Leader Election Algorithm In Distributed Systems – Bully Election Leader Algorithm

Leader Election Algorithm In Distributed Systems – Bully Election Leader Algorithm.

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Contents [hide]

1 Bully Election Algorithm in Distributed Systems
2 How Bully Election Algorithm Works
3 Steps of the Bully Algorithm
4 Example Scenario
5 Advantages of the Bully Algorithm
6 Disadvantages
7 Code Implementation in Python
8 Conclusion
- 8.1 Leader Election Algorithm In Distributed Systems – Bully Election Leader Algorithm
9 Lecture 14: March 21 14.1 Overview 14.2 Leader Election
10 Lecture 2: Leader election algorithms.

Bully Election Algorithm in Distributed Systems

The Bully Election Algorithm is a leader election algorithm used in distributed systems where multiple processes (nodes) need to agree on a single process as their leader. This algorithm is designed for synchronous systems where processes can communicate with each other reliably.

How Bully Election Algorithm Works

The Bully Algorithm operates under the assumption that:

Each process in the system has a unique ID.
Processes communicate using message passing.
Any process can initiate an election if it detects that the current leader has failed.
The process with the highest ID becomes the leader.

Steps of the Bully Algorithm

Election Triggering:
- If a process detects that the leader has failed (no response), it starts an election.
- The process sends “Election” messages to all processes with higher IDs.
Responses from Higher Processes:
- If a higher-ID process is alive, it replies with an “OK” message, indicating it is still active.
- The initiator stops its election, as a higher process will handle the election.
If No Response:
- If no higher-ID processes respond, the initiator declares itself as the leader.
- It sends a “Coordinator” message to all lower-ID processes, informing them of its leadership.
Election by Higher Process:
- If a higher-ID process is available, it initiates its own election, following the same steps.
- This continues until the highest-ID process becomes the leader.

Example Scenario

Assume we have 5 processes in a distributed system with IDs:
P1, P2, P3, P4, P5 (P5 has the highest ID).

P3 detects the leader (P5) has failed.
P3 starts an election and sends an “Election” message to P4 and P5.
P5 is down, but P4 replies with an “OK” message.
P4 starts its own election, sending an “Election” message to P5.
P5 is down, so P4 declares itself as the new leader.
P4 sends a “Coordinator” message to P1, P2, and P3, informing them.

Advantages of the Bully Algorithm

Ensures the highest-ID process becomes the leader.
Works efficiently in failure-prone environments.
Simple to implement in synchronous systems.

Disadvantages

High message overhead (many messages exchanged).
Can cause network congestion in large systems.
Not suitable for asynchronous systems (timeouts may cause false election triggers).

Code Implementation in Python

Here’s a simple implementation of the Bully Algorithm in Python:

class Process:

    def __init__(self, id, processes):

        self.id = id

        self.processes = processes

        self.leader = None
    def start_election(self):

        print(f"Process {self.id} started an election.")

        higher_processes = [p for p in self.processes if p.id > self.id]



 

        if not higher_processes:

            self.become_leader()

        else:

            for p in higher_processes:

                p.receive_election(self)
    def receive_election(self, initiator):

        print(f"Process {self.id} received an election message from {initiator.id}. Sending OK.")

        initiator.receive_ok()

        self.start_election()



 

    def receive_ok(self):

        pass  # This process will wait for another leader announcement
    def become_leader(self):

        print(f"Process {self.id} becomes the leader.")

        for p in self.processes:

            p.leader = self

        self.announce_leader()



 

    def announce_leader(self):

        for p in self.processes:

            print(f"Process {p.id} acknowledges {self.id} as the leader.")
# Example execution

p1 = Process(1, [])

p2 = Process(2, [])

p3 = Process(3, [])

p4 = Process(4, [])

p5 = Process(5, [])  # Highest ID, should become leader



 

all_processes = [p1, p2, p3, p4, p5]

for p in all_processes:

    p.processes = all_processes  # Assign all processes to each one

p3.start_election() # Trigger election from Process 3

Conclusion

The Bully Election Algorithm is widely used in distributed computing to ensure there is a single leader in a system. However, due to its high message complexity, alternatives like the Ring Election Algorithm or Paxos are sometimes preferred in large-scale systems.

Would you like an explanation of an alternative leader election algorithm?

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Leader Election Algorithm In Distributed Systems – Bully Election Leader Algorithm