Distributed%20Operating%20Systems%20CS551

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Distributed Operating SystemsCS551

• Colorado State University
• at Lockheed-Martin
• Lecture 3 -- Spring 2001

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CS551 Lecture 3

• Topics
• Real Time Systems (and networks)
• Interprocess Communication (IPC)
• message passing
• pipes
• sockets
• remote procedure call (RPC)
• Memory Management

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Real-time systems

• Real-time systems
• systems where the operating system must ensure
  that certain actions are taken within specified
  time constraints Chow Johnson, Distributed
  Operating Systems Algorithms, Addison-Wesley
  (1997).
• systems that interact with the external world in
  a way that involves time When the answer is
  produced is as important as which answer is
  produced. Tanenbaum, Distributed Operating
  Systems, Prentice-Hall (1995).

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Real-time system examples

• Examples of real-time systems
• automobile control systems
• stock trading systems
• computerized air traffic control systems
• medical intensive care units
• robots
• space vehicle computers (space ground)
• any system that requires bounded response time

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Soft real-time systems

• Soft real-time systems
• missing an occasional deadline is all right
  Tanenbaum, Distributed Operating Systems,
  Prentice-Hall (1995).
• have deadlines but are judged to be in working
  order as long as they do not miss too many
  deadlines Chow Johnson, Distributed Operating
  Systems Algorithms, Addison-Wesley (1997).
• Example multimedia system

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Hard real-time systems

• Hard real-time systems
• only judged to be correct if every task is
  guaranteed to meet its deadline Chow Johnson,
  Distributed Operating Systems Algorithms,
  Addison-Wesley (1997).
• a single missed deadline is unacceptable, as
  this might lead to loss of life or an
  environ-mental catastrophe Tanenbaum,
  Distributed Operating Systems, Prentice-Hall
  (1995).

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Hard/Soft real-time systems

• A job should be completed before its deadline to
  be of use (in soft real-time systems) or to avert
  disaster (in hard real-time systems). The major
  issue in the design of real-time operating
  systems is the scheduling of jobs in such a way
  that a maximum number of jobs satisfy their
  deadlines. Singhal Shivaratri, Advanced
  Concepts in Operating Systems, McGraw-Hill (1994).

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Firm real-time systems

• Firm real-time systems
• similar to a soft real-time system, but tasks
  that have missed their deadlines are discarded
  Tanenbaum, Distributed Operating Systems,
  Prentice-Hall (1995).
• where missing a deadline means you have to kill
  off the current activity, but the consequence is
  not fatal Chow Johnson, Distributed Operating
  Systems Algorithms, Addison-Wesley (1997).
• E.g. partially filled bottle on assembly line

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Types of real-time systems

• Re-active
• interacts with environment
• Embedded
• controls specialized hardware
• Event-triggered
• unpredictable, asynchronous
• Time-Triggered
• predictable, synchronous, periodic

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Myths of real-time systems (Tanenbaum)

• Real-time systems are about writing device
  drivers in assembly code.
• involve more than device drivers
• Real-time computing is fast computing.
• computer-powered telescopes
• Fast computers will make real-time systems
  obsolete.
• no -- only more will be expected of them

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Message passing

• A form of communication between two processes
• A physical copy of message is sent from one
  process to the other
• Blocking vs Non-blocking

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Blocking message passing

• Sending process must wait after send until an
  acknowledgement is made by the receiver
• Receiving process must wait for expected message
  from sending process
• A form of synchronization
• Receipt determined
• by polling common buffer
• by interrupt

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Figure 3.1 Blocking Send and Receive
Primitives No Buffer. (Galli, p.58)
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Figure 3.2 Blocking Send and Receive Primitives
with Buffer. (Galli, p.58)
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Non-blocking message passing

• Asynchronous communication
• Sending process may continue immediately after
  sending a message -- no wait needed
• Receiving process accepts and processes message
  -- then continues on
• Control
• buffer -- receiver can tell if message still
  there
• interrupt

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Process Address

• One-to-one addressing
• explicit
• implicit
• Group addressing
• one-to-many
• many-to-one
• many-to-many

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One-to-one Addressing

• Explicit address
• specific process must be given as parameter
• Implicit address
• name of service used as parameter
• willing to communicate with any client
• acts like send_any and receive_any

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Figure 3.3 Implicit Addressing for Interprocess
Communication. (Galli, p.59)
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Figure 3.4 Explicit Addressing for Interprocess
Communication. (Galli,p.60)
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Group addressing

• One-to-many
• one sender, multiple receivers
• broadcast
• Many-to-one
• multiple senders, but only one receiver
• Many-to-many
• difficult to assure order of messages received

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Figure 3.5 One-to-Many Group Addressing.
(Galli, p.61)
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Many-to-many ordering

• Incidental ordering
• least structured, fastest
• acceptable if all related messages received in
  any order
• Uniform ordering
• all receivers receive messages in same order
• Universal ordering
• all messages must be received in exactly the same
  order as sent

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Figure 3.6 Uniform Ordering. (Galli, p.62)
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Pipes

• interprocess communication APIs
• implemented by a finite-size, FIFO byte-stream
  buffer maintained by the kernel
• serves as a unidirectional communication link so
  that one process can write data into the tail end
  of the pipe while another process may read from
  the head end of the pipe
• Chow Johnson, Distributed Operating Systems
  Algorithms, Addison-Wesley (1997).

