1. Chapter 18-1: Distributed Coordination

2. 18.2 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Chapter 18 Distributed Coordination Chapter 18.1 Event Ordering Mutual Exclusion Atomicity Chapter 18.2 Concurrency Control Deadlock Handling Election Algorithms Reaching Agreement

3. 18.3 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Chapter Objectives Chapter 18.1 To describe various methods for achieving mutual exclusion in a distributed system To explain how atomic transactions can be implemented in a distributed system Chapter 18.2 To show how some of the concurrency-control schemes discussed in Chapter 6 can be modified for use in a distributed environment To present schemes for handling deadlock prevention, deadlock avoidance, and deadlock detection in a distributed system

4. 18.4 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Background When we are dealing with distributed systems, we have unique activities that must be addressed. A number of these deal with mutual exclusion and synchronization. Is synchronization handled centrally or not? Problems with deadlock are clearly related. Many of the activities – and solutions – deal with an ordering of events that take place. So we will start out with Event Ordering.

5. 18.5 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts 1. Event Ordering Ordering in a centralized system is facilitated with common memory and a single clock. We can ensure that one event ‘occurs’ before another. We know, for example, that we can allocate a resource to a process after a different process releases it. We can say that one event must occur prior to a second event. Clearly, in a distributed environment, this is not an easy case…

6. 18.6 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Event Ordering - continued In a distributed system, we need a distributed algorithm to control a ‘happened before’ relation and apply this to all events in the system. Notation : Let’s use the following conventions: as applied to sequential processes: Happened-before relation (denoted by  ) If A and B are events in the same process, and A was executed before B, then A  B If A is the event of sending a message by one process and B is the event of receiving that message by another process, then A  B If A  B and B  C then A  C Further, an event cannot occur before itself. Concurrent Events: If two events are NOT related by , that is A did not happen before B and B did not happen before A, we say that these two events were executed concurrently. There is no cause-effect relationship between the two; however, it is possible for event A to affect event B causally. Let’s consider the next slide…

7. 18.7 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Relative Time for Three Concurrent Processes Labeled dots represent events that are part of processes (or processors). The wavy line implies that a message is sent from one process to the other. Events are concurrent “iff” no path exists between them. Can see p1  q2; p1  q4 (since p1  q2 and q2  q4) But there are some concurrent events here too: q0 and p2; r0 and q3 and others. Now, importantly, we don’t know which of q0 and p2 occurred first. But for happened before events, there is some kind of order agreed to.

8. 18.8 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Implementation of  To implement a ‘happened before’ feature, we need a common clock or a perfectly synchronized set of clocks. But we don’t have these in distributed systems. One approach is to use a timestamp for each event. Then we can establish some kind of global ordering By require this for all system events, then for every pair of events A and B, if A  B, then the timestamp of A is less than the timestamp of B But how do we do this? Within each process Pi we have a logical clock, LCi associated with it. The logical clock can be implemented as a simple counter incremented in a monotonically increasing fashion. Thus a number can be assigned to each event and these values can be compared. So, for events within the same process, this notion of a global ordering is met, and this is good, But…this approach does not ensure a global ordering across different processes / processors..

9. 18.9 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Implementation of  For different processors: Issues arise almost immediately with the recognition that clocks on certain processors operate more slowly than for others. So what to do? One approach is to require a process to advance its logical clock when it receives a message whose timestamp is greater than the current value of its clock. This makes perfect sense and thus puts the ‘logical clocks’ compatible. Only fly in the ointment is if two timestamps are the same.  Here, events are considered concurrent.  There are other techniques to deal with this – ahead. In particular, we can use process identity numbers to break ties and to create the total ordering we need.

10. 18.10 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts 2. Distributed Mutual Exclusion (DME) Here, we will discuss mutual exclusion, deadlock, starvation problems that may occur in a distributed system. Assumptions The system consists of n processes; each process P i resides at a different processor Each process has a critical section that requires mutual exclusion Processes are numbered sequentially from 1 to n; result is that each process has its own processor. Requirement If P i is executing in its critical section, then no other process P j is executing in its critical section We present two algorithms to ensure the mutual exclusion execution of processes in their critical sections The two approaches are the Centralized Approach and the Fully-Distributed Approach

11. 18.11 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts DME: Centralized Approach (1 of 2) This is a simpler approach by far: One of the processes in the system is chosen to coordinate the entry to the critical section A process that wants to enter its critical section sends a request message to the coordinator The coordinator decides which process can enter the critical section next, and its sends that process a reply message When the process receives a reply message from the coordinator, it enters its critical section After exiting its critical section, the process sends a release message to the coordinator and proceeds with its execution This scheme requires three messages per critical-section entry: request reply release

