Outline Distributed Mutual Exclusion Introduction Performance measures Centralized

Outline • 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 11/5/2020 COP 5611 1

Announcement • 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 11/5/2020 COP 5611 2

The Critical Section Problem • 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 11/5/2020 COP 5611 3

An Example • 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 P 1: load counter, r 1 P 2: add r 1, #1, r 2 P 3: store r 2, counter – Consumer: counter = counter - 1 C 1: load counter, r 1 C 2: add r 1, #-1, r 2 C 3: store r 2, counter 11/5/2020 COP 5611 4

An Example - cont. • A particular execution sequence – P 1: load counter, r 1 – P 2: add r 1, #1, r 2 --- Context switch ---– C 1: load counter, r 1 – C 2: add r 1, #-1, r 2 – C 3: store r 2, counter --- Context switch ---– P 3: store r 2, counter – What is the value of counter? 11/5/2020 COP 5611 5

An Example - cont. • A particular execution sequence – C 1: load counter, r 1 – C 2: add r 1, #-1, r 2 --- Context switch ---– P 1: load counter, r 1 – P 2: add r 1, #1, r 2 – P 3: store r 2, counter --- Context switch ---– C 3: store r 2, counter – What is the value of counter this time? 11/5/2020 COP 5611 6

An Example - cont. • A particular execution sequence – C 1: load counter, r 1 – C 2: add r 1, #-1, r 2 – C 3: store r 2, counter --- Context switch ---– P 1: load counter, r 1 – P 2: add r 1, #1, r 2 – P 3: store r 2, counter --- Context switch ---– What is the value of counter this time? 11/5/2020 COP 5611 7

Mutual Exclusion • 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 11/5/2020 COP 5611 8

The Structure of Processes • Structure of process Pi repeat entry section critical section exit section reminder section until false; 11/5/2020 COP 5611 9

Mutual Exclusion in Traditional OS • 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; 11/5/2020 COP 5611 10

Mutual Exclusion in Traditional OS – cont. • Shared variables – var mutex : semaphore – initially mutex = 1 • Process Pi repeat wait(mutex); critical section signal(mutex); remainder section until false; 11/5/2020 COP 5611 11

Distributed Mutual Exclusion • 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 11/5/2020 COP 5611 12

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 11/5/2020 COP 5611 13

Performance Measure for Distributed Mutual Exclusion 11/5/2020 COP 5611 14

A Centralized Algorithm • 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 11/5/2020 COP 5611 15

A Centralized Algorithm – cont. a) b) c) Process 1 asks the coordinator for permission to enter a critical region. Permission is granted Process 2 then asks permission to enter the same critical region. The coordinator does not reply. When process 1 exits the critical region, it tells the coordinator, when then replies to 2 11/5/2020 COP 5611 16

A Centralized Algorithm – cont. • 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 11/5/2020 COP 5611 17

Distributed Solutions • 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 11/5/2020 COP 5611 18

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_queuei, which contains mutual exclusion requests ordered by their timestamp and associated id – Ri of each process consists of all the processes – The communication channel is assumed to be FIFO 11/5/2020 COP 5611 19

Lamport’s Distributed Mutual Exclusion Algorithm – cont. 11/5/2020 COP 5611 20

Lamport’s Distributed Mutual Exclusion Algorithm – cont. 11/5/2020 COP 5611 21

Lamport’s Distributed Mutual Exclusion Algorithm – cont. 11/5/2020 COP 5611 22

Lamport’s Distributed Mutual Exclusion Algorithm – cont. 11/5/2020 COP 5611 23

Lamport’s Distributed Mutual Exclusion Algorithm – cont. • Performance analysis – Number of messages per CS – Synchronization delay – Throughput – Response time 11/5/2020 COP 5611 24

Ricart-Agrawala Algorithm 11/5/2020 COP 5611 25

Ricart-Agrawala Algorithm – cont. 11/5/2020 COP 5611 26

Ricart-Agrawala Algorithm – cont. 11/5/2020 COP 5611 27

Ricart-Agrawala Algorithm – cont. • Performance analysis – Number of messages per CS – Synchronization delay – Throughput – Response time 11/5/2020 COP 5611 28

A Simple Toke Ring Algorithm • 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 11/5/2020 COP 5611 29

A Simple Toke Ring Algorithm – cont. a) An unordered group of processes on a network. b) A logical ring constructed in software. 11/5/2020 COP 5611 30

A Simple Toke Ring Algorithm – cont. • Performance analysis – Number of messages per CS – Synchronization delay – Response time – Problems • Lost token • Process crash 11/5/2020 COP 5611 31

Suzuki-Kasami’s Algorithm • 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 11/5/2020 COP 5611 32

Suzuki-Kasami’s Algorithm – cont. 11/5/2020 COP 5611 33

Suzuki-Kasami’s Algorithm – cont. • Performance analysis – Number of messages per CS invocation – Synchronization delay – Response time – System throughput 11/5/2020 COP 5611 34

Singhal’s Heuristic Algorithm • 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 11/5/2020 COP 5611 35

Raymond’s Tree-Based Algorithm • In this algorithm, sites are logically arranged as a directed tree 11/5/2020 COP 5611 36

Comparison of Distributed Mutual Exclusion Algorithms 11/5/2020 COP 5611 37

Summary • 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 11/5/2020 COP 5611 38