EEC-681/781 Distributed Computing Systems

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EEC-681/781Distributed Computing Systems

• Lecture 3
• Wenbing Zhao
• Department of Electrical and Computer Engineering
• Cleveland State University
• wenbing_at_ieee.org

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Outline

• Mock quiz
• Techniques for scaling
• Middleware
• Distributed system models
• Fundamental model

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Techniques for Scaling

• Hiding communication latencies
• Distribution
• Replication

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Hiding Communication Latencies

• Applicable to geographical scalability
• Technique 1 Avoid waiting for responses to
  remote service requests
• Use asynchronous communication style
• Technique 2 Reduce the overall communication by
  moving part of the computation from server to
  client
• Code/process migration

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Scaling by Distribution

• Distribution Partition data and computations
  across multiple machines
• Examples Domain name services (DNS)
• DNS name space is hierarchically organized into a
  tree of domains, which are divided into
  nonoverlapping zones

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Decentralized Naming Service
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Scaling by Replication

• Replication Make copies of data available at
  different machines across the distributed system
• Examples
• Replicated file servers
• Replicated databases
• Mirrored Web sites
• Large-scale distributed shared memory systems

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Scaling by Replication

• Replication Benefits
• Increasing availability
• Load balancing
• Increasing the geographical scalability by
  placing a copy nearby different users

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Problem with Scaling by Replication

• Having multiple copies might leads to
  inconsistencies
• Modifying one copy makes that copy different from
  the rest
• Always keeping copies consistent and in a general
  way requires global synchronization on each
  modification
• Global synchronization precludes large-scale
  solutions
• Global synchronization is needed to minimize
  inconsistencies

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Scaling by Caching

• Caching A special form of replication. It allows
  client processes to access local copies
• Web caches (browser/Web proxy)
• File caching (at server and client)
• Similarity to replication making a copy of a
  resource, generally in the proximity of the
  client accessing that resource
• Difference from replication caching is a
  decision made by the client of a resource, not by
  the owner of the resource

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Middleware

• Middleware
• Position in between a distributed application
  and operating system
• Functionality it provides common services for
  distributed computing
• Implementation it incorporates lots of
  distributed systems design principles

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Why Middleware

• Better productivity
• Quicker implementation of business logic because
  you dont worry many low level distributed
  computing issues
• Better performance
• Middleware is written by experts
• Better interoperability, extensibility, etc.
• Better security

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Middleware Services

• Many middleware systems offer a more-or-less
  complete collection of services and discourage
  using anything else but their interfaces to those
  services

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Middleware Services

• Communication services Abandon primitive socket
  based message passing in favor of
• Procedure calls across networks
• Remote-object method invocation
• Message-queuing systems
• Advanced communication streams
• Event notification service

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Middleware Services

• Information system services help manage data in
  a distributed system
• Large-scale, system-wide naming services
• Advanced directory services (search engines)
• Location services for tracking mobile objects
• Persistent storage facilities
• Data caching and replication

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Middleware Services

• Control services Giving applications control
  over when, where, and how they access data
• Distributed transaction processing
• Code migration
• Security services Secure processing and
  communication
• Authentication and authorization services
• Simple encryption services
• Auditing service

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Distributed System Models

• Fundamental models
• Concerned with a more formal description of the
  properties that are common to all of the
  architectural models
• Architectural models
• Concerned with the placement of its parts and the
  relationships between them

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Fundamental Models

• Interaction Models
• Synchronous distributed systems
• Asynchronous distributed systems
• Failure Models
• Timing faults
• Process faults
• Security Models
• Protecting process
• Protecting communication channels
• Protecting objects against authorized access

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Common Properties on Interactions

• Communications over computer networks
• Latency, throughput, jitter
• Synchronization of distributed processes
• No global time, each machine has its own viewof
  time
• As a result, cannot fully control process
  execution, message delivery, clock drift

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Synchronous Distributed Systems

• Definition
• Time to execute each step of a process has known
  lower and upper bounds
• Each message transmitted over a channel is
  received within a known bounded time
• Each process has a local clock whose drift rate
  from real time has a known bound

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Synchronous Distributed Systems

• How to build one
• For each task, guaranteed sufficient resources
  being allocated, e.g., processor cycles and
  network bandwidth
• Clocks with bounded drift rates

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Asynchronous Distributed Systems

• Definition
• Unbounded time to execute each step of a process
• Unbounded message transmission
• Unbounded clock drift rates from real time

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Asynchronous Distributed Systems

• Actual systems are very often asynchronous
  because of the need for sharing of processors and
  network
• Protocols designed for asynchronous systems can
  be used in any system

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Impossibility Results

• In an asynchronous distributed system, processes
  cannot reach consensus with even one process
  failure
• One cannot distinguish a failed node from a slow
  one
• Implications Perfect Common knowledge is not
  achievable in an asynchronous distributed system