© Oxford University Press 2011 DISTRIBUTED COMPUTING Sunita Mahajan Seema Shah.
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Transcript of © Oxford University Press 2011 DISTRIBUTED COMPUTING Sunita Mahajan Seema Shah.
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© Oxford University Press 2011
DISTRIBUTED COMPUTING Sunita Mahajan
Seema Shah
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© Oxford University Press 2011
Chapter-1
Basic Distributed System Concepts
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What is a distributed system?
• Tanenbaum’s 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 coherent system.”
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An example of a Distributed System
• Nationalized Bank with multiple Branch Offices
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Requirements of Distributed systems
• Security and reliability.• Consistency of replicated data.• Concurrent transactions (operations which
involve accounts in different banks; simultaneous access from several users, etc)
• Fault tolerance
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Architectures for Distributed systems
• Shared memory architectures / Tightly coupled systems – easier to program
• Distributed memory architectures / Loosely coupled systems– offer a superior price performance ratio and are
scalable
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Architectures for Distributed systems
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Distributed Computing Models
• Workstation model• Workstation–server model • Processor-pool model
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Workstation model
• Consists of network of personal computers,• Each one with its own hard disk and local file
system • Interconnected over the network(diskful
workstation.
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workstation-server model
• Consists of multiple workstations coupled with powerful servers with extra hardware to store the file systems and other software like databases(diskless workstations.)
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processor-pool model
• consists of multiple processors: a pool of processors and a group of workstations
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Advantages of Distributed systems• Inherently distributed applications• Information sharing among geographically
distributed users• Resource Sharing• Better price performance ratio• Shorter response time & higher
throughput• Higher reliability and availability against
component failures• Extensibility and Incremental Growth• Better Flexibility
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Disadvantages of Distributed systems
• Relevant software does not exist currently• Security poses a problem due to easy access
to all data• Networking saturation may cause a hurdle in
data transfer.
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Software concepts
• Network Operating System (NOS)• Distributed Operating System (DOS)• Multiprocessor Time Sharing System
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Network Operating System (NOS)
• Build using a distributed system from a network of workstations connected by high speed network.
• Each workstation is an independent computer with its own operating system, memory and other resources like hard disks, file system and databases
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Distributed Operating System (DOS)
• Enables a distributed system to behave like a virtual uniprocessor even though the system operates on a collection of machines.
• Characteristics – enabling Inter process communication, – Uniform process management mechanism,– Uniform and visible file system, – Identical kernel implementation, – Local control of machines – handling scheduling issues.
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Multiprocessor Time Sharing System
• Combination of tightly coupled software and tightly coupled hardware with multiple CPUs projecting a uniprocessor image.
• Tasks are queued in shared memory and are scheduled to be executed in time shared mode on available processors.
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Comparison of different Operating systems
Software Concepts
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Issues in Designing Distributed systems
• Transparency• Flexibility• Reliability• Performance• Scalability• Security
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Transparency
Transparencies required for Distributed Systems
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Replication Transparency
Locating Replicated File stored on any server
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Flexibility
• Monolithic kernel approach • Microkernel approach
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Monolithic kernel approach
• uses the minimalist , modular approach with accessibility to other services as needed.
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Microkernel approach
• uses the kernel does it all approach with all functionalities provided by the kernel irrespective whether all machines use it or not
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Monolithic versus Microkernel Approach
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Reliability
• Availability in case of Hardware failure • Data recovery in case of Data failure• Maintain consistency in case of replicated data
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Performance
Metrics are:• Response time, • Throughput, • System utilization • Amount of network capacity used
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Scalability
• Techniques to handle scalability issues – hide communication latencies, – hide distribution – hide replication
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Hide communication latencies,
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Hide distribution
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Security
• confidentiality means protection against unauthorized access;
• integrity implies protection of data against corruption
• availability means protection against failure always accessible.
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Client Server model
Client Server Interaction
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Client Server addressing techniques
• Machine addressing, • process addressing • Name server addressing
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Client Server addressing techniques
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Client Server implementation
• Messages for client server interaction– Request, Reply, Acknowledge, Are you Alive, I am
Alive.
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differentiation between the client and the server
• User interface level• Processing level• data level
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Client Server Architecture
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Case Study: World Wide Web 1.0
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Internet scenario with web servers and web browsers
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Case study: World Wide Web 2.0
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Case Study: Google Servers
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Summary
• Multiple-interconnected computers can have either shared memory or distributed memory architectures
• Distributed systems offer integration of distributed applications, resource sharing, more reliability, better flexibility
• Network operating system, distributed operating system and multiprocessor timesharing system are different types of distributed systems