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Distributed Process Management
Chapter 15
2
Process Migration
• Transfer of sufficient amount of the state
of a process from one computer to
another
• The process executes on the target
machine
3
Motivation
• Load sharing
– Move processes from heavily loaded to
lightly load systems
• Communications performance
– Processes that interact intensively can be
moved to the same node to reduce
communications cost
– May be better to move process to where the
data reside when the data is large
4
Motivation
• Availability
– Long-running process may need to move
because the machine it is running on will be
down
• Utilizing special capabilities
– Process can take advantage of unique
hardware or software capabilities
5
Initiation of Migration
• Operating system
– When goal is load balancing
• Process
– When goal is to reach a particular resource
6
What is Migrated?
• Must destroy the process on the source
system and create it on the target system
• Process image and process control block
and any links must be moved
7
Example of Process Migration
8
Example of Process Migration
9
What is Migrated?
• Eager (all):Transfer entire address space
– No trace of process is left behind
– If address space is large and if the process
does not need most of it, then this approach
my be unnecessarily expensive
10
What is Migrated?
• Precopy: Process continues to execute
on the source node while the address
space is copied
– Pages modified on the source during
precopy operation have to be copied a
second time
– Reduces the time that a process is frozen
and cannot execute during migration
11
What is Migrated?
• Eager (dirty): Transfer only that portion
of the address space that is in main
memory and have been modified
– Any additional blocks of the virtual address
space are transferred on demand
– The source machine is involved throughout
the life of the process
12
What is Migrated?
• Copy-on-reference: Pages are only
brought over when referenced
– Has lowest initial cost of process migration
• Flushing: Pages are cleared from main
memory by flushing dirty pages to disk
– Relieves the source of holding any pages of
the migrated process in main memory
13
Negotiation of Migration
• Migration policy is responsibility of
Starter utility
• Starter utility is also responsible for
long-term scheduling and memory
allocation
• Decision to migrate must be reached
jointly by two Starter processes (one on
the source and one on the destination)
14
15
Eviction
• Destination system may refuse to accept
the migration of a process to itself
• If a workstation is idle, process may
have been migrated to it
– Once the workstation is active, it may be
necessary to evict the migrated processes to
provide adequate response time
16
Distributed Global States
• Operating system cannot know the
current state of all process in the
distributed system
• A process can only know the current
state of all processes on the local system
• Remote processes only know state
information that is received by messages
– These messages represent the state in the
past
17
Example
• Bank account is distributed over two
branches
• The total amount in the account is the
sum at each branch
• At 3 PM the account balance is
determined
• Messages are sent to request the
information
18
Example
19
Example
• If at the time of balance determination,
the balance from branch A is in transit to
branch B
• The result is a false reading
20
Example
21
Example
• All messages in transit must be
examined at time of observation
• Total consists of balance at both
branches and amount in message
22
Example
• If clocks at the two branches are not
perfectly synchronized
• Transfer amount at 3:01 from branch A
• Amount arrives at branch B at 2:59
• At 3:00 the amount is counted twice
23
Example
24
Some Terms
• Channel
– Exists between two processes if they
exchange messages
• State
– Sequence of messages that have been sent
and received along channels incident with
the process
25
Some Terms
• Snapshot
– Records the state of a process
• Global state
– The combined state of all processes
• Distributed Snapshot
– A collection of snapshots, one for each
process
26
Inconsistent Global State
27
Consistent Global State
28
Distributed Snapshot
Algorithm
29
Distributed Snapshot Algorithm
Process 1
Outgoing channels
2 sent 1, 2, 3, 4, 5, 6
3 sent 1, 2, 3, 4, 5, 6
Incoming channels
Process 3
Outgoing channels
2 sent 1, 2, 3, 4, 5, 6, 7, 8
Incoming channels
1 received 1, 2, 3 stored
4, 5, 6
2 received 1, 2, 3 stored
4
4 received 1, 2, 3
Process 2
Outgoing channels
3 sent 1, 2, 3, 4
4 sent 1, 2, 3, 4
