Improving Performance in Distributed Database Systems Using Speculative Transaction Processing

In distributed database systems (DDBSs), a transaction acquires the locks on the data objects during the execution and releases them only after the completion of commit processing. In DDBSs, it can be observed that, even though a transaction produces new data object values on completion of execution and these new data object values are not a ected during commit processing, the locks are released only after completion of commit processing. In this paper, we propose speculative distributed transaction processing (SDTP) approach, which allows the transaction to release locks on the data objects on completion of its execution. On completion of transaction's execution, by accessing both original and updated values, the waiting transaction carries out speculative executions and then starts commit processing. Before the end of commit processing, the transaction that has carried out speculative executions retains appropriate execution based on the termination decisions of preceding transactions. Thus, con icting transactions can be processed in parallel without violating the serializability criteria. In this paper, we have explained the transaction processing strategy employing speculation and then presented SDTP algorithm. This approach is free from cascading aborts. Also, SDTP approach does not require extra number of messages since every message is piggy backed with the messages of commit processing. However, it needs both extra processing power and main memory to support speculative executions. This approach can be tuned according to the resources available in the system. Through simulation experiments, it has been shown that SDTP approach considerably reduces the response time in the case of higher resource con icts and longer transmission times. This approach suits best for the wide area network environments where the message transmission time dominates the processing time.