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UNIT-I

UNIT-I. UNIT-I Distributed Systems. ECS-701 Lecture Note NEERAJ KUMAR. Distributed Systems. What is a Distributed System? Tanenbaum and van Renesse : A distributed system is one that looks to its users like an ordinary, centralized, system but runs on multiple independent CPUs

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UNIT-I

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  1. UNIT-I

  2. UNIT-IDistributed Systems ECS-701 Lecture Note NEERAJ KUMAR CSE 380

  3. Distributed Systems • What is a Distributed System? • Tanenbaum and van Renesse: A distributed system is one that looks to its users like an ordinary, centralized, system but runs on multiple independent CPUs • Symptoms? Shroeder: • Multiple, independent processing units • Processors communicate via a hardware interconnect • Processing unit failures are independent • Manage resource sharing • State is shared among processors

  4. Distributed Systems, cont. Design Issues • Scaling • Communication • Coordination • Transparency • Naming • Load sharing • Consistency • Failures • Security • Heterogeneity • Mobility

  5. Advantages of Distributed Systems over Centralized Systems • Economics: a collection of microprocessors offer a better price/performance than mainframes. Low price/performance ratio: cost effective way to increase computing power. • Speed: a distributed system may have more total computing power than a mainframe. Ex. 10,000 CPU chips, each running at 50 MIPS. Not possible to build 500,000 MIPS single processor since it would require 0.002 nsec instruction cycle. Enhanced performance through load distributing. • Inherent distribution: Some applications are inherently distributed. Ex. a supermarket chain. • Reliability: If one machine crashes, the system as a whole can still survive. Higher availability and improved reliability. • Incremental growth: Computing power can be added in small increments. Modular expandability • Another deriving force: the existence of large number of personal computers, the need for people to collaborate and share information. CSE 380

  6. Advantages of Distributed Systems over Independent PCs • Data sharing: allow many users to access to a common data base • Resource Sharing: expensive peripherals like color printers • Communication: enhance human-to-human communication, e.g., email, chat • Flexibility: spread the workload over the available machines CSE 380

  7. Disadvantages of Distributed Systems • Software: difficult to develop software for distributed systems • Network: saturation, lossy transmissions • Security: easy access also applies to secrete data CSE 380

  8. Distributed kdAlgorithms Algorithms • Many processors • Faulty (crash, byzantine, etc.) • Communication over network • Concurrent: • One step at a time • Complexity: • Message complexity • Latency analysis • Examples: • Leader election • Consensus (Agreement) • Mutual exclusion (Dining Philosophers) • Atomic objects • One processor • Reliable (no faults) • No communication • Sequential: • One step at a time • Complexity: • Step complexity • Examples: • Sorting (Quicksort, Mergesort, Heapsort) • Searching (Binary search) • Matrix mult. (Strassen’s) • Primality testing

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