Incoming channels
1 received 1, 2, 3, 4
stored 5, 6
3 received 1, 2, 3, 4, 5, 6,
7, 8
Process 4
Outgoing channels
3 sent 1, 2, 3
Incoming channels
2 received 1, 2 stored 3,
4
30
Distributed Mutual Exclusion
Concepts
• Mutual exclusion must be enforced: only one
process at a time is allowed in its critical
section
• A process that halts in its noncritical section
must do so without interfering with other
processes
• It must not be possible for a process requiring
access to a critical section to be delayed
indefinitely: no deadlock or starvation
31
Distributed Mutual Exclusion
Concepts
• When no process is in a critical section,
any process that requests entry to its
critical section must be permitted to
enter without delay
• No assumptions are made about relative
process speeds or number of processors
• A process remains inside its critical
section for a finite time only
32
33
Centralized Algorithm for
Mutual Exclusion
• One node is designated as the control node
• This node control access to all shared objects
• Only the control node makes resource-
allocation decision
• All necessary information is concentrated in
the control node
• If control node fails, mutual exclusion breaks
down
34
Distributed Algorithm
• All nodes have equal amount of
information, on average
• Each node has only a partial picture of
the total system and must make
decisions based on this information
• All nodes bear equal responsibility for
the final decision
35
Distributed Algorithm
• All nodes expend equal effort, on
average, in effecting a final decision
• Failure of a node, in general, does not
result in a total system collapse
• There exits no systemwide common
clock with which to regulate the time of
events
36
Ordering of Events
• Events must be order to ensure mutual
exclusion and avoid deadlock
• Clocks are not synchronized
• Communication delays
37
Ordering of Events
• Need to consistently say that one event
occurs before another event
• Messages are sent when want to enter
critical section and when leaving critical
section
• Time-stamping
– Orders events on a distributed system
– System clock is not used
38
Time-Stamping
• Each system on the network maintains a
counter which functions as a clock
• Each site has a numerical identifier
• When a message is received, the
receiving system sets is counter to one
more than the maximum of its current
value and the incoming time-stamp
(counter)
39
Time-Stamping
• If two messages have the same time-
stamp, they are ordered by the number
of their sites
• For this method to work, each message
is sent from one process to all other
processes
– Ensures all sites have same ordering of
messages
– For mutual exclusion and deadlock all
processes must be aware of the situation
40
41
42
43
Token-Passing Approach
• Pass a token among the participating processes
• The token is an entity that at any time is held
by one process
• The process holding the token may enter its
critical section without asking permission
• When a process leaves its critical section, it
passes the token to another process
44
Deadlock in Resource
Allocation
• Mutual exclusion
• Hold and wait
• No preemption
• Circular wait
45
Phantom Deadlock
46
Deadlock Prevention
• Circular-wait condition can be prevented
by defining a linear ordering of resource
types
• Hold-and-wait condition can be
prevented by requiring that a process
request all of its required resource at one
time, and blocking the process until all
requests can be granted simultaneously
47
Deadlock Avoidance
• Distributed deadlock avoidance is
impractical
– Every node must keep track of the global
state of the system
– The process of checking for a safe global
state must be mutually exclusive
– Checking for safe states involves
considerable processing overhead for a
distributed system with a large number of
processes and resources
48
Distributed Deadlock
Detection
• Each site only knows about its own resources
– Deadlock may involve distributed resources
• Centralized control – one site is responsible
for deadlock detection
• Hierarchical control – lowest node above the
nodes involved in deadlock
• Distributed control – all processes cooperate in
the deadlock detection function
49
Deadlock in Message
Communication
• Mutual Waiting
– Deadlock occurs in message
communication when each of a group of
processes is waiting for a message from
another member of the group and there are
no messages in transit
50
51
Deadlock in Message
Communication
• Unavailability of Message Buffers
– Well known in packet-switching data
networks
– Example: buffer space for A is filled with
packets destined for B. The reverse is true
at B.
