1. Causality & Global States

2. P1 P2 P3 12 3 4 5 0 0 0 1 2 Physical Time 4 6 Include(obj1 ) obj1.method() P2 has obj1 Causality violation occurs when order of messages causes an action based on information that another host has not yet received. In designing a DS, potential for causality violation is important

3. Detecting Causality Violation P1 P2 P3 (1,0,0) (2,0,0) Physical Time (2,0,2) Potential causality violation can be detected by vector timestamps. If the vector timestamp of a message is less than the local vector timestamp, on arrival, there is a potential causality violation. 0,0,0 1,0,0 2,0,1 2,2,2 2,1,2 2,0,2 2,0,0 Violation: (1,0,0) < (2,1,2)

4. Communication Modes in DS  Unicast (best effort or reliable)  Messages are sent from exactly one host to one host  Best effort guarantees that if a message is delivered it would be intact  Reliable guarantees delivery of messages.  Broadcast  Messages are sent from exactly one host to all hosts on the same network.  Reliable broadcast protocols are not practical  Multicast  Messages are sent from exactly one host to several hosts on the same or different networks.  Multicast can be implemented above a reliable unicast

5.  Process messages from each host in the order they were sent:  Each processor keeps a sequence number for each host (use own sequence for marking own messages)  When a message is received, as expected, accept higher than expected, buffer in a queue lower than expected, reject Ordering Guarantees (FIFO) If Message# is

6. Example: FIFO Multicast P1 P2 P3 0 0 0 Physical Time 1 0 0 2 0 0 1 0 0 2 0 0 2 1 0 0 0 0 2 1 0 0 0 01 0 0 2 1 0 1 1 1 2 2 1 1 Reject: 1 < 1 + 1 Accept 1 = 0 + 1 Accept: 2 = 1 + 1 2 0 0 Buffer 2 > 0 + 1 Accept: 1 = 0 + 1 2 0 0 Accept Buffer 2 = 1 + 1 Reject: 1 < 1 + 1 Accept 1 = 0 + 1 Sequence Vector 0 0 0

7.  Process messages in an order that guarantees no potential causal violation  Each processor keeps a vector of sequences, one entry for each host  A copy of the vector is sent with each message  When a message is received, If all vector entries are as expected, accept else higher than expected, buffer in a queue lower than expected, reject Ordering Guarantees (Causal) If any vector entry is

8. Example: Causal Ordering Multicast P1 P2 P3 Physical Time (1,1,0) Reject: Accept 0,0,0 1,0,0 1,1,0 1,0,0 Buffer, missin g P1(1) 1,1,0 Accept: 1,0,0 Accept Buffered messag e 1,1,0 (1,0,0) (1,1,0) Accept

9. Process Histories and States  For a process P i, history(P i ) = h i = prefix history(P i k ) = h i k = S i k, P i ‘s State immediately before k th event  For a set of processes, global history, H =  i (h i ) global state, S =  i (S i k i ) a cut C  H = h 1 c1  h 2 c2  …  h n cn the frontier of C = {e i ci, i = 1,2, … n}

10. Consistent States  A cut C is consistent if  e  C (if f  e then f  C)  A global state S is consistent if it corresponds to a consistent cut P1 P2 P3 e10e10 e11e11 e12e12 e13e13 e20e20 e21e21 e22e22 e30e30 e31e31 e32e32 Inconsistent cut Consistent cut

11. Global States  A Run is a total ordering of events in H that is consistent with each h i ’s ordering  A Linearization is a run consistent with happens-before (  ) relation in H.  Linearizations pass through consistent global states.  A global state S k is reachable from global state S i, if there is a lineralization, L, that passes through S i and then through S k.  A DS evolves as a series of transitions between global states S 0, S 1, ….

12. Global State Predicates  A global-state-predicate is a function from the set of global states to {true, false}, e.g. deadlock, termination  A stable global-state-predicate is one that once it becomes true, remains true in subsequent global states, e.g. deadlock  if P is a gobal-state-predicate, then safety(P)   S reachable from S 0, P(S) = false liveness(p)   L  lineralizatoins from S0  S L : L passes through S L & P(S L ) = true  We need a way to record global states

13. The “Snapshot” Algorithm  Records a set of process and channel states such that the combination is a consistent GS.  Assumptions:  No failure, all mages arrive intact, exactly once  Communication channels are unidirectional  Message access is FIFO-ordered  There is a comm. Path between any two processes  Any process may initiate the snapshot (sends Marker)  Snapshot does not interfere with normal execution behavior  Each process records its state and the state of its incoming channels (no central collection)

14. The “Snapshot” Algorithm (2) Marker sending rule for process P i  record P i ’s state  for each outgoing channel C, send a marker on C Marker receiving rule for a process P k, on receipt of a marker over channel C`  if P k has not yet recorded its state -record P k ’s state -record the state of C` as “empty” -turn on recording of messages over other incoming channels -for each outgoing channel C, send a marker on C else -record the state of C` as all the messages received over C` since P k saved its state

15. Snapshot Example P1 P2 P3 e10e10 e20e20 e23e23 e30e30 e13e13 a b M e 1 1,2 M 1- P1 initiates snapshot: records its state (S1); sends Markers to P2 & P3; turns on recording for channels C21 and C31 e 2 1,2,3 M M 2- P2 receives Marker over C12, records its state (S2), sets state(C12) = {} sends Marker to P1 & P3; turns on recording for channel C32 e14e14 3- P1 receives Marker over C21, sets state(C21) = {a} e 3 2,3,4 M M 4- P3 receives Marker over C13, records its state (S3), sets state(C13) = {} sends Marker to P1 & P2; turns on recording for channel C23 e24e24 5- P2 receives Marker over C32, sets state(C32) = {b} e31e31 6- P3 receives Marker over C23, sets state(C23) = {} e13e13 7- P1 receives Marker over C31, sets state(C31) = {}