12. 18.12 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts DME: Centralized Approach (2 of 2) The coordinator must determine if any other process is in its critical section in order to send back a reply message. If a process is in its critical section, then the request is queued. When the coordinator receives a release message, it can access its queue of queued request messages and then send a reply message to the initiating process. This implementation is essentially a FCFS scheduler. Thus it is: Fair, and Prevents Starvation, and Ensures mutual exclusion. Of course, if the coordinator fails then there must be some algorithm available to reestablish a coordinator which will poll processes in the system in order to rebuilt its request queue.

13. 18.13 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts DME: Fully Distributed Approach Ah, but now we have the real power …. And complexity!! When process P i wants to enter its critical section, it generates a new timestamp, TS, and sends the message request (P i, TS) to all other processes in the system When process P j receives a request message, it may reply immediately or it may defer sending a reply back When process P i receives a reply message from all other processes in the system, it can enter its critical section After exiting its critical section, the process sends reply messages to all its deferred requests

14. 18.14 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts DME: Fully Distributed Approach (Cont.) The decision whether process P j replies immediately to a request(P i, TS) message or defers its reply is based on three factors: If P j is in its critical section, then it defers its reply to P i If P j does not want to enter its critical section, then it sends a reply immediately to P i If P j wants to enter its critical section but has not yet entered it, then it compares its own request timestamp with the timestamp TS  If its own request timestamp is greater than TS, then it sends a reply immediately to P i (P i asked first)  Otherwise, the reply is deferred

15. 18.15 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Desirable Behavior of Fully Distributed Approach This distributed approach provides three nice features: Mutual exclusion is established – as before, Freedom from Deadlock is ensured Freedom from starvation is ensured, since entry to the critical section is scheduled according to the timestamp ordering and all requests will sometime get a reply message returned. The timestamp ordering ensures that processes are served in a first-come, first served order So, these look pretty good. But unfortunately, there are three ‘downsides.’

16. 18.16 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Three Undesirable Consequences 1. The processes need to know the identity of all other processes in the system, which makes the dynamic addition and removal of processes more complex This means that processes recdeive names of other processes and the names of a new process must be distributed to all other processes in the group! If one of the processes fails, then the entire scheme collapses This can be dealt with by continuously monitoring the state of all the processes in the system If a process goes down, then all processes need to be notified so that they don’t send request messages to that process. Of course, when a process is restored, all processes must be similarly informed so that they can send request messages to that restored site. Clearly this introduces a great deal of overhead! Processes that have not entered their critical section must pause frequently to assure other processes that they intend to enter the critical section This protocol is therefore suited for small, stable sets of cooperating processes

17. 18.17 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Token-Passing Approach Circulate a token among processes in system Token is special type of message Possession of token entitles holder to enter critical section Processes logically organized in a ring structure Don’t need to literally be a ring, but organized like a ring so that a token can be passed from one process to another. Once process is complete, the token is passed to the next process in the logical ring. Unidirectional ring guarantees freedom from starvation Two types of failures Lost token – election must be called Failed processes – new logical ring established and all processes must be informed. All must be informed with a process is restored as well.

18. 18.18 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Atomicity Either all the operations associated with a program unit are executed to completion, or none are performed This is a complicated process in a distributed system. Ensuring atomicity in a distributed system requires a transaction coordinator, which is responsible for the following: Starting the execution of the transaction Breaking the transaction into a number of subtransactions, and distribution these subtransactions to the appropriate sites for execution Coordinating the termination of the transaction, which may result in the transaction being committed at all sites or aborted at all sites Also note that each site has its own transaction coordinator for requests sent to it. It, in turn, must coordinate the execution of all transactions initiated at that site.

19. 18.19 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Two-Phase Commit Protocol (2PC) This is pretty interesting and complicated… Since we are talking distributed execution, parts of a process may be executed at a number of cooperating sites. For atomicity to be guaranteed, all participating sites must be on board. A transaction T must either commit at all sites or must abort at all sites. There is no middle ground. To guarantee all sites are on board – more precisely, to guarantee atomicity, the transaction coordinator of T must execute a commit protocol, the most popular of which is a two-phase commit (2PC) protocol. Consider a transaction T, at site S that has a transaction coordinator C at that site. When all sites where T (or parts of T) has been executed tell the coordinator, C, that T is done, the coordinator, C, starts the 2PC protocol.

