermittent, permanent) • Fault Tolerance • Steps of fault tolerance - Fault detection - Fault diagnosis - Assessment - Recovery - Redundancy Isha Padhy, Department of CSE
- 12. Security • 3 components - Confidentiality: keeping secret. - Integrity: protection against alteration. - Availability: protection against interference. • Identification of the user • Security challenges - Denial of service attack - Security of mobile code Isha Padhy, Department of CSE
- 13. Trends in DS • Distributed computing systems: used for high performance computing task. - Cluster computing: Underlying components are simple and similar. - Cloud computing: Relies on sharing of resources - Grid computing: Run an application on different machines. Isha Padhy, Department of CSE
- 14. • Distributed Information systems(EPI): - Transaction Processing system: captures, enters, stores, retrieves the relevant details of business events and generates information required. - Enterprise application integration: moderning and co-ordinating applications. • Distributed pervasive systems: Embedding microprocessors in everyday objects. Isha Padhy, Department of CSE