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Pipes, continued

• created by a pipe system call, which returns two
  pipe descriptors (similar to a file descriptor),
  one for reading and the other for writing using
  ordinary write and read operations (CJ)
• exists only for the time period when both reader
  and writer processes are active (CJ)
• the classical producer and consumer IPC
  problem (CJ)

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Figure 3.7 Interprocess Communication Using
Pipes. (Galli, p.63)
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Unnamed pipes

• Pipe descriptors are shared by related
  processes (e.g. parent, child)
• Chow Johnson, Distributed Operating Systems
  Algorithms, Addison-Wesley (1997).
• Such a pipe is considered unnamed
• Cannot be used by unrelated processes
• a limitation

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Named pipes

• For unrelated processes, there is a need to
  uniquely identify a pipe since pipe descriptors
  cannot be shared. One solution is to replace the
  kernel pipe data structure with a special FIFO
  file. Pipes with a path name are called named
  pipes. (CJ)
• Since named pipes are files, the communicating
  processes need not exist concurrently (CJ)

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Named pipes, continued

• Use of named pipes is limited to a single domain
  within a common file system. (CJ)
• a limitation
• . Therefore, sockets.

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Sockets

• a communication endpoint of a communication link
  managed by the transport services (CJ)
• created by making a socket system call that
  returns a socket descriptor for subsequent
  network I/O operations, including file-oriented
  read/write and communication-specific
  send/receive (CJ)

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Figure 1.4 The ISO/OSI Reference Model. (Galli,
p.9)
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Sockets, continued

• A socket descriptor is a logical communication
  endpoint (LCE) that is local to a process it
  must be associated with a physical communication
  endpoint (PCE) for data transport. A physical
  communication endpoint is specified by a network
  host address and transport port pair. The
  association of a LCE with a PCE is done by the
  bind system call. (CJ)

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Types of socket communication

• Unix
• local domain
• a single system
• Internet
• world-wide
• includes port and IP address

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Types , continued

• Connection-oriented
• uses TCP
• a connection-oriented reliable stream transport
  protocol (CJ)
• Connectionless
• uses UDP
• a connectionless unreliable datagram transport
  protocol (CJ)

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Connection-oriented socket communication
Client
Server
socket
socket
bind
listen
rendezvous
connect
accept
request
read
write
reply
write
read

• Adapted from Chow Johnson

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Connectionless socket communication
Peer Processes
Peer Processes
socket
socket
LCE
LCE
bind
bind
PCE
PCE
Sendto /recvfrom

• Adapted from Chow Johnson

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Socket support

• Unix primitives
• socket, bin, connect, listen, send, receive,
  shutdown
• available through C libraries
• Java classes
• Socket
• ServerSocket

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Figure 3.8

• Socket
• Analogy
• (Galli,p.66)

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Figure 3.9  Remote Procedure Call Stubs.
(Galli,p.73)
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Figure 3.10  Establishing Communication for
RPC. (Galli,p.74)
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Table 3.1 Summary of IPC Mechanisms and Their Use
in Distributed System Components.

• (Galli, p.77)

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Memory Management

• Review
• Simple memory model
• Shared memory model
• Distributed shared memory
• Memory migration

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Virtual memory (pages, segments)

• Virtual memory
• Memory management unit
• Pages - uniform sized
• Segments - of different sizes
• Internal fragmentation
• External fragmentation

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Figure 4.1  Fragmentation in Page-Based Memory
versus a Segment-Based Memory. (Galli, p.83)
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Page replacement algorithms

• Page fault
• Thrashing
• First fit
• Best fit
• LRU (NRU)
• second chance
• Worst fit

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Figure 4.2 

• Algorithms
• for
• Choosing
• Segment
• Location
• (Galli,p.84)

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Simple memory model

• Parallel UMA systems
• thrashing can occur when parallel processes each
  want its own pages in memory
• time to service all memory requests expensive,
  unless memory large
• virtual memory expensive
• caching can be expensive

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Shared memory model

• NUMA
• Memory bottleneck
• Cache consistency
• Snoopy cache
• enforce critical regions
• disallow caching shared memory data

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Figure 4.3 

• Snoopy
• Cache
• (Galli, p.89)

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Distributed shared memory

• BBN Butterfly
• Reader-writer problems

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Figure 4.4  Centralized Server for Multiple
Reader/Single Writer DSM. (Galli,p.92)
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Figure 4.5  Partially Distributed Invalidation
for Multiple Reader/Single Writer DSM. (Galli,
p.92)
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Ffigure 4.6  Dynamic Distributed Multiple
Reader/Single Writer DSM. (Galli, P.93)
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Figure 4.7  Dynamic Data Allocation for Multiple
Reader/Single Writer DSM.(Galli,p.96)
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Figure 4.8  Stop-and-Copy Memory Migration.
(Galli,p.99)