20. 18.20 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Phase 1: Obtaining a Decision C i adds record to the log and records this record on stable storage. C i sends message to all sites. When a site receives a message, the transaction manager at that site determines if it can commit the transaction. If this transaction manager decides on ‘no’: it adds a record to the log and responds to C i with message. If yes, the transaction manager at this site:  adds a record to the log  force all log records for T onto stable storage  transaction manager sends message to C i

21. 18.21 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Phase 1 (Cont.) The initial Transaction Coordinator collects responses All respond “ready”, decision is commit At least one response is “abort”, decision is abort At least one participant fails to respond within time out period, decision is abort

22. 18.22 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Phase 2: Recording Decision in the Database Then the Transaction Coordinator adds a decision record or to its log and forces record onto stable storage Once that record reaches stable storage it is irrevocable (even if failures occur) Coordinator sends a message to each participant informing it of the decision (commit or abort) Receiving site records the message in the log; that is, participants take appropriate action locally

23. 18.23 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts More on 2PC It is interesting to note that any site that T or part of T has be executed may unconditionally abort T at any time before sending a ready T message to the coordinator. The ready T is essentially a promise to follow the coordinator’s order to commit T or to abort T. But the site can only make such a promise when all the needed information it requires is available in its stable storage (disk) so that in the event the site crashes, the non-volatility nature of the stable-storage enables it to follow through on its promise, once it is up and running again. Also interesting that it only takes a single abort T to kill any potential commit T. But the final decision is rendered by the transaction coordinator which writes this decision to its log and forces it onto stable storage. A nice ‘touch’ in some implementations of the 2PC protocol is that some sites send an acknowledge T back to the coordinator at the end of the second phase of the 2PC protocol.

24. 18.24 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Failure Handling in 2PC – Site Failure The log contains a record In this case, the site executes redo(T) The log contains an record In this case, the site executes undo(T) The contains a record; consult C i If C i is down, site sends query-status T message to the other sites The log contains no control records concerning T In this case, the site executes undo(T)

25. 18.25 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Failure Handling in 2PC – Coordinator C i Failure If an active site contains a record in its log, the T must be committed If an active site contains an record in its log, then T must be aborted If some active site does not contain the record in its log then the failed coordinator C i cannot have decided to commit T Rather than wait for C i to recover, it is preferable to abort T All active sites have a record in their logs, but no additional control records In this case we must wait for the coordinator to recover Blocking problem – T is blocked pending the recovery of site S i

26. 18.26 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Concurrency Control Modify the centralized concurrency schemes to accommodate the distribution of transactions Transaction manager coordinates execution of transactions (or subtransactions) that access data at local sites Local transaction only executes at that site Global transaction executes at several sites

27. 18.27 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Locking Protocols Can use the two-phase locking protocol in a distributed environment by changing how the lock manager is implemented Nonreplicated scheme – each site maintains a local lock manager which administers lock and unlock requests for those data items that are stored in that site Simple implementation involves two message transfers for handling lock requests, and one message transfer for handling unlock requests Deadlock handling is more complex

28. 18.28 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Single-Coordinator Approach A single lock manager resides in a single chosen site, all lock and unlock requests are made a that site Simple implementation Simple deadlock handling Possibility of bottleneck Vulnerable to loss of concurrency controller if single site fails Multiple-coordinator approach distributes lock-manager function over several sites

29. 18.29 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Majority Protocol Avoids drawbacks of central control by dealing with replicated data in a decentralized manner More complicated to implement Deadlock-handling algorithms must be modified; possible for deadlock to occur in locking only one data item

30. 18.30 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Biased Protocol Similar to majority protocol, but requests for shared locks prioritized over requests for exclusive locks Less overhead on read operations than in majority protocol; but has additional overhead on writes Like majority protocol, deadlock handling is complex

31. 18.31 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Primary Copy One of the sites at which a replica resides is designated as the primary site Request to lock a data item is made at the primary site of that data item Concurrency control for replicated data handled in a manner similar to that of unreplicated data Simple implementation, but if primary site fails, the data item is unavailable, even though other sites may have a replica

32. 18.32 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Timestamping Generate unique timestamps in distributed scheme: Each site generates a unique local timestamp The global unique timestamp is obtained by concatenation of the unique local timestamp with the unique site identifier Use a logical clock defined within each site to ensure the fair generation of timestamps Timestamp-ordering scheme – combine the centralized concurrency control timestamp scheme with the 2PC protocol to obtain a protocol that ensures serializability with no cascading rollbacks