52
Direct Store-and-Forward
Deadlock
53
Deadlock in Message
Communication
• Unavailability of Message Buffers
– For each node, the queue to the adjacent
node in one direction is full with packets
destined for the next node beyond
54
55
Structured Buffer Pool
56
Finite Channels Lead to
Deadlock

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Chapter00000000

  • 2. 2 Process Migration • Transfer of sufficient amount of the state of a process from one computer to another • The process executes on the target machine
  • 3. 3 Motivation • Load sharing – Move processes from heavily loaded to lightly load systems • Communications performance – Processes that interact intensively can be moved to the same node to reduce communications cost – May be better to move process to where the data reside when the data is large
  • 4. 4 Motivation • Availability – Long-running process may need to move because the machine it is running on will be down • Utilizing special capabilities – Process can take advantage of unique hardware or software capabilities
  • 5. 5 Initiation of Migration • Operating system – When goal is load balancing • Process – When goal is to reach a particular resource
  • 6. 6 What is Migrated? • Must destroy the process on the source system and create it on the target system • Process image and process control block and any links must be moved
  • 9. 9 What is Migrated? • Eager (all):Transfer entire address space – No trace of process is left behind – If address space is large and if the process does not need most of it, then this approach my be unnecessarily expensive
  • 10. 10 What is Migrated? • Precopy: Process continues to execute on the source node while the address space is copied – Pages modified on the source during precopy operation have to be copied a second time – Reduces the time that a process is frozen and cannot execute during migration
  • 11. 11 What is Migrated? • Eager (dirty): Transfer only that portion of the address space that is in main memory and have been modified – Any additional blocks of the virtual address space are transferred on demand – The source machine is involved throughout the life of the process
  • 12. 12 What is Migrated? • Copy-on-reference: Pages are only brought over when referenced – Has lowest initial cost of process migration • Flushing: Pages are cleared from main memory by flushing dirty pages to disk – Relieves the source of holding any pages of the migrated process in main memory
  • 13. 13 Negotiation of Migration • Migration policy is responsibility of Starter utility • Starter utility is also responsible for long-term scheduling and memory allocation • Decision to migrate must be reached jointly by two Starter processes (one on the source and one on the destination)
  • 14. 14
  • 15. 15 Eviction • Destination system may refuse to accept the migration of a process to itself • If a workstation is idle, process may have been migrated to it – Once the workstation is active, it may be necessary to evict the migrated processes to provide adequate response time
  • 16. 16 Distributed Global States • Operating system cannot know the current state of all process in the distributed system • A process can only know the current state of all processes on the local system • Remote processes only know state information that is received by messages – These messages represent the state in the past
  • 17. 17 Example • Bank account is distributed over two branches • The total amount in the account is the sum at each branch • At 3 PM the account balance is determined • Messages are sent to request the information
  • 19. 19 Example • If at the time of balance determination, the balance from branch A is in transit to branch B • The result is a false reading
  • 21. 21 Example • All messages in transit must be examined at time of observation • Total consists of balance at both branches and amount in message
  • 22. 22 Example • If clocks at the two branches are not perfectly synchronized • Transfer amount at 3:01 from branch A • Amount arrives at branch B at 2:59 • At 3:00 the amount is counted twice
  • 24. 24 Some Terms • Channel – Exists between two processes if they exchange messages • State – Sequence of messages that have been sent and received along channels incident with the process
  • 25. 25 Some Terms • Snapshot – Records the state of a process • Global state – The combined state of all processes • Distributed Snapshot – A collection of snapshots, one for each process
  • 29. 29 Distributed Snapshot Algorithm Process 1 Outgoing channels 2 sent 1, 2, 3, 4, 5, 6 3 sent 1, 2, 3, 4, 5, 6 Incoming channels Process 3 Outgoing channels 2 sent 1, 2, 3, 4, 5, 6, 7, 8 Incoming channels 1 received 1, 2, 3 stored 4, 5, 6 2 received 1, 2, 3 stored 4 4 received 1, 2, 3 Process 2 Outgoing channels 3 sent 1, 2, 3, 4 4 sent 1, 2, 3, 4 Incoming channels 1 received 1, 2, 3, 4 stored 5, 6 3 received 1, 2, 3, 4, 5, 6, 7, 8 Process 4 Outgoing channels 3 sent 1, 2, 3 Incoming channels 2 received 1, 2 stored 3, 4
