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Process Synchronization. Concurrent access to shared data may result in data inconsistency We must have mechanisms to ensure the orderly execution of cooperating processes

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Process synchronization
Process Synchronization

  • Concurrent access to shared data may result in data inconsistency

  • We must have mechanisms to ensure the orderly execution of cooperating processes

  • Suppose we consider the bounded buffer problem and add a variable, counter, initialized to 0 and incremented each time a new item is added to the buffer

Bounded buffer
Bounded Buffer

  • Shared data

    typeitem = …;

    varbuffer: array[0..n-1]ofitem;

    in, out: 0..n-1;

    counter: 0..n;

    in, out, counter := 0;

Bounded buffer cont
Bounded Buffer (cont)

  • Producer process


    produce an item in nextp

    whilecounter = ndono-op;

    buffer[in] := nextp;

    in := (in + 1)modn;

    counter := counter + 1;


Bounded buffer cont1
Bounded Buffer (cont)

  • Consumer process


    whilecounter = 0dono-op;

    nextc := buffer[out];

    out := (out + 1)modn;

    counter := counter – 1;

    consume the next item in nextc



Bounded buffer cont2
Bounded Buffer (cont)

  • The statements that increment and decrement the counters have to be executed atomically

  • Atomically means that they cannot be interrupted in their execution

  • What happens if they are not executed atomically?

Bounded buffer cont3
Bounded Buffer (cont)

  • Race condition – several processes access and manipulate the same data concurrently, and the outcome of the execution depends on the particular order in which the access takes place

Critical section problem
Critical Section Problem

  • n processes all competing to use some shared data

  • Each process has a code segment, call the critical section, in which shared data is accessed

  • Problem – ensure that processes cannot execute their critical sections at the same time

Requirements for solution to critical section problem
Requirements for Solution to Critical Section Problem

1. Mutual Exclusion – if process Pi is executing in the critical section, no other processes can be executing in their critical sections

2. Progress – if no process is executing in its critical section and there is some process waiting to enter the critical section, the waiting process will not be postponed indefinitely

Requirements for solution to critical section problem cont
Requirements for Solution to Critical Section Problem (cont)

  • Bounded Waiting – a bound must exist on the number of times that other processes are allowed to enter their critical sections after a process has made a request to enter and before that request is granted

    • Assume that each process executes at a nonzero speed

    • No assumption is made about the relative speed of the n processes

Critical section problem cont
Critical Section Problem (cont)

  • Requirements of the solution:

    • Does not rely on any assumptions concerning the hardware instructions

    • Does not rely on the number of processes

    • We assume some underlying machine language for the computer we are running on

Critical section problem cont1
Critical Section Problem (cont)

  • Structure of process Pi


    entry section

    critical section

    exit section

    remainder section


Attempts to solve problem
Attempts to Solve Problem

  • Only 2 processes, P0 and P1

  • General structure of processes is as seen before

  • Processes may share some common variables to synchronize their actions.

Algorithm 1
Algorithm 1

  • Shared variables:

    varturn: 0..1; initially turn = 0

    turn = i Pi can enter critical section

  • Process P0


    whileturn 0 dono-op;

    critical section

    turn := 1;

    remainder section


  • Satisfies mutual exclusion, but not progress

Algorithm 2
Algorithm 2

  • Shared variables:

    varflag: array[0..1] ofboolean;

    initially flag[0] = flag[1] = 0

    flag[i] = true Pi ready to enter critical section

  • Process P0


    flag[0] := true;


    critical section

    flag[0] := false;

    remainder section


  • Satisfies mutual exclusion, but not progress

Algorithm 3
Algorithm 3

  • Combine shared variables of algorithm 1 and 2

  • Process P0


    flag[0] := true;

    turn := 1;

    while (flag[1]and turn = 1) dono-op;

    critical section

    flag[0] := false;

    remainder section


  • Meets all three requirements

Bakery algorithm
Bakery Algorithm

Critical section for n processes

  • Before entering its critical section, process receives a number. Holder of the smallest number enters the critical section

  • If processes Pi and Pj receive the same number, if i < j, then Pi is served first; else Pj is served first

Bakery algorithm cont
Bakery Algorithm (cont)

  • The numbering scheme always generates numbers in increasing order of enumeration; i.e., 1,2,3,3,3,3,4,5,…

  • Notation  lexicographical order (ticket#, process id#)

    • (a,b) < (c,d) if a < c or if a = c and b < d

    • max(a0,…,an-1) is a number, k, such that k ai for i = 0, …, n-1

Bakery algorithm cont1
Bakery Algorithm (cont)

  • Shared data

    • varchoosing: array [0..n-1] ofboolean;

    • varnumber: array [0..n-1] ofinteger;