33. 18.33 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Generation of Unique Timestamps

34. 18.34 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Deadlock Prevention Resource-ordering deadlock-prevention – define a global ordering among the system resources Assign a unique number to all system resources A process may request a resource with unique number i only if it is not holding a resource with a unique number grater than i Simple to implement; requires little overhead Banker’s algorithm – designate one of the processes in the system as the process that maintains the information necessary to carry out the Banker’s algorithm Also implemented easily, but may require too much overhead

35. 18.35 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Timestamped Deadlock-Prevention Scheme Each process P i is assigned a unique priority number Priority numbers are used to decide whether a process P i should wait for a process P j ; otherwise P i is rolled back The scheme prevents deadlocks For every edge P i  P j in the wait-for graph, P i has a higher priority than P j Thus a cycle cannot exist

36. 18.36 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Wait-Die Scheme Based on a nonpreemptive technique If P i requests a resource currently held by P j, P i is allowed to wait only if it has a smaller timestamp than does P j (P i is older than P j ) Otherwise, P i is rolled back (dies) Example: Suppose that processes P 1, P 2, and P 3 have timestamps t, 10, and 15 respectively if P 1 request a resource held by P 2, then P 1 will wait If P 3 requests a resource held by P 2, then P 3 will be rolled back

37. 18.37 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Would-Wait Scheme Based on a preemptive technique; counterpart to the wait-die system If P i requests a resource currently held by P j, P i is allowed to wait only if it has a larger timestamp than does P j (P i is younger than P j ). Otherwise P j is rolled back (P j is wounded by P i ) Example: Suppose that processes P 1, P 2, and P 3 have timestamps 5, 10, and 15 respectively If P 1 requests a resource held by P 2, then the resource will be preempted from P 2 and P 2 will be rolled back If P 3 requests a resource held by P 2, then P 3 will wait

38. 18.38 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Two Local Wait-For Graphs

39. 18.39 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Global Wait-For Graph

40. 18.40 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Deadlock Detection – Centralized Approach Each site keeps a local wait-for graph The nodes of the graph correspond to all the processes that are currently either holding or requesting any of the resources local to that site A global wait-for graph is maintained in a single coordination process; this graph is the union of all local wait-for graphs There are three different options (points in time) when the wait-for graph may be constructed: 1. Whenever a new edge is inserted or removed in one of the local wait-for graphs 2.Periodically, when a number of changes have occurred in a wait-for graph 3.Whenever the coordinator needs to invoke the cycle-detection algorithm Unnecessary rollbacks may occur as a result of false cycles

41. 18.41 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Detection Algorithm Based on Option 3 Append unique identifiers (timestamps) to requests form different sites When process P i, at site A, requests a resource from process P j, at site B, a request message with timestamp TS is sent The edge P i  P j with the label TS is inserted in the local wait-for of A. The edge is inserted in the local wait-for graph of B only if B has received the request message and cannot immediately grant the requested resource

42. 18.42 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts The Algorithm 1.The controller sends an initiating message to each site in the system 2.On receiving this message, a site sends its local wait-for graph to the coordinator 3.When the controller has received a reply from each site, it constructs a graph as follows: (a)The constructed graph contains a vertex for every process in the system (b) The graph has an edge Pi  Pj if and only if (1) there is an edge Pi  Pj in one of the wait-for graphs, or (2) an edge Pi  Pj with some label TS appears in more than one wait-for graph If the constructed graph contains a cycle  deadlock

43. 18.43 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Local and Global Wait-For Graphs

44. 18.44 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Fully Distributed Approach All controllers share equally the responsibility for detecting deadlock Every site constructs a wait-for graph that represents a part of the total graph We add one additional node P ex to each local wait-for graph If a local wait-for graph contains a cycle that does not involve node P ex, then the system is in a deadlock state A cycle involving P ex implies the possibility of a deadlock To ascertain whether a deadlock does exist, a distributed deadlock-detection algorithm must be invoked

45. 18.45 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Augmented Local Wait-For Graphs

46. 18.46 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Augmented Local Wait-For Graph in Site S2

47. 18.47 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Election Algorithms Determine where a new copy of the coordinator should be restarted Assume that a unique priority number is associated with each active process in the system, and assume that the priority number of process P i is i Assume a one-to-one correspondence between processes and sites The coordinator is always the process with the largest priority number. When a coordinator fails, the algorithm must elect that active process with the largest priority number Two algorithms, the bully algorithm and a ring algorithm, can be used to elect a new coordinator in case of failures

