Lecture 9: Ordered Multicasting

Lecture 9: Ordered Multicasting

TVS: Section 6.2

(CDK: Section 12.4)

Apr 19, 2023 COMP28112 Lecture 9 2

Contents

• What is an ordered multicast?

• Why is it useful?

• How can it be done?– Using logical timestamps


Multicast

• 1 process sends a message to a group of other processes

• More efficient than looping in the application sending a message to each

• May be able to guarantee that either all recipients get the message or none does.


Example: duplicate bank records

• For speed of response to queries, and improved reliability, suppose a bank keeps its database replicated in geographically distant locations (e.g. London & Edinburgh)

• Each update request is sent to both (as a multicast)

• But this leads to an ordering constraint


Fig 6.11 from TvS


The Updates

• Suppose Update 1 credits £100 to an account containing £100

• Suppose Update 2 adds 1% interest to the account.

• If not done in the same order, can get balances of £201 and £202 in the two databases.


Totally-Ordered multicast

• To get the same answers, we need totally-ordered multicast, i.e. all messages are delivered in the same order to each receiver.

• Can be done with Lamport’s logical clocks.• Consider a group of processes multicasting

to each other. • Each message is timestamped with the

logical time of the sender.


T-O Multicast (2)• Assume multicast also goes to the sender• Assume messages from the same sender are received

by any 1 receiver in the order they were sent• Assume that no messages are lost• When message is received, put it in a local queue

ordered by its timestamp.• The receiver multicasts an ACK to all processes.

(Note ACK is not queued!)• A process can “act on” a queued message when it is

at the head of the queue, and has been ACK’d by every other process.

• Each process has the same contents in the queue …!


A

B

C

A will have to process messages in a different order(message delivery can be anything as long as it is the

same for all processes)


Implications

• Note: the need to receive ACKs from all processes reduces advantage of replication! A crashed process will cause everything to stop ….

• Keeping replicas consistent by executing same operations in the same order is a general technique (state machine replication)


Causally-Ordered Multicasting

• Weaker than totally-ordered because unrelated messages can be processed in different orders on different machines.

• Useful on, e.g., a bulletin board – may want messages delivered in the correct order where they are related, but not to tie down ordering between messages on unrelated topics


C-O multicasting

• Now we use Vector clocks – but only noticing sends as events ….

• Suppose Pj receives message m from Pi with timestamp ts(m)

• Delay delivery to application until:– ts(m)[i] = VCj[i] + 1– ts(m)[k] <= VCj[k] for all other k


C-O multicasting (2)

• The 1st condition means that this is the next message Pj was expecting from Pi

• The 2nd means that Pj has seen all the messages seen by Pi when it sent message m.


Example

P0

P1

P2

(1,0,0)

(1,1,0)

(1,1,0)

(0,0,0) (1,0,0) (1,1,0)

m m m*

m*delay


Explanation

• m* from P1 arrives at P2 before m from P0

• But m* was sent after m arrived at P1

• Therefore delivery of m* in P2 is delayed until after m has been delivered.


End-to-end argument

• Some systems have provided T-O and C-O multicasting (e.g. ISIS)

• Some debate about whether this is a Good Thing or not

• Two main problems:– Not all causality is real (e.g. 1 sender may send

unrelated messages, but the system will believe the order matters)


E-to-E argument (cont.)

– Not all causality may be captured. E.g. users of the bulletin board might discuss issues offline and then post related messages without reading logically preceding ones first.

• A particular application will have its own approach, but we may or may not want to build it on top of an infrastructure which assumes the answers.


Exercisea b c d f

g i j k l m

n o p q r s

Use (i) Lamport Clocks; (ii) Vector Clocks to order the events

Documents

Lecture 9: Ordered Multicasting