  • 30. 30 Distributed Mutual Exclusion Concepts • Mutual exclusion must be enforced: only one process at a time is allowed in its critical section • A process that halts in its noncritical section must do so without interfering with other processes • It must not be possible for a process requiring access to a critical section to be delayed indefinitely: no deadlock or starvation
  • 31. 31 Distributed Mutual Exclusion Concepts • When no process is in a critical section, any process that requests entry to its critical section must be permitted to enter without delay • No assumptions are made about relative process speeds or number of processors • A process remains inside its critical section for a finite time only
  • 32. 32
  • 33. 33 Centralized Algorithm for Mutual Exclusion • One node is designated as the control node • This node control access to all shared objects • Only the control node makes resource- allocation decision • All necessary information is concentrated in the control node • If control node fails, mutual exclusion breaks down
  • 34. 34 Distributed Algorithm • All nodes have equal amount of information, on average • Each node has only a partial picture of the total system and must make decisions based on this information • All nodes bear equal responsibility for the final decision
  • 35. 35 Distributed Algorithm • All nodes expend equal effort, on average, in effecting a final decision • Failure of a node, in general, does not result in a total system collapse • There exits no systemwide common clock with which to regulate the time of events
  • 36. 36 Ordering of Events • Events must be order to ensure mutual exclusion and avoid deadlock • Clocks are not synchronized • Communication delays
  • 37. 37 Ordering of Events • Need to consistently say that one event occurs before another event • Messages are sent when want to enter critical section and when leaving critical section • Time-stamping – Orders events on a distributed system – System clock is not used
  • 38. 38 Time-Stamping • Each system on the network maintains a counter which functions as a clock • Each site has a numerical identifier • When a message is received, the receiving system sets is counter to one more than the maximum of its current value and the incoming time-stamp (counter)
  • 39. 39 Time-Stamping • If two messages have the same time- stamp, they are ordered by the number of their sites • For this method to work, each message is sent from one process to all other processes – Ensures all sites have same ordering of messages – For mutual exclusion and deadlock all processes must be aware of the situation
  • 40. 40
  • 41. 41
  • 42. 42
  • 43. 43 Token-Passing Approach • Pass a token among the participating processes • The token is an entity that at any time is held by one process • The process holding the token may enter its critical section without asking permission • When a process leaves its critical section, it passes the token to another process
  • 44. 44 Deadlock in Resource Allocation • Mutual exclusion • Hold and wait • No preemption • Circular wait
  • 46. 46 Deadlock Prevention • Circular-wait condition can be prevented by defining a linear ordering of resource types • Hold-and-wait condition can be prevented by requiring that a process request all of its required resource at one time, and blocking the process until all requests can be granted simultaneously
  • 47. 47 Deadlock Avoidance • Distributed deadlock avoidance is impractical – Every node must keep track of the global state of the system – The process of checking for a safe global state must be mutually exclusive – Checking for safe states involves considerable processing overhead for a distributed system with a large number of processes and resources
  • 48. 48 Distributed Deadlock Detection • Each site only knows about its own resources – Deadlock may involve distributed resources • Centralized control – one site is responsible for deadlock detection • Hierarchical control – lowest node above the nodes involved in deadlock • Distributed control – all processes cooperate in the deadlock detection function
  • 49. 49 Deadlock in Message Communication • Mutual Waiting – Deadlock occurs in message communication when each of a group of processes is waiting for a message from another member of the group and there are no messages in transit
  • 50. 50
  • 51. 51 Deadlock in Message Communication • Unavailability of Message Buffers – Well known in packet-switching data networks – Example: buffer space for A is filled with packets destined for B. The reverse is true at B.
  • 53. 53 Deadlock in Message Communication • Unavailability of Message Buffers – For each node, the queue to the adjacent node in one direction is full with packets destined for the next node beyond
  • 54. 54
  • 56. 56 Finite Channels Lead to Deadlock