48. 18.48 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Bully Algorithm Applicable to systems where every process can send a message to every other process in the system If process P i sends a request that is not answered by the coordinator within a time interval T, assume that the coordinator has failed; P i tries to elect itself as the new coordinator P i sends an election message to every process with a higher priority number, P i then waits for any of these processes to answer within T

49. 18.49 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Bully Algorithm (Cont.) If no response within T, assume that all processes with numbers greater than i have failed; P i elects itself the new coordinator If answer is received, P i begins time interval T´, waiting to receive a message that a process with a higher priority number has been elected If no message is sent within T´, assume the process with a higher number has failed; P i should restart the algorithm

50. 18.50 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Bully Algorithm (Cont.) If P i is not the coordinator, then, at any time during execution, P i may receive one of the following two messages from process P j P j is the new coordinator (j > i). P i, in turn, records this information P j started an election (j > i). P i, sends a response to P j and begins its own election algorithm, provided that Pi has not already initiated such an election After a failed process recovers, it immediately begins execution of the same algorithm If there are no active processes with higher numbers, the recovered process forces all processes with lower number to let it become the coordinator process, even if there is a currently active coordinator with a lower number

51. 18.51 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Ring Algorithm Applicable to systems organized as a ring (logically or physically) Assumes that the links are unidirectional, and that processes send their messages to their right neighbors Each process maintains an active list, consisting of all the priority numbers of all active processes in the system when the algorithm ends If process Pi detects a coordinator failure, I creates a new active list that is initially empty. It then sends a message elect(i) to its right neighbor, and adds the number i to its active list

52. 18.52 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Ring Algorithm (Cont.) If P i receives a message elect(j) from the process on the left, it must respond in one of three ways: 1. If this is the first elect message it has seen or sent, P i creates a new active list with the numbers i and j  It then sends the message elect(i), followed by the message elect(j) 2. If i  j, then the active list for P i now contains the numbers of all the active processes in the system  P i can now determine the largest number in the active list to identify the new coordinator process 3. If i = j, then P i receives the message elect(i)  The active list for P i contains all the active processes in the system  P i can now determine the new coordinator process.

53. 18.53 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Reaching Agreement There are applications where a set of processes wish to agree on a common “value” Such agreement may not take place due to: Faulty communication medium Faulty processes  Processes may send garbled or incorrect messages to other processes  A subset of the processes may collaborate with each other in an attempt to defeat the scheme

54. 18.54 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Faulty Communications Process P i at site A, has sent a message to process P j at site B; to proceed, P i needs to know if P j has received the message Detect failures using a time-out scheme When P i sends out a message, it also specifies a time interval during which it is willing to wait for an acknowledgment message form P j When P j receives the message, it immediately sends an acknowledgment to P i If P i receives the acknowledgment message within the specified time interval, it concludes that P j has received its message  If a time-out occurs, P j needs to retransmit its message and wait for an acknowledgment Continue until P i either receives an acknowledgment, or is notified by the system that B is down

55. 18.55 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Faulty Communications (Cont.) Suppose that P j also needs to know that P i has received its acknowledgment message, in order to decide on how to proceed In the presence of failure, it is not possible to accomplish this task It is not possible in a distributed environment for processes P i and P j to agree completely on their respective states

56. 18.56 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Faulty Processes (Byzantine Generals Problem) Communication medium is reliable, but processes can fail in unpredictable ways Consider a system of n processes, of which no more than m are faulty Suppose that each process P i has some private value of V i Devise an algorithm that allows each nonfaulty P i to construct a vector X i = (A i,1, A i,2, …, A i,n ) such that:: If P j is a nonfaulty process, then A ij = V j. If P i and P j are both nonfaulty processes, then X i = X j. Solutions share the following properties A correct algorithm can be devised only if n  3 x m + 1 The worst-case delay for reaching agreement is proportionate to m + 1 message-passing delays

57. 18.57 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Faulty Processes (Cont.) An algorithm for the case where m = 1 and n = 4 requires two rounds of information exchange: Each process sends its private value to the other 3 processes Each process sends the information it has obtained in the first round to all other processes If a faulty process refuses to send messages, a nonfaulty process can choose an arbitrary value and pretend that that value was sent by that process After the two rounds are completed, a nonfaulty process Pi can construct its vector Xi = (Ai,1, Ai,2, Ai,3, Ai,4) as follows: A i,j = V i For j  i, if at least two of the three values reported for process P j agree, then the majority value is used to set the value of A ij  Otherwise, a default value (nil) is used

58. End of Chapter 18