Locking-based protocols are widely used in concurrency control for Relational Database Management Systems (RDBMS). These protocols use locks to control concurrent access to data and prevent conflicts between transactions. Here are some prominent locking-based protocols:

1. Strict Two-Phase Locking (Strict 2PL):

Strict 2PL is a well-known locking protocol that ensures strict serializability. It follows two simple rules:

- Growing Phase: Transactions acquire all the required locks on data items before accessing them. Once a lock is released, no new locks can be acquired.
- Shrinking Phase: Transactions release all their locks only after the transaction commits or aborts. No new locks can be acquired after releasing any lock.

Strict 2PL guarantees serializability by ensuring that conflicting operations on the same data item do not occur simultaneously. However, it may suffer from lock contention and deadlocks.

2. Rigorous Two-Phase Locking (Rigorous 2PL):

Rigorous 2PL is an extension of Strict 2PL that incorporates the strictness in both read and write operations. It follows the same rules as Strict 2PL but also enforces exclusive locks on data items for read operations, in addition to write operations. This ensures that read operations also honor the locks acquired and prevents any conflicts.

Rigorous 2PL ensures strict serializability by eliminating the possibility of reading uncommitted data or dirty reads. However, it can lead to increased lock contention and potential performance degradation due to the exclusive locks acquired during read operations.

3. Conservative Two-Phase Locking (Conservative 2PL):

Conservative 2PL is a pessimistic locking protocol where locks are acquired before a transaction begins. Each transaction explicitly specifies all the data items it will access, and the system checks for conflicts and ensures that all the required locks can be granted before the transaction starts. This protocol eliminates the possibility of deadlocks since locks are acquired upfront, but it can suffer from lock contention if multiple transactions request locks on the same data items.

4. Deadlock Detection and Prevention:

Deadlock is a situation where two or more transactions are waiting indefinitely for each other to release the locks they hold. To handle deadlocks, locking-based protocols often employ deadlock detection and prevention mechanisms. Deadlock detection periodically examines the lock graph to identify circular wait dependencies among transactions. Deadlock prevention techniques, such as resource ordering or timeouts, are also used to avoid potential deadlocks.

These are some of the prominent locking-based protocols used for concurrency control in RDBMS. The choice of protocol depends on factors such as the expected workload, data access patterns, and the trade-offs between performance and data consistency.

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