  • The above data structures are initialized to false and zero, respectively

Bakery algorithm cont2
Bakery Algorithm (cont)


choosing[i] := true;

number[i] := max(number[0], …, number[n-1]) + 1;

choosing[i] := false;

forj := 0 ton-1 do begin

whilechoosing[j] do no-op;

whilenumber[j]  0 and

(number[j],j) < (number[i],i) do no-op;


critical section

number[i] := 0;

remainder section


Synchronization hardware
Synchronization Hardware

  • Test and modify the contents of a word atomically

    functionTest-and-Set(vartarget: boolean): boolean;


    Test-and-Set := target;

    target := true;


Mutual exclusion with test and set
Mutual Exclusion with Test-and-Set

  • Shared data: varlock: boolean := false

  • Process Pi


    whileTest-and-Set(lock) dono-op;

    critical section

    lock := false;

    remainder section



  • Synchronization tool that does not require busy waiting.

  • Semaphore S – integer variable

  • Can only be accessed via two indivisible (atomic) operations:

    • wait(S): whileS 0 dono-op;

      S := S – 1;

    • signal(S): S := S + 1;

Critical section for n processes
Critical Section for n Processes

  • Shared variable: varmutex: semaphore := 1;

  • Process Pi



    critical section


    remainder section


Semaphore implementation
Semaphore Implementation

  • Define a semaphore as a record

    typesemaphore = record

    value: integer;

    L: list ofprocess;

  • Assume two simple operations:

    • block suspends the process that invokes it

    • wakeup(P) resumes the execution of a blocked process P

Implementation cont
Implementation (cont)

  • Semaphore operations are now defined as

    • wait(S): S.value := S.value – 1;

      ifS.value < 0


      add this process to S.L;



    • signal(S): S.value := S.value + 1;

      ifS.value 0


      remove a process P from S.L;



Semaphore as general synchronization tools
Semaphore as General Synchronization Tools

  • Execute B in Pj after A executed in Pi

  • Use semaphore flag initialized to 0

  • Code

    Pi Pj

    ... …

    A wait(flag)

    signal(flag) B


  • Deadlock – two or more processes waiting indefinitely for an event that can be caused by only one of the waiting processes

  • Let S and Q be two semaphores initialized to 1


    wait(S) wait(Q)

    wait(Q) wait(S)

    … …

    signal(S) signal(Q)

    signal(Q) signal(S)


  • Starvation – indefinite blocking. A process may never be removed from the semaphore queue in which it is suspended.

Types of semaphores
Types of Semaphores

  • Counting semaphore – integer value can range over an unrestricted domain

  • Binary semaphore – integer value can range only between 0 and 1; can be simpler to implement

  • Can implement a counting semaphore S as a binary semaphore

Implementing a counting semaphore
Implementing a Counting Semaphore

  • Shared data:

    varS1: binary semaphore;

    S2: binary semaphore;

    C : integer;

  • Initialization

    S1 = 1

    S2 = 0

    C = initial value of semaphore S

Counting semaphore cont
Counting Semaphore (cont)

  • Wait wait(S1);

    C := C – 1;

    ifC < 0

    thensignal(S1); wait(S2);


  • Signal wait(S1);

    C := C + 1;

    ifC 0



Classical problems of synchronization
Classical Problems of Synchronization

  • Bounded buffer problem

  • Readers and writers problem

  • Dining philosophers problem

Bounded buffer problem
Bounded Buffer Problem

  • Shared data

    typeitem = …

    varbuffer = …

    full, empty, mutex: semaphore;

    nextp, nextc: item;

    full := 0; empty := n; mutex = 1;

Producer process
Producer Process


produce an item in nextp



add nextp to buffer




Consumer process
Consumer Process




remove an item from buffer to nextc



consume the item in nextc


Readers and writers problem
Readers and Writers Problem

  • Shared data

    varmutex, wrt: semaphore = 1;

    readcount: integer = 0;

  • Writer Process


    writing is performed


Reader process
Reader Process


readcount := readcount + 1;

ifreadcount = 1 thenwait(wrt);


reading is performed


readcount := readcount – 1;

ifreadcount = 0 thensignal(wrt);


Dining philosophers problem
Dining Philosophers Problem

  • Shared data

    varchopstick: array [0..4] ofsemaphore = 1;

Dining philosophers problem cont
Dining Philosophers Problem (cont)

  • Philosopher i:



    wait(chopstick[(i+1) mod 5]);



    signal(chopstick[(i+1) mod 5]);



Dining philosopher cont
Dining Philosopher (cont)

  • The previous solution has a problem – it can deadlock if both philosophers pick up their left fork at the same time.

  • There are solutions to this problem, but we won’t consider them at this time.

Critical regions
Critical Regions

  • High level synchronization construct

  • A shared variable v of type T is declared as:

    varv: sharedT

  • Variable v accessed only inside statement:


    where B is a boolean expression

  • While statement S is being executed, no other process can access variable v

Critical regions cont
Critical Regions (cont)

  • Regions referring to the same shared variable exclude each other in time

  • When a process tries to execute the region statement, the boolean expression B is evaluated. If B is true, statement S is executed. If B is false, the process is delayed until B becomes true and no other process is in the region associated with v.

Bounded buffer1
Bounded Buffer

  • Shared variable

    varbuffer : sharedrecord

    pool: array[0..n-1] ofitem;

    count, in, out : integer;


  • Producer process

    regionbufferwhencount < n do

    pool[in] := nextp;

    in := (in + 1) modn;

    count := count + 1;


Bounded buffer cont4
Bounded Buffer (cont)

  • Consumer process

    regionbufferwhencount > 0 do

    nextc := pool[out];

    out := (out + 1) modn;

    count := count – 1;


Implementation of critical regions
Implementation of Critical Regions

  • Associate with the shared variable v the following variables:

    varmutex, first-delay, second-delay: semaphore;

    first-count, second-count; integer;

  • Mutually exclusive access to the critical section is provided by mutex.

Implementation of cr cont
Implementation of CR (cont)

  • If a process cannot enter the critical section because the boolean expression B is false, it initially waits on the first-delay semaphore; moved to the second-delay semaphore before it is allowed to reevaluate B

  • Keep track of the number of processes waiting on first-delay and second-delay with first-count and second-count, respectively

Implementation of cr cont1
Implementation of CR (cont)

  • The algorithm assumes a FIFO ordering on the queuing of processes for a semaphore

  • For an arbitrary queuing discipline, a more complicated implementation is required

Implementation of cr cont2
Implementation of CR (cont)

wait(mutex); S;

whilenot B doiffirst-count > 0

first-count := first-count + 1; thensignal(first-delay)

ifsecond-count > 0 else

thensignal(second-delay) ifsecond-count > 0

elsesignal(mutex); thensignal(second-delay)

wait(first-delay); elsesignal(mutex);

first-count := first-count – 1;

second-count := second-count + 1;

iffirst-count > 0




second-count := second-count – 1;



  • High level synchronization construct that allows the safe sharing of an abstract data type among concurrent processes

    typemonitor-name = monitor

    variable declarations

    procedureentry P1 ( … );

    begin … end;

    procedureentryPn ( … );

    begin … end;


    initialization code


Monitors cont
Monitors (cont)

  • To allow a process to wait within the monitor, a condition variable must be declared as:

    varx,y: condition

  • Condition variable can only be used with the operations below:

    • x.wait – the process invoking this operation is suspended until another process invokes x.signal

    • x.signal – resumes exactly one suspended process. If no process is suspended, then the signal operation has no effect.

Monitors dining philosophers
Monitors – Dining Philosophers

typedining-philosophers = monitor

varstate:array[0..4] of (thinking,hungry,eating);

varself: array[0..4] ofcondition;

procedureentrypickup (i: 0..4);

state[i] := hungry;


ifstate[i]  eatingthenself[i].wait;


procedureentryputdown (i: 0..4);

state[i] := thinking;

test((i+4) mod 5);

test((i+1) mod 5);


Dining philosophers cont
Dining Philosophers (cont)

proceduretest (k: 0..4);

ifstate[(k+4) mod 5)  eating

andstate[k] = hungry

andstate[(k+1) mod 5]  eating


state[k] := eating;





fori := 0 to 4 do

state[i] := thinking;


Monitor implementation using semaphores
Monitor Implementation Using Semaphores

  • Variables:

    varmutex: semaphore (init = 1)

    next: semaphore (init = 0)

    next-count: semaphore (init = 0)

  • Each external procedure F is replaced by


    body of F;

    ifnext-count > 0



Monitor implementation cont
Monitor Implementation (cont)

  • Mutual exclusion within a monitor is ensured.

  • For each condition variable x, we have:

    varx-sem: semaphore (init = 0)

    x-count: integer (init = 0)

Monitor implementation cont1
Monitor Implementation (cont)

  • The operation x.wait can be implemented as

    x-count := x-count + 1;

    ifnext-count > 0




    x-count := x-count – 1;

  • The operation x.signal can be implemented as

    ifx-count > 0 then

    next-count := next-count + 1;



    next-count := next_count – 1;


Monitor implementation cont2
Monitor Implementation (cont)

  • Conditional wait construct: x.wait(c)

    • c - integer expression evaluated when the wait operation is executed.

    • Value of c (priority number) stored with the name of the process that is suspended.

    • When x.signal is executed, process with smallest associated priority number is resumed next.

Monitor implementation cont3
Monitor Implementation (cont)

  • Check two conditions to establish the correctness of the system:

    • User processes must always make their calls on the monitor in a correct sequence.

    • Must ensure that an uncooperative process does not ignore the mutual exclusion gateway provided by the monitor, and try to access the shared resource directly, without using the access protocols.

Solaris 2 operating system
Solaris 2 Operating System

  • Implements a variety of locks to support multitasking, multithreading (including real time threads), and multiprocessing

  • Uses adaptive mutexes for efficiency when protecting data from short code segments

  • Uses condition variables and readers-writers locks when longer sections of code need access to date

Atomic transactions
Atomic Transactions

  • Transaction - program unit that must be executed atomically; that is, either all the operations associated with it are executed to completion, or none are performed.

  • Must preserve atomicity despite possibility of failure.

  • We are concerned with ensuring transaction atomicity in an environment where failures result in the loss of information on volatile storage.

Log based recovery
Log Based Recovery

  • Write-ahead log - all updates are recorded on the log, which is kept in stable storage; has the following fields:

    • transaction name

    • data item name, old value, new value

  • The log has a record of <Tistarts>, and either

    • <Ticommits> if the transactions commits, or

    • <Tiaborts> if the transaction aborts

Log based recovery cont
Log Based Recovery (cont)

  • Recovery algorithm uses two procedures:

    • undo(Ti) - restores value of all data updated by transaction Ti to the old values. It is invoked if the log contains record <Tistarts>, but not <Ticommits>

    • redo(Ti) - sets value of all data updated by transaction Ti to the new values. It is invoked if the log contains both <Tistarts> and <Ticommits>

Checkpoints reduce recovery overhead
Checkpoints - Reduce Recovery Overhead

1. Output all log records currently residing in volatile storage onto stable storage

2. Output all modified data residing in volatile storage to stable storage

3.Output log record <checkpoint> onto stable storage

Checkpoints cont
Checkpoints (cont)

  • Recovery routine examines log to determine the most recent transaction Ti that started executing before the most recent checkpoint took place

    • Search log backward for first <checkpoint> record

    • Find subsequent <Tistart> record

  • redo and undo operations need to be applied only to transaction Ti and all transactions Tj that started executing after transaction Ti.

Concurrent atomic transactions
Concurrent Atomic Transactions

  • Serial schedule - the transactions are executed sequentially in some order

  • Example of a serial schedule in which T0 is followed by T1

    T0 T1









Concurrent atomic transactions cont
Concurrent Atomic Transactions(cont)

  • Conflicting operations – Oi and Ojconflict if they access the same data item, and at least one of these operations is a write operation

  • Conflict serializable schedule - schedule that can be transformed into a serial schedule by a series of swaps of nonconflicting operations

Example of serializable schedule
Example of Serializable Schedule

T0 T1









Concurrent transactions cont
Concurrent Transactions (cont)

  • Locking protocol governs how locks are acquired and released; data item can be locked in the following modes:

    • Shared: If Ti has obtained a shared mode lock on data item Q, then Tican read this item, but it cannot write Q

    • Exclusive: If Ti has obtained an exclusive mode lock on data item Q, then Ti can both read and write Q

Concurrent transactions cont1
Concurrent Transactions (cont)

  • Two phase locking protocol

    • Growing phase: A transaction may obtain locks, but may not release any lock

    • Shrinking phase: A transaction may release locks, but may not obtain any new locks

  • The two phase locking protocol ensures conflict serializability, but does not ensure freedom from deadlock

Concurrent transactions cont2
Concurrent Transactions (cont)

  • Timestamp ordering scheme – transaction ordering protocol for determining serializability order

    • With each transaction Ti in the system, associate a unique fixed timestamp, denoted by TS(Ti)

    • If Ti has been assigned timestamp TS(Ti) , and a new transaction Tj enters the system, then TS(Ti) < TS(Tj)

Concurrent transactions cont3
Concurrent Transactions (cont)

  • Implement by assigning two timestamp values to each data item Q

    • W-timestamp(Q) – denotes largest timestamp of any transaction that executed write(Q) successfully

    • R-timestamp(Q) – denotes largest timestamp of any transaction that executed read(Q) successfully

Schedule possible under timestamp protocol
Schedule Possible under Timestamp Protocol








Schedule possible under timestamp protocol cont
Schedule Possible under Timestamp Protocol (cont)

  • There are schedules that are possible under the two phase locking protocol but are not possible under the timestamp protocol, and vice versa

  • The timestamp ordering protocol ensures conflict serializability; conflicting operations are processed in timestamp order