94 research outputs found

    An Efficient Concurrency Control Technique for Mobile Database Environment

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    Day by day wireless networking technology and mobile computing devices are becoming more popular for their mobility as well as great functionality Now it is an extremely growing demand to process mobile transactions in mobile databases that allow mobile users to access and operate data anytime and anywhere irrespective of their physical positions Information is shared among multiple clients and can be modified by each client independently However for the assurance of timely access and correct results in concurrent mobile transactions concurrency control techniques CCT happen to be very difficult Due to the properties of Mobile databases e g inadequate bandwidth small processing capability unreliable communication mobility etc existing mobile database CCTs cannot employ effectively With the client-server model applying common classic pessimistic techniques of concurrency control like 2PL in mobile database leads to long duration Blocking and increasing waiting time of transactions Because of high rate of aborting transactions optimistic techniques aren t appropriate in mobile database as well This paper discusses the issues that need to be addressed when designing a CCT technique for Mobile databases analyses the existing scheme of CCT and justify their performance limitations A modified optimistic concurrency control scheme is proposed which is based on the number of data items cached amount of execution time and current load of the database server Experimental results show performance benefits such as increase in average response time and decrease in waiting time of the transaction

    A Concurrency Control Method Based on Commitment Ordering in Mobile Databases

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    Disconnection of mobile clients from server, in an unclear time and for an unknown duration, due to mobility of mobile clients, is the most important challenges for concurrency control in mobile database with client-server model. Applying pessimistic common classic methods of concurrency control (like 2pl) in mobile database leads to long duration blocking and increasing waiting time of transactions. Because of high rate of aborting transactions, optimistic methods aren`t appropriate in mobile database. In this article, OPCOT concurrency control algorithm is introduced based on optimistic concurrency control method. Reducing communications between mobile client and server, decreasing blocking rate and deadlock of transactions, and increasing concurrency degree are the most important motivation of using optimistic method as the basis method of OPCOT algorithm. To reduce abortion rate of transactions, in execution time of transactions` operators a timestamp is assigned to them. In other to checking commitment ordering property of scheduler, the assigned timestamp is used in server on time of commitment. In this article, serializability of OPCOT algorithm scheduler has been proved by using serializability graph. Results of evaluating simulation show that OPCOT algorithm decreases abortion rate and waiting time of transactions in compare to 2pl and optimistic algorithms.Comment: 15 pages, 13 figures, Journal: International Journal of Database Management Systems (IJDMS

    An Efficient Concurrency Control Technique for Mobile Database Environment

    Get PDF
    Day by day, wireless networking technology and mobile computing devices are becoming more popular for their mobility as well as great functionality. Now it is an extremely growing demand to process mobile transactions in mobile databases that allow mobile users to access and operate data anytime and anywhere, irrespective of their physical positions. Information is shared among multiple clients and can be modified by each client independently. However, for the assurance of timely access and correct results in concurrent mobile transactions, concurrency control techniques (CCT) happen to be very difficult. Due to the properties of Mobile databases e.g. inadequate bandwidth, small processing capability, unreliable communication, mobility etc. existing mobile database CCTs cannot employ effectively. With the client-server model, applying common classic pessimistic techniques of concurrency control (like 2PL) in mobile database leads to long duration Blocking and increasing waiting time of transactions. Because of high rate of aborting transactions, optimistic techniques aren`t appropriate in mobile database as well. This paper discusses the issues that need to be addressed when designing a CCT technique for Mobile databases, analyses the existing scheme of CCT and justify their performance limitations. A modified optimistic concurrency control scheme is proposed which is based on the number of data items cached, amount of execution time and current load of the database server. Experimental results show performance benefits, such as increase in average response time and decrease in waiting time of the transactions

    Towards context-aware ubiquitous transaction processing: a model and algorithm

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    Transaction management for mobile and ubiquitous computing aims at providing mobile users with reliable services in a transparent way anytime anywhere. To make such a vision a reality, transaction processing for the mobile and ubiquitous computing needs to adapt to the runtime environments dynamically. However, most existing mobile transaction models do not consider the context-based transaction management. In this paper, we propose a context-aware transaction model and context-driven coordination algorithms. They are built on an event-context-action mechanism, enabling the transaction processing to adapt well to dynamically changing transaction context. The simulation results have also demonstrated that our model and algorithms can significantly improve the successful commit ratio under unstable context conditions. © 2011 IEEE.published_or_final_versionThe 2011 IEEE International Conference on Communications (ICC), Kyoto, Japan, 5-9 June 2011. In IEEE International Conference on Communications, 2011, p. 1-

    Uniparallel Execution and its Uses.

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    We introduce uniparallelism: a new style of execution that allows multithreaded applications to benefit from the simplicity of uniprocessor execution while scaling performance with increasing processors. A uniparallel execution consists of a thread-parallel execution, where each thread runs on its own processor, and an epoch-parallel execution, where multiple time intervals (epochs) of the program run concurrently. The epoch-parallel execution runs all threads of a given epoch on a single processor; this enables the use of techniques that are effective on a uniprocessor. To scale performance with increasing cores, a thread-parallel execution runs ahead of the epoch-parallel execution and generates speculative checkpoints from which to start future epochs. If these checkpoints match the program state produced by the epoch-parallel execution at the end of each epoch, the speculation is committed and output externalized; if they mismatch, recovery can be safely initiated as no speculative state has been externalized. We use uniparallelism to build two novel systems: DoublePlay and Frost. DoublePlay benefits from the efficiency of logging the epoch-parallel execution (as threads in an epoch are constrained to a single processor, only infrequent thread context-switches need to be logged to recreate the order of shared-memory accesses), allowing it to outperform all prior systems that guarantee deterministic replay on commodity multiprocessors. While traditional methods detect data races by analyzing the events executed by a program, Frost introduces a new, substantially faster method called outcome-based race detection to detect the effects of a data race by comparing the program state of replicas for divergences. Unlike DoublePlay, which runs a single epoch-parallel execution of the program, Frost runs multiple epoch-parallel replicas with complementary schedules, which are a set of thread schedules crafted to ensure that replicas diverge only if a data race occurs and to make it very likely that harmful data races cause divergences. Frost detects divergences by comparing the outputs and memory states of replicas at the end of each epoch. Upon detecting a divergence, Frost analyzes the replica outcomes to diagnose the data race bug and selects an appropriate recovery strategy that masks the failure.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/89677/1/kaushikv_1.pd

    Optimistic replication

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    Data replication is a key technology in distributed data sharing systems, enabling higher availability and performance. This paper surveys optimistic replication algorithms that allow replica contents to diverge in the short term, in order to support concurrent work practices and to tolerate failures in low-quality communication links. The importance of such techniques is increasing as collaboration through wide-area and mobile networks becomes popular. Optimistic replication techniques are different from traditional “pessimistic ” ones. Instead of synchronous replica coordination, an optimistic algorithm propagates changes in the background, discovers conflicts after they happen and reaches agreement on the final contents incrementally. We explore the solution space for optimistic replication algorithms. This paper identifies key challenges facing optimistic replication systems — ordering operations, detecting and resolving conflicts, propagating changes efficiently, and bounding replica divergence — and provides a comprehensive survey of techniques developed for addressing these challenges
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