1. Chap 15. Agreement

2. Problem Processes need to agree on a single bit No link failures A process can fail by crashing (no malicious behavior) Messages take finite (though unbounded) time Looks easy, can this be solved ?

3. Consensus in Asynchronous systems Impossible even if just one process can fail ! (Fischer, Lynch, Peterson – FLP result) N (N ¸ 2) processes Each process starts with an initial value {0,1} that is modeled as the input register x Making a decision is modeled by writing to the output register y Output registers are write once

4. Assumptions Initial independence  Processes can choose their input independently Commute property :  If events e and f are on different processes they commute

5. Assumptions (contd.) Asynchrony of events:  Any receive event can be arbitrarily delayed  Every message is eventually delivered  If e is a receive event and e is enabled at G then se is also enabled at G

6. Requirements Agreement  Two non-faulty processes cannot commit on different values Non-triviality  Both 0 and 1 should be possible outcomes Termination  A non-faulty process terminates in finite time

7. Informal proof of the impossibility result We show that no protocol can satisfy agreement, non-triviality and termination in the presence of even 1 failure We show that :  There is an initial global state in which the system is non-decisive  There exists a way to keep the system non- decisive

8. Indecision Lat G.V be the set of decision values reachable from a global state G Since a non-faulty process terminates, G.V is non- empty G is :  Bivalent: G.V = { 0,1 } – indecisive  0-Valent: G.V = { 0 } – always leads to deciding 0  1-Valent: G.V = { 1 } – always leads to deciding 1 We show that there exists a bivalent initial state

9. Claim: Every consensus protocol has a bivalent initial state Assume claim is false Non-triviality : The initial set of global states must contain 0-valent and 1-valent states Adjacent global states: If they differ in the state of exactly one process There must be adjacent 0-valent and 1-valent states which differ in the state of, say, p Apply a sequence where p does not take any steps Contradiction

10. Claim: There exists a method to keep the system indecisive Event e (on process p) is applicable to G G is the set of global states reachable from G without applying e H = e( G ) Claim : H contains a bivalent global state

11. Assume that H contains no bivalent states Claim 1: H contains both 0-valent and 1- valent states Neighbors : 2 global states are neighbors if one results from the other in a single step Claim 2: There exist neighbors G 0, G 1 such that  H 0 = e(G 0 ) is 0-valent and  H 1 = e(G 1 ) is 1-valent

12. Claim 2:There exist neighbors G 0, G 1 : H 0 = e(G 0 ) is 0-valent and H 1 = e(G 1 ) is 1-valent Let the the smallest sequence of events applied to G without applying e such that et(G) has a different valency from e(G)  Such a sequence exists  The last two global states in the sequence give us the required neighbors

13. w.l.o.g. let G 1 = f(G 0 ) where f is an event on process q. Case 1 : p is different from q  F is applicable to H 0 resulting in H 1  But H 0 is 0-valent and H 1 is 1-valent

14. Case 2:  p=q  Commute property

15. Application: Terminating Reliable Broadcast (TRB) There are N processes in the system and P 0 wants to broadcast a message to all processes.  Termination: Every correct process eventually delivers some message  Validity: If the sender is correct and broadcasts m then all correct processes deliver m  Agreement: If a correct process delivers m then all correct processes deliver m  Integrity: Every correct process delivers at most one message, and if it delivers m ( and m  ‘sender faulty’) then the sender must have broadcasted m

16. TRB is impossible in asynchronous systems Can use TRB to solve consensus If a process receives ‘sender faulty’ it decides on 0 Else it decides on the value of the message received

17. Faults in a distributed system Crash: Processor halts, does not perform any other action and does not recover Crash+Link: Either processor crashes or the link fails and remains inactive. The network may get partitioned Omission: Process sends or receives only a proper subset of messages required for correct operation Byzantine: Process can exhibit arbitrary behavior

18. Consensus in synchronous systems There is an upper bound on the on the message delay and the durations of actions performed by the processes  Consensus under crash failures  Consensus under Byzantine faults

19. Consensus under crash failures Requirements :  Agreement: Non faulty processes cannot decide on different values  Validity: If all processes propose the same value, v, then the decided value should be v  Termination: A non-faulty process decides in a finite time

20. Algorithm f denotes the maximum number of failures Each process maintains V the set of values proposed by other processes (initially it contains only its own value) In every round a process:  Sends to all other processes the values from V that it has not sent before After f+1 rounds each process decides on the minimum value in V

21. Algorithm

22. Proof: Agreement If value x is in V i at correct process i then belongs to the V of all correct processes If x was added to V i in round k<f+1, all correct process will receive that value in round k+1 If x was added to V i in the last round (f+1) then there exists a chain of f+1 processes that have x in their V. At least one of them is non-faulty and will broadcast the value to other correct processes

23. Complexity Message complexity:  O((f+1)N 2 )  If each value needs b bits then the total bits communicated per round is O(bN 3 ) Time:  Needs f+1 rounds

24. Consensus under Byzantine faults Story:  N Byzantine generals out to repel an attack by a Turkish Sultan  Each general has a preference – attack or retreat  Coordinated attack or retreat by loyal generals necessary for victory  Treacherous Byzantine generals could conspire together and send conflicting messages to mislead loyal generals

25. Byzantine General Agreement (BGA) Reliable messages Possible to show that no protocol can tolerate f failures if N · 3f Lets assume N > 4f

26. BGA Algorithm Takes f+1 rounds Rotating coordinator processes (kings) P i is the king in round i Phase 1:  Exchange V with other processes  Based on V decide myvalue (majority value) Phase 2:  Receive value from king- kingvalue  If V has more than N/2 + f copies of myvalue then V[i]=myvalue else V[i]= kingvalue After f+1 rounds decide on V[i]

27. BGA Algorithm

28. Informal proof argument If correct processes agree on a value at the beginning of a round they continue to do so at the end N>4f N-N/2 > 2f N-f > N/2 +f  Each process will receive > N/2+f identical messages At least one non-faulty process becomes the king (f+1 rounds)  In the correct round if any process chooses myvalue then it received more than N/2+f myvalue messages)  Therefore king received more than N/2 myvalue messages, i.e., kingvalue = myvalue

29. Knowledge Knowledge about the system can be increased by communicating with other processes Can use notion of knowledge to prove fundamental results, e.g. Agreement is impossible in asynchronous unreliable systems

30. Notations and definitions K i (b) : process i in group G of processors knows b Someone knows b: Everyone knows b: Everyone knows E(b): E(E(b)) E k (b) : k ¸ 0  E 0 (b) = b and E k+1 (b) = E(E k (b))

31. Notations and definitions Common knowledge C(b): Hence for any k C(b) ) E k (b)

32. Application: Two generals problem The situation:  Enemy camped in valley  Two generals hills separated by enemy  Communication by messengers who have to pass through enemy territory … may be delayed or caught  Generals need to agree whether to attack or retreat Protocol which always solves problem impossible Can we design a protocol that can lead to agreement in some run?

33. Application: Two generals problem Solution: Don’t start a war if your enemy controls the valley Agreement not possible Let r be the run corresponding to the least number of messages that lead to common knowledge Let m be the last message, say it was sent from P to Q Since channel is unreliable P does not know if m was received, hence P can assert C(b) before m was sent Contradiction – r is the minimal run