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Online algorithms for scheduling transactions on python software transactional memory

机译:用于在python软件事务存储器上调度事务的在线算法

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Designing online transaction scheduling algorithms is challenging because one needs to reconcile three opposing requirements: (i) they should be fast, (ii) they should minimize make span and maximize throughput, and (iii) they should produce conflict-free transaction schedules. In this paper we present four online transaction scheduling algorithms, namely, RR, ETLB, AC, and AAC algorithm, we prove their correctness and time bounds, and we conduct a theoretical analysis of the transaction schedules they produce, using three different workloads (RDW, CFW, and WDW). Finally, we compare various features of the four algorithms. The results are as expected, as we go from RR, over ETLB and AC, to AAC algorithms, the quality of the resulting schedules increases at the cost of increase of algorithm’s time complexity.
机译:设计在线交易调度算法具有挑战性,因为需要调和三个相对的要求:(i)它们应该是快速的;(ii)应该最小化制造跨度和最大化吞吐量;(iii)他们应该产生无冲突的交易调度。在本文中,我们提出了四种在线事务调度算法,分别是RR,ETLB,AC和AAC算法,我们证明了它们的正确性和时限,并使用三种不同的工作负载(RDW)对它们产生的事务调度进行了理论分析。 ,CFW和WDW)。最后,我们比较了四种算法的各种功能。从RR,到ETLB和AC,再到AAC算法,结果都是预期的,结果调度的质量提高了,但代价是算法的时间复杂度增加了。

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