LOGICAL CLOCK IN DISTRIBUTED SYSTEM HAPPENED BEFORE CLOCK CLOCK SYNC CLOCK VECTOR

LOGICAL CLOCK IN DISTRIBUTED SYSTEM HAPPENED BEFORE CLOCK CLOCK SYNC CLOCK VECTOR.

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Here’s a clear and concise explanation of Logical Clocks in Distributed Systems, including concepts like Happened-Before Relation, Lamport Clock, Vector Clock, and Clock Synchronization.

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LOGICAL CLOCK IN DISTRIBUTED SYSTEMS

In distributed systems, there’s no global clock. So, we use logical clocks to order events correctly across multiple processes (nodes).

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1. Happened-Before Relation (→) – by Leslie Lamport

This defines a partial order of events.

Definition:

• If A and B are events in the same process and A occurs before B → A → B

• If A is sending a message and B is receiving the same → A → B

• If A → B and B → C → then A → C (transitivity)

Purpose: Establish a cause-effect relationship between events in different processes.

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2. Lamport’s Logical Clock (Scalar Clock)

Goal: Assign numbers (timestamps) to events to maintain A → B ⇒ timestamp(A) < timestamp(B)

Rules:

1. Each process maintains a local clock (initially 0).

2. Before executing any event, increment the clock: C := C + 1

3. When sending a message, send timestamp with it.

4. On receiving a message with timestamp T, set:
   C := max(C, T) + 1

Limitation:

• It can say one event happened before another but not if two events are concurrent.

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3. Vector Clocks

Goal: Detect causal relationships and concurrent events accurately.

How it works:

• Each process keeps a vector V[i] of size n (number of processes).

• Before event: V[i] := V[i] + 1

• On sending message, send vector.

• On receiving message with vector V':

  • V[i] := V[i] + 1

  • For all j ≠ i, V[j] := max(V[j], V'[j])

Comparison:

• Event A happened before B ⇨ V(A) < V(B) (element-wise)

• Events concurrent ⇨ V(A) and V(B) are not comparable

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4. Clock Synchronization

Since there’s no common clock:

• NTP (Network Time Protocol): Sync real clocks (physical)

• Cristian’s Algorithm: Get time from time server (1 request)

• Berkeley Algorithm: Average times across nodes

These aim to reduce clock drift and keep system-wide time in sync, though not perfect.

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Summary Table

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Real-World Use

• Databases (like Cassandra, DynamoDB) → use vector clocks for conflict resolution.

• Distributed logs (Kafka) → maintain event order.

• Debugging distributed systems → to trace event flows.

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Would you like:

• A diagram of these clocks in action?

• Sample code in Python or Java to simulate this?

• Or a PDF summary sheet for revision?

Let me know!

LOGICAL CLOCK IN DISTRIBUTED SYSTEM HAPPENED BEFORE CLOCK CLOCK SYNC CLOCK VECTOR

Clocks in Distributed System