Graph Based Concurrency Control Protocol in DBMS (original) (raw)

Last Updated : 25 Oct, 2025

In a Database Management System (DBMS), multiple transactions often execute concurrently, which can lead to conflicts when they access the same data items. The Graph-Based Concurrency Control Protocol manages these conflicts using a directed graph structure to ensure conflict serializability and consistency.

• Transactions -> Nodes
• Conflicts (dependencies) -> Edges

Before granting a lock, the system checks the graph:

• If adding a new edge creates a cycle, a deadlock is detected.
• To resolve it, one of the transactions is rolled back to break the cycle.

**Note: Thus, the protocol ensures that the serialization graph remains acyclic, maintaining database consistency.

Properties

• **Deadlock-Free: Since cycles are not allowed, deadlocks cannot occur.
• **No guarantee of recoverability: Transactions can still cause cascading rollbacks.
• **More powerful than simple lock-based protocols because it can handle complex dependencies.
• **Computationally expensive for large databases due to cycle detection and graph maintenance.

Partial Ordering Requirement

Before applying the protocol, a partial ordering is defined on the set of data items. Let the set of database items be D = {d₁, d₂, d₃, ..., dₙ}. If dᵢ -> dⱼ, then any transaction accessing both must access dᵢ before dⱼ.

**Note: This ordering forms a Directed Acyclic Graph (DAG) - called the Database Graph.

Tree Based Protocol

The Tree Protocol is a graph-based concurrency control method that ensures conflict serializability and deadlock freedom. Unlike Two-Phase Locking (2PL), it follows a hierarchical structure for locking data items.

Rules of Tree Protocol:

1. **Only exclusive (X) locks are allowed: No shared (S) locks are used.
2. **The first lock can be on any data item: After that, a transaction can lock a data item only if it has locked its parent first.
3. **Data items can be unlocked at any time: There is no strict two-phase rule.
4. **No relocking: Once a transaction unlocks a data item, it cannot lock it again.

**Note: The Tree Protocol offers a balance between concurrency and deadlock prevention, making it useful in certain database applications.

**Image - Database Graph

Let's look at an example based on the above Database Graph. We have three Transactions in this schedule and this is a skeleton example, i.e, we will only see how Locking and Unlocking work, let's keep this simple and not make this complex by adding operations on data.

• From the above example, first see that the schedule is Conflict Serializable.
• Serializability for Locks can be written as T2 -> T1 -> T3.
• Data items Locked and Unlocked are following the same rule as given above and follow the Database Graph.

Advantages of Tree Protocol

• **Deadlock-free – No cycles form in the lock order, so no rollbacks are needed.
• **Increased concurrency – Unlocking can happen earlier than in Two-Phase Locking, reducing wait times.
• **Allows different schedules – Some schedules that are not possible under 2PL can be executed under the tree protocol.

Drawbacks of Tree Protocol

• **No guarantee of recoverability – Can lead to cascading rollbacks if not handled properly.
• **Extra locks required – Transactions may need to lock unnecessary data items, increasing waiting time and locking overhead.
• **Some schedules allowed in 2PL are not possible in Tree Protocol – While it provides flexibility, it also has limitations.