Time stamp Ordering

In Database Management Systems (DBMS), multiple users or applications often try to access and modify the database at the same time. This creates the possibility of concurrency problems, such as lost updates, dirty reads, and inconsistent results. To avoid these problems, DBMS uses concurrency control techniques.

One of the most important techniques is Timestamp Ordering (TO) protocol. It ensures transactions are executed in a consistent and conflict-free manner using timestamps.

Understanding Timestamps

A timestamp is a unique identifier assigned to each transaction when it starts. It is usually based on:

• System clock time (e.g., the exact time of transaction arrival), or
• A logical counter that increases with every new transaction.

The timestamp reflects the order of arrival of transactions. For example:

• Transaction T1 starts at 10:00:05 → Timestamp = 5
• Transaction T2 starts at 10:00:07 → Timestamp = 7

Here, T1 is older than T2.

The Idea of Timestamp Ordering

The Timestamp Ordering protocol ensures that transactions are executed in the order of their timestamps, regardless of when they actually get executed.

In other words:

• If a transaction T1 is older than T2 (TS(T1) < TS(T2)), then T1 should access database items before T2, whenever both transactions want to use the same item.

This prevents conflicts and maintains the database in a consistent state.

Key Rules in Timestamp Ordering

For each data item (say X), the system keeps two important values:

1. Read Timestamp (RTS(X)) – The largest timestamp of a transaction that has successfully read X.
2. Write Timestamp (WTS(X)) – The largest timestamp of a transaction that has successfully written X.

Now, when a transaction requests a read or write, DBMS applies the following rules:

1. Read Operation (Read(X)):

• If TS(T) < WTS(X) → The transaction is too old and wants to read a value that has already been overwritten by a newer transaction.
  → The read is rejected and transaction T is aborted.
• Otherwise → Allow the read and update RTS(X) = max(RTS(X), TS(T)).

2. Write Operation (Write(X)):

• If TS(T) < RTS(X) → Transaction is too old because a newer transaction has already read the item.
  → Writing now would create inconsistency → Abort T.
• If TS(T) < WTS(X) → A newer transaction has already written the item.
  → Again, Abort T.
• Otherwise → Allow the write and set WTS(X) = TS(T).

This ensures that no conflicting operations violate timestamp order.

Example of Timestamp Ordering

Suppose two transactions are running:

• T1 (TS = 5): Wants to read and write on item X.
• T2 (TS = 10): Wants to write on X.

Steps:

1. T1 reads X. → Allowed, RTS(X) = 5.
2. T2 tries to write X. → TS(T2) = 10 > RTS(X) = 5 → Allowed, WTS(X) = 10.
3. Later, T1 tries to write X. → TS(T1) = 5 < WTS(X) = 10 → Not allowed, so T1 is aborted.

Here, timestamp ordering ensures T1 (older) does not overwrite the changes of T2 (newer).

Advantages of Timestamp Ordering

1. Simple and clear – Easy to implement since transactions are ordered based on timestamps.
2. No deadlocks – Unlike locking protocols, timestamp ordering does not require waiting. Transactions are simply aborted and restarted if they violate rules.
3. Fair execution order – Older transactions always get priority.

Disadvantages of Timestamp Ordering

1. High abort rate – If there are many conflicts, older transactions may be frequently aborted.
2. Wasted work – A transaction may do a lot of processing but still get aborted at the end.
3. Starvation – If conflicts keep happening, some transactions may never finish.

Variants of Timestamp Ordering

1. Basic Timestamp Ordering (BTO): The standard version described above.
2. Strict Timestamp Ordering (STO): Ensures that a transaction cannot overwrite uncommitted values, making recovery easier.
3. Multiversion Timestamp Ordering (MVTO): Keeps multiple versions of data items, allowing both old and new transactions to proceed without many aborts.

Conclusion

Timestamp Ordering in DBMS is a powerful concurrency control method that ensures transactions are executed in a consistent and serializable order using timestamps. While it avoids deadlocks and maintains fairness, it may suffer from frequent transaction rollbacks in highly concurrent environments.

Despite its limitations, timestamp ordering plays a crucial role in modern databases and forms the basis for more advanced techniques like multiversion concurrency control (MVCC).