• Distributed Mutual Exclusion
– Introduction
– Performance measures
– Centralized algorithm
– Non-token-based algorithms
• Lamport’s algorithm
• Ricart-Agrawala algorithm
– Token-based algorithms
• Suzuki-Kasami’s broadcast algorithm
– Singhal’s heuristic algorithm
– Raymond’s tree-based algorithm
– Comparison
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• Next Tuesday (Feb. 18, 2003) Dr. Ted Baker will lecture on distributed deadlock detection
(Chapter 7)
– Please read the materials ahead of time
– Please review the local deadlock detection algorithms (Chapter 3)
– I will post his lecture notes on the class web too
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• When processes (centralized or distributed) interact through shared resources, the integrity of the resources may be violated if the accesses are not coordinated
– The resources do not record all the changes
– A process may obtain inconsistent values
– The final state of the shared resource may be inconsistent
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• Suppose we have two processes, (one is called producer and the other one consumer), the shared variable counter is 5 initially
– Producer: counter = counter +1
P1: load counter, r1
P2: add r1, #1, r2
P3: store r2, counter
– Consumer: counter = counter - 1
C1: load counter, r1
C2: add r1, #-1, r2
C3: store r2, counter
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- cont.
• A particular execution sequence
– P1: load counter, r1
– P2: add r1, #1, r2
--- Context switch ----
– C1: load counter, r1
– C2: add r1, #-1, r2
– C3: store r2, counter
--- Context switch ----
– P3: store r2, counter
– What is the value of counter ?
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- cont.
• A particular execution sequence
– C1: load counter, r1
– C2: add r1, #-1, r2
--- Context switch ----
– P1: load counter, r1
– P2: add r1, #1, r2
– P3: store r2, counter
--- Context switch ----
– C3: store r2, counter
– What is the value of counter this time?
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- cont.
• A particular execution sequence
– C1: load counter, r1
– C2: add r1, #-1, r2
– C3: store r2, counter
--- Context switch ----
– P1: load counter, r1
– P2: add r1, #1, r2
– P3: store r2, counter
--- Context switch ----
– What is the value of counter this time?
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• One solution to the problem is that at any time at most only one process can access the shared resources
– This solution is known as mutual exclusion
– A critical section is a code segment in a process which shared resources are accessed
• A process can have more than one critical section
• There are problems which involve shared resources where mutual exclusion is not the optimal solution
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• Structure of process
P i repeat entry section critical section exit section reminder section
until false ;
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• Through semaphores, monitors or other programming-language constructs
• Semaphore
S
– integer variable
– can only be accessed via two indivisible (atomic) operations wait ( S ): while S

0 do no-op ;
S := S
– 1; signal ( S ): S := S + 1;
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– cont.
• Shared variables
–
var mutex : semaphore
– initially mutex = 1
• Process P i repeat wait ( mutex ); critical section signal ( mutex ); remainder section
until false ;
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• Due to the absence of shared memory, solutions for mutual exclusion based on shared memory cannot be used in distributed systems
– It must be based on message passing
12 4/13/2020 COP5611

Performance Measure for Distributed Mutual Exclusion
• The number of messages per CS invocation
• Synchronization delay
– The time required after a site leaves the CS and before the next site enters the CS
– System throughput 1/(sd+E), where sd is the synchronization delay and E the average CS execution time
• Response time
– The time interval a request waits for its CS execution to be over after its request messages have been sent out
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Performance Measure for Distributed Mutual Exclusion
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• It is a simple solution
– One site, called the control site, is responsible for granting permission to the CS execution
– To request the CS, a site sends a REQUEST message to the control site
• When a site is done with CS execution, it sends a
RELEASE message to the control site
– The control site queues up the requests for the CS and grant them permission
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a) Process 1 asks the coordinator for permission to enter a critical region. Permission is granted b) Process 2 then asks permission to enter the same critical region. The coordinator does not reply.
c) When process 1 exits the critical region, it tells the coordinator, when then replies to 2
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• Analysis of the centralized algorithm
– There is a single point of failure
– Number of messages per CS
– The synchronization delay
• System throughput
– Response time
• Best case
• Worst case
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• Non-token-based algorithms
– Use timestamps to order requests and resolve conflicts between simultaneous requests
– Lamport’s algorithm and Ricart-Agrawala
Algorithm
• Token-based algorithms
– A unique token is shared among the sites
– A site is allowed to enter the CS if it possess the token and continues to hold the token until its CS execution is over; then it passes the token to the next site
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Lamport’s Distributed Mutual Exclusion Algorithm
• This algorithm is based on the total ordering using
Lamport’s clocks
– Each process keeps a Lamport’s logical clock
• Each process is associated with a unique id that can be used to break the ties
– In the algorithm, each process keeps a queue, request_queue i
, which contains mutual exclusion requests ordered by their timestamp and associated id
– R i of each process consists of all the processes
– The communication channel is assumed to be FIFO
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Lamport’s Distributed Mutual Exclusion Algorithm
– cont.
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Lamport’s Distributed Mutual Exclusion Algorithm
– cont.
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Lamport’s Distributed Mutual Exclusion Algorithm
– cont.
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Lamport’s Distributed Mutual Exclusion Algorithm
– cont.
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Lamport’s Distributed Mutual Exclusion Algorithm
– cont.
• Performance analysis
– Number of messages per CS
– Synchronization delay
– Throughput
– Response time
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– cont.
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– cont.
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– cont.
• Performance analysis
– Number of messages per CS
– Synchronization delay
– Throughput
– Response time
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• When the ring is initialized, one process is given the token
• The token circulates around the ring
– It is passed from k to k+1 (modulo the ring size)
– When a process acquires the token from its neighbor, it checks to see if it is waiting to enter its critical section
• If so, it enters its CS
– When exiting from its CS, it passes the token to the next
• Otherwise, it passes the token to the next
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– cont.
a) An unordered group of processes on a network. b) A logical ring constructed in software.
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– cont.
• Performance analysis
– Number of messages per CS
– Synchronization delay
– Response time
– Problems
• Lost token
• Process crash
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• Data structures
– Each site maintains a vector consisting the largest sequence number received so far from other sites
– The token consists of a queue of requesting sites and an array of integers, consisting of the sequence number of the request that a site executed most recently
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– cont.
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– cont.
• Performance analysis
– Number of messages per CS invocation
– Synchronization delay
– Response time
– System throughput
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• In this algorithm, each site maintains information about the state of other sites in the system
– The site only sends the request to a subset of sites that most likely have the token will in a near future
– This reduces the number of messages per CS execution
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• In this algorithm, sites are logically arranged as a directed tree
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Comparison of Distributed Mutual Exclusion Algorithms
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• Mutual exclusion is one solution to the critical section problem
• Due to the absence of shared memory, distributed mutual exclusion algorithms are message-based
– Centralized algorithms
– Non-token-based algorithms
– Token-